the scandinavian journal for humanandapplied sciences

THE SCANDINAVIAN JOURNAL FOR HUMANAND

APPLIED SCIENCES

The Scandinavian Journal for Human and Applied Sciences , Issue(3), N.(1)

1The Scandinavian Journal for Human and Applied Sciences , Issue(3), N.(1)

Index Using Music As a Mediator to Enhance Group Play in Children With Autism pp.1-9 Adel Abdulla Mohammed , & Samar Adel AbdullaSelf-knowledge and Self-regulation of writing in Students with Learning Disabilities: Review and Instruction. pp10- 35

Raquel Fidalgo, Patricia Robledo, & Mª Lourdes Álvarez

Emotional Intelligence and Ways of Coping among college Students pp 36-46Gamal Al Sayed Tofaha, The Effect Of The Jigsaw Technique On Prospective Teachers’ Achievement pp 47-60 Kerim GÜNDOĞDU, Ceyhun OZAN., Adnan TAŞGIN

A third generation personality test pp 61- 75Lennart SjöbergRelationship Between Senior Secondary School Students’ Computer Literacy Skill And Science Achievement pp 76- 87 Olatoye, R.A. , E. Mosunmola Aanu Communication Skills In Children With Autism: The Effect Of The Social Stories Technique PP88- 104 Mohamed Ali , AbdullhamidUsing Computerized Games As A Computer- Assisted Instruction Format To Enhance Helping Behaviour In Kindergartners At- Risk For Learning Disabilities pp105-117 Adel Abdulla MohammedThe effects of learning- styles intervention on achievement in and attitudes towards Mathematics in elementary school students with learning disabilities pp 118-126Mourad Ali Eissa


Using Music As a Mediator to Enhance Group Play in Children With Autism

Adel Abdulla Mohammed ,PhD. Samar Adel Abdulla Abstract

Children with autism often show a heightened interest and response to music as most of them respond positively to it which in turn makes music an excellent therapeutic tool to meet their needs, and promote learning. It can also provide opportunities for positive interactions,


and communication. This study investigated the effectiveness of music therapy on enhancing the group play in children with autism. Participants were eight 10- 12 year- old- children from Zagazig, Egypt. They were divided into two matched groups (experimental & control) with 4 participants each. Experimental method was used, and the results indicated that use of music therapy increased group play. It is concluded that music has a strong effect on children with autism as it could help modify their social behaviors.

Keywords; Music therapy, Group play, Autism.

Introduction Autism is a pervasive developmental disorder characterized by severe disturbance in the child`s cognition, social interaction, communication, and affective sharing that produces widespread complication of the developmental process. It also causes restricted, repetitive, and stereotyped behaviors, all starting before a child is three years old ( DSM- IV- TR, 2000). Furthermore, children with autism always play alone, but they exhibit a severe impairment in interpersonal or social play (Hallahan& Kauffman, 2007). Although their sensory responses are often extreme, most of children with autism often show a great and deep interest in music as a basic human response and a non-threatening way to assist themselves experience outside social stimuli. This in turn makes most of them respond positively to it, and makes music itself an excellent therapeutic tool to develop positive interactions (Kern et al., 2007).

Purpose of the Study The purpose of this study was to develop a music therapy program to be used with children with autism, and to examine the effectiveness of such a program on enhancing social or group play in those children. A secondary purpose of the study was to examine the continuing effectiveness of the program used during the follow- up period.

Literature Review

The term " autism " is often used to refer to a pervasive developmental disorder reflecting a concomitant intellectual and social impairment, and a type of autism spectrum disorder (Mohammed, 2008). Children with autism should prior to three years of age have a developmental delay in either language, social interaction, or play. They should meet six at least of the DSM-IV-TR (2000) autism criteria which require that a child meet at least two from the four criteria of social behavior as indicated, at least one out of the 4 language and communication criteria indicated, and at least one from the other 4 criteria indicated for activities and interests. Hence, individuals with the diagnosis of autism may display qualitative impairments in social


interaction and communication, and often manifest restricted repetitive and stereotyped patterns of behavior, interests and activities. Delays and/or abnormal functioning usually occur before age 3 and may be marked by a lack of symbolic or imaginative play as well (DSM- IV-TR, 2000).

On the other hand, autism is a complex condition that impedes children’s spontaneous development of reciprocal social interaction, communication, play and imagination. Despite opportunities for play, these children do not naturally acquire capacities to pretend and coordinate social activities with other children. Also, it is characterized by abnormal or absent play which makes the assessment of play skills useful in the clinical diagnosis of autism because the development of play is thought to reflect a sequential growth of cognitive skills (Kendall, 2000). The development of play behaviors reflects a growth in cognitive abilities. So, it is often related to symbolic functioning, pretense and substitution, or social interaction (Mohammed, 2008). MacAlpine (1998) described a system for the development of play in children with autism and developmentally delayed peers. Such a system is not related to age and was developed through observations of free play. It consists of four sequential levels of play (sensory play, exploration of change, social representational play, and role play), with a series of increasingly complex stages within each level. These stages represent a child's ability to explore and understand objects and experiences that are increasingly more complex.

Problems conveying and interpreting social-communication cues often make it difficult for children with autism to join peers in play (Hallahan& Kauffman, 2007). Attempts to socialize are often subtle, obscure or poorly timed and mistaken as signs of deviance or limited social interest. Many children appear to spend inordinate amounts of time alone pursuing many repetitive and unimaginative activities. Without appropriate intervention, they will be at high risk for being excluded from their peer culture and still leading solitary play instead (Kendall, 2000). Since play's significance is far reaching as a social, cultural, and developmental context through which children acquire symbolic capacities, interpersonal skills and social knowledge, opportunities for children with autism should be enhanced to become competent in play with peers making use of the strengths of those children (El- Ghoroury& Romanczyk, 1999).

Children with autism often exhibit a high level of preference for the music modality and show little deficit in processing musical components although they may have processing difficulties in non-musical areas. Because music is processed in both hemispheres of the brain, music can stimulate cognitive functioning and may be used for remediation of some speech / language skills (Heaton et al., 1998) for Brown et al. (2003) speculate that the genes that underlie absolute pitch may be among the genes that contribute to autism. Musical instruments and interactive songs are presented to address turn-taking, cooperative interaction, and other social skills including learning and role playing "social stories" (Brownell, 2002). Individualized tapes are often made for additional home practice of skills (Kern et al., 2007). Many individuals with autism demonstrate a highly accurate memory for song lyrics,


increased initiation of singing compared with speaking, and significant increases in attention, motivation, and emotional engagement during music activities (Braithwaite& Sigafoos,1998).

Music Therapy is the unique application of music to enhance positive changes in human behavior. It is an allied health profession utilizing music as a tool to encourage development in social, emotional, cognitive, and perceptual-motor areas (Mohammed, 2008). Music Therapy has a wide variety of functions with the children with disabilities in medical, institutional and educational settings. Music is effective because it is a nonverbal form of communication, a natural reinforcer, immediate in time, and provides motivation for practicing nonmusical skills. Most importantly, it is a successful medium because almost everyone responds positively to at least some kind of music (Staum, 2008).

Generally speaking, music is particularly useful to children with autism because of its nonverbal, and non threatening nature. In such a way, music activities are designed to support the objectives of the child as observed or indicated by a professional where many activities might be used to meet the child's need to socially interact with others, and reduce social withdrawal (Kern& Aldridge, 2006; Mohammed, 2008). In such a way, musical games might be used to foster this interaction. Eye contact might be encouraged with imitative clapping games near the eyes or with activities which focus attention on an instrument played near the face. Preferred music may be used for social behaviors like sitting in a chair or staying with a group of other children in a circle which may enhance the development of social or group play.

The literature about persons with autism show music and music therapy techniques to have significant, and positive influences in the treatment of autism as participation in music is a non-threatening way to allow the individual to experience outside stimuli. Preliminary findings of music therapy for persons with autism show potential for interactive and individualized music strategies to enhance areas such as communication and socialization (Allgood, 2005), modify social behaviors (Brownell, 2002), and improve communicative behaviors through improvisation (Edgerton, 1994). Findings also show that it could improve children’s peer interaction, social interaction of children, facilitate their play and involvement with peers (Kern & Aldridge, 2006), and Interrupt patterns of isolation and social withdrawal, and enhance socio-emotional development (Thaut, 1984). It could also facilitate verbal and nonverbal communication, decrease behaviors characteristic of disturbed perceptual and motor functioning, enhance appropriate and coordinated perceptual and motor development, and facilitate creative self-expression and promote emotional satisfaction (Nelson et al. 1984). Furthermore, it helped improve self- care activity performance ( Kem et al., 2007), highly affected imitation of sign and speech, and the development of language (Buday, 1995), and improved the ability to identify and remember single notes (Heaton et al., 1998). Finally, it affected pitch memory, and labeling and could facilitate performance on musical disembedding tasks (Heaton, 2003),


Hypotheses;

The present study tries to answer four questions manipulated in the form of the following hypotheses :

1. There are statistically significant differences between mean ranks of experimental and control groups in the post- test of group play level favoring the first.

2. There are statistically significant differences between mean ranks of pre- and post- test of group play level for experimental group favoring the post- test.

3. There are no statistically significant differences between mean ranks of pre- and post- test of group play level for control group.

4. There are no statistically significant differences between mean ranks of group play level in post- test and follow- up for experimental group

Methodology

Participants;

Participants are eight 10- 12 year- old- children with autism from Zagazig Social Rehabilitation Center at Zagazig city situated in Sharkiya Governorate, Egypt, with mean age of 10.67 years, and SD of 2.02 years. They were divided into two equal groups ( experimental & control ) with 4 participants each. They were also matched in age, IQ and in group play level as shown in table (1). A process of informed consent was used to make sure that parents of the participants know what would happen in the experiment and understand that they were allowed to quit the experiment at any time, and that no harm would be done to the participants.

Table 1, Results indicating the two groups are matched ( n1= n2 = 4 )

Variables Group Mean rank

Sum of ranks U Z Sig.

Chronolog. Age

ExperimentalControl

4.384.63

17.5018.50

7.50 - 0.149 N. Sig.

Intelligence ExperimentalControl

4.005.00

16.0020.00

6.00 - 0.607 N. Sig.

Group Play Level

ExperimentalControl

4.134.88

16.5019.50

6.50 - 0.500 N. Sig.


Instruments;

Instruments used by authors in this study were; 1) The Arabic version of Gadard Scale for Intelligence was used to select

participants without any statistically significant differences in IQ .

2) Autism Diagnostic Interview- Revised (ADI- R) as a semistructured parent interview was used to make sure that participants from the Social Rehabilitation Center meet the criteria for autism.

3) A scale for group play tasks was developed by the authors where participants were anticipated to perform the tasks included in a group basis. It was used to assess each participant`s level of group play which was determined in the light of the scores a participant gets. Depending on observation, two raters assessed and scored each one`s participation in the tasks included at pre- test, post- test, and follow- up evaluations. Hence, 12 tasks were developed to constitute the whole scale with 3 options for every task representing (yes, to some extent, and no), and ranging in scores from zero ( for not being able to group play) to 2 (perfectly group plays ). Therefore, the scores dedicated for the scale as a whole ranged from zero to 24, and the higher the scores a participant gets, the better. To ensure reliability of the scale it was re administered (n = 20 participants other than those of the final sample) two weeks after the first administration(r = 0.603 > 0.01 ), and results of internal consistency indicated that ( r ) values for the correlations between the item- task scores ranged from 0.417 > 0.05 – 0.623 > 0.01 . To test the scale validity, the sociability subscale from Autism Treatment Evaluation Checklist ATEC was used as a criterion, and ( r ) value was 0.611 > 0.01 .

Procedure

A music therapy program of seventy two, 4- times- a week sessions, each of which lasts for 30 minutes, was developed making use of preferred music in five social activities as musical games i.e. (1) passing a ball back and forth to music, (2) playing sticks and cymbals with another person, (3) what in the Arabic folk we call musical chairs, (4) playing with the other children as a group in a circle, and (5) imitative clapping game near the eyes so as to enhance the development of social or group play. Participants were trained by both authors (individually then in groups) to perform these activities or games according to the components or the constituents contained. The program consisted of three main phases of which the first contained 6 sessions, and aimed to create familiarity between both authors and participants in addition to qualifying them to receive training determined through reducing their inattention. The second phase in which training was presented through out 60 sessions was introduced with 12 sessions for each activity or group play using modeling, rehearsals, manual guidance, repetition, and reinforcement. The final stage aimed to make quick revision on the constituents contained using the 5 group games in 6 sessions with one session for each game whereas the


last session was general. To make sure that the program developed by the authors was effective, it was implemented in a pilot study of three participants other than those of the final sample of the present study, and the results indicated that all 3 participants improved in the post- test evaluation as W = 0.00 > 0.05 indicating the effectiveness of the program used.

Research Method;

Experimental method was used with the music therapy program as an independent variable, and group play as a dependent one. The experimental design of 2 groups ( experimental& control ) was used.

Results

Table 1, U, W,& Z values for the differences between experimental and control groups in all measurements of group play level

Measurement&Group Mean Mean

rankSum of ranks

U W Z Sig.

Post- test ExperimentalControl group

11.436.21

6.502.50

26.0010.00

0.00 10.00 - 2.323 0.01

Experimentalgroup

Post- testPre- test

11.436.05

6.502.50

26.0010.00

0.00 10.00 - 2.337 0.01

Control group Post- testPre- test

6.216.13

4.754.25

19.0017.00

7.00 17.00 - 0.300 N. Sig.

Experimentalgroup

Post- testFollow- up

11.4311.52

4.134.88

16.5019.50

6.50 16.50 - 0.438 N. Sig.

Discussion

To examine the 4 hypotheses Mann- Whitney (U), Wilcoxon (W),& Z values were calculated, and the results indicated the effectiveness of the music therapy program as there were statistically significant differences between experimental and control groups in post- test of group play level favoring the experimental group as U, W,& Z values were all > 0.01. There were also similar statistically significant differences between pre- and post- test of group play level for the experimental group favoring the post one as U, W,& Z values were all > 0.01 . The results did not indicate the presence of any statistically significant differences between pre- and post- test of group play level for the control group nor between post- test and follow- up evaluations of group play level for the experimental group as U, W,& Z values were all < 0.05. Such results might be interpreted on the basis that music therapy in general, and musical games and activities in particular might be used to remediate the social deficiencies of the children with autism as it helps to modify their social behaviors, and improve communicative behaviors (Brownell, 2002; Edgerton, 1994). In line with the results indicated by the present study which demonstrated the positive effect of music on the social


aspect in those children which led to the significant progress of their social and group play, music provides concrete, multi-sensory stimulation (auditory, visual, and tactile), and the rhythmic component of music is very organizing for the sensory systems of individuals diagnosed with autism (Staum, 2008). As a result, auditory processing and other sensory-motor, perceptual/ motor, gross and fine motor skills can be enhanced through music therapy. So, when participants in the present study were trained to share the group or social activities included as musical games depending on such rhythmic component of music whether in passing the ball back and forth to music, playing sticks and cymbals with another person, musical chairs game, playing with the other children as a group in a circle, or imitative clapping game near the eyes, those skills were enhanced by music, and led to enhance the development of social or group play in all 4 participants of the experimental group despite their uneven progress. At last they could, to a reasonable extent, play together even though 2 of them were not able to speak at a similar extent, and another one was echolalic. Therefore, we could not use meaningful word phrases and songs presented with various cues whether visual or tactile so as to facilitate this process even further, nor sing simple phrases set to a familiar melody with full rhythmic and harmonic accompaniment, and the children playing together with various objects while singing which we considered limitations in the present study .

Using music with the children with autism in the present study facilitated learning, social play, relationships, and communication because it could capture and help maintain their attention. Being highly motivating and engaging, music might be used as a natural "reinforcer" for desired responses. It could stimulate children to reduce negative and/or self-stimulatory responses and increase participation in more appropriate and socially acceptable ways. It also assisted in the development of nonverbal communication (Edgerton, 1994) which we noted in the study. Music therapy could also augment the interpersonal timing and reciprocity in shared play, turn-taking, listening and responding to another person (Buday, 1995) which made participants share positively in the targeted social or group play.

Hence participants in the experimental group, who received the music therapy program have become able to group play or engage more in social play while their control peers were still unable to do so. This interpretation explained the presence of statistically significant differences between both groups in the first hypothesis favoring the experimental group, and the presence of similar differences between pre- and post- test for the experimental group in the second hypothesis favoring the post one . Meanwhile, because the control group did not receive the music program as the experimental one, no change has occurred, and this fact indirectly supported the importance and effectiveness of the program used. Also, the absence of statistically significant differences between post- test and follow- up for the experimental group went back to what happened during the last phase of the program as the participants were retrained to group play in various musical activities which led to transmission of training through such a period without drawbacks.


Finally, it was recommended to use music, music therapy, or musical activities as a therapeutic tool to help children with autism acquire the socially desired patterns of behavior, and reduce the socially undesirable ones which may in turn help them to communicate with others.

References

Allgood, N. (2005), Parents’ perception of family-based group music therapy for children with autism spectrum disorders. Music Therapy Perspectives, 23 (2), 92-99.

American Psychiatric Association (2000), Diagnostic and Statistical Manual of Mental Disorders ( 4th ed.), Text Revision. DSM-IV- TR. Washington, DC: author.

Braithwaite, B. & Sigafoos, J. (1998), Effects of social versus musical antecedents on communication responsiveness in five children with developmental disabilities. Journal of Music Therapy, 35 (2), 88-104.

Brown, W.A., Cammuso, K., Sachs, H., Winklosky, B., Mullane, J., Bernier, R., Svenson, S., Arin, D., Rosen-Sheidley, B., & Folstein, S.E. (2003), Autism-related language, personality, and cognition in people with absolute pitch: results of a preliminary study . Journal of Autism and Developmental Disorders, 33 (2), 163-167

Brownell, M. (2002), Musically adapted social stories to modify behaviors in students with autism: Four case studies. Journal of Music Therapy, 39 (2), 117-144

Buday, E. M. (1995), The effects of signed and spoken words taught with music on sign and speech imitation by children with autism. Journal of Music Therapy, 32 (3), 189-202.

Edgerton, C.L. (1994), The effect of improvisational music therapy on the communicative behaviors of autistic children. Journal of Music Therapy, 31 (1), 31-62

El- Ghoroury, N. H.& Romanczyk, R. G. (1999), Play interactions of family members towards children with autism. Journal of Autism and Developmental Disorders, 29 (3), 335- 344.

Hallahan, D. P.& Kauffman, J. M. (2007), Exceptional learners; Introduction to special education (10th ed.). New York: Allyn & Bacon.

Heaton, P. (2003), Pitch memory, labeling and disembedding in autism .

Journal of Child Psychiatry and Psychology, 44 (4), 543- 551. Heaton, P.; Hermelin, B.; & Pring, L. (1998), Autism and pitch processing: A

precursor for savant musical ability? Music Perception, 15 (3), 291-305.Kendall, P. (2000), Childhood disorders. East Sussex : Psychology Press Ltd. Kern, P., & Aldridge, D. (2006), Using embedded music therapy interventions

to support outdoor play of young children with autism in an inclusive community-based child care program. Journal of Music Therapy, 43 (4), 270-294.

Kern, P., Wakeford, L., & Aldridge, D. (2007), Improving the performance of a young child with autism during self-care tasks using embedded song interventions: A case study. Music Therapy Perspectives, 25(1), 43-51.


MacAlpine, M. L. (1998), Microdevelopment in Autism: The Power of Play. Unpublished Ph.D. Dissertation, University of Texas at Dallas

Mohammed, A. A. (2008), Music Therapy for autistic children. Cairo, Dar al- Rashad (Arabic version).

Nelson, D., Anderson, V.,& Gonzalez, A. (1984), Music activities as therapy for children with autism and other developmental disorders. Journal of Music Therapy, 21 (3), 100- 116.

Staum, M. J. (2008), Music therapy and language for the autistic child. www.autism.com

Thaut, M.H. (1984), A music therapy treatment model for autistic children. Music Therapy Perspectives, 1 (4), 7-13.

AUTHORSDr. Adel Abdulla Mohammed, Professor of Special Education, Faculty of Education, Zagazig University, Zagazig, Egypt. PO Box 532 Zagazig, Egypt. E-mail; [email protected]. Samar Adel Abdulla, Demonstrator of Music, Faculty of Specific Education, Zagazig University, Zagazig, Egypt.

Self-knowledge and Self-regulation of writing in

Students with Learning Disabilities:

Review and Instruction

Raquel Fidalgo, Patricia Robledo, & Mª Lourdes Álvarez

University of León, Spain

Correspondence should be directed to Raquel Fidalgo, Psychology, Sociology and Philosophy Department. University of León, Spain. E-mail: [email protected]; Campus de Vegazana s/n, 24071 – León, Spain.


mailto:[email protected]


http://www.autism.com/

Abstract

Nowadays, it is accepted that metacognition, self-knowledge and self-regulation, play an important role in the development of writing competence. At the same time, several research studies have shown that students with learning disabilities have serious limitations in their metacognitive writing knowledge and in their self-regulatory processes. Given the importance of metacognition in the development of writing competence and the constraints on metacognition in the writing of students with learning disabilities, the purpose of this paper is to provide teachers with useful writing strategies and techniques based on empirical researches which can be implemented in school settings to develop both the metacognitive dimensions: self-knowledge and self-regulation of writing, with a view to improving the written compositions of students with learning disabilities.

Key Words. Writing Knowledge, self-regulation, learning disabilities, writing composition, writing instruction.

The last decades have supposed a great development in the research on writing from cognitive perspective, which has meant considerable progress in the understanding of the cognitive processes and personal variables involved in writing (Alamargot & Chanquoy, 2001; MacArthur, Graham, & Fitzgerald, 2006). In this sense, writing is recognized as a complex and demanding task which would answer to a large set of higher and lower order cognitive processes, which must be activated and coordinated recursively during the entire writing process.

The writing complexity supposes that the development of writing competence makes great demands on one’s cognitive resources, requiring extensive self-regulation and attention control in order to manage the writing environment, the constraints imposed by the writing topic, and the processes involved in composing a text (Graham & Harris, 2000; Kellogg, 1987; Ransdell & Levy, 1996; Zimmerman & Risemberg, 1997). For this reason, specific instruction in composition writing, that develops metacognitive knowledge and self-regulation dominance in writing, is necessary to achieve competence in writing. In the area of writing research, actual theoretical models (Alamargot & Chanquoy, 2001) and empirical studies recognize that metacognition has an important role in the development of students´ writing competence.

In general, the complex nature of writing supposes that development in writing competence is a demanding task for all students, and especially for students who have some learning disabilities (LD).

A substantial body of research has reported on the limitations and difficulties in the written compositions of students with LD (Troia, 2006). In general, the texts of these students are shorter, poorly organized, more incomplete, with more superfluous data, with mistakes in structure, have


greater incidence of incoherence and are poorer in overall quality compared to the compositions of their peers without LD (Englert & Thomas, 1988; Graham, 1990; Graham, Harris, MacArthur, & Schwartz, 1991; MacArthur & Graham, 1987; Nodine, Barenbaum, & Newcomer, 1985; Thomas, Englert, & Gregg, 1987). Some other features of the written products in students with LD reflect the greater difficulties in the production of sentence structures, showing a minor number of sentences, or sentence combining links or shorter sentences (Gregg, 1986; Gregg, Hoy, McAlexander, & Hayes, 1991). Furthermore, the findings of several previous research studies have reported that students with LD make more spelling, capitalization and punctuation mistakes in their compositions than their peers without LD (Fulk & Stormont-Spurgin, 1995; Graham et al., 1991; MacArthur, Graham, Schwartz, & Schafer, 1995). In addition, their texts are less legible and more uneven than those written by normally achieving students (Graham & Weintraub, 1996; MacArthur & Graham, 1987).

A possible explanation for the difficulties of students with LD have in writing may be found in their limitations as regards their metacognition of writing, that is, in the knowledge and self-regulation strategies of writing. Many students with LD possess limited metacognitive awareness of domain-specific knowledge, skills and strategies, and procedural knowledge about how to apply, self-regulate and control them for effective and efficient task performance (Troia, 2002; 2006).

A review of empirical studies has shown that students with LD generally demonstrate less metacognitive awareness of the writing process, and tend to focus on the concrete demands of tasks rather than on the more obscure evaluative and self-awareness skills demanded by metacognitive processes (Butler, 1998c).

As for the metacognitive knowledge of writing, syntheses of research show that students with LD, in comparison to their normally achieving peers, have a less mature conceptualization of what composing involves (Graham, Schwartz, & McArthur, 1993), and a more incoherent awareness of the writing process (Wong, Wong, & Blenkinsop, 1989). They are frequently less knowledgeable about how to develop and organize ideas, control and regulate the writing process, and monitor the quality of the text produced. They also have more immature and incoherent conceptions of the writing process and deficient knowledge as concerns text structure (Englert, Raphael, Fear, & Anderson, 1988). Their knowledge of writing is mainly focused on the secretarial or mechanical aspects of writing, and they give more importance to the lower-order cognitive processes of writing, such as, spelling or handwriting than the higher level cognitive processes of writing (García & Fidalgo, 2008).

On the other hand, as for the self-regulation of writing, students with LD tend to engage in a “knowledge telling” writing strategy (Bereiter & Scardamalia, 1987), and employ a more directed process without planning or revising (García & Fidalgo, 2008), and have difficulty with substantive revision (De la Paz, Swanson, & Graham, 1998; García & Arias-Gundín, 2004;


Graham, 1997; MacArthur, Graham & Schwartz, 1991; Thomas, Englert & Gregg, 1987). Students with LD devote significantly less time to the writing process, and specifically, in the editing and revision processes opposite to the students without LD. Furthermore, specifically, students with LD focus on the revising process in localizing and correcting only the mechanical aspects of their compositions, such as, spelling, changing words or phrase selections (Graham, 1997; MacArthur & Graham, 1987; McCutchen, 1995). They do not proceed to a revision of the conceptual and linguistic characteristics of the text according to its audience or purpose. In addition, LD students show a significantly lower number of self-regulation strategies in the writing process than their peers without LD (Fidalgo & García, 2008).

Therefore, two important goals in writing instruction for students with LD are to develop a more substantive knowledge of writing process, and to help them develop a more self-regulated approach to composing, specifically as concerns the cognitive strategies for planning and revising text, for the purpose of improving their writing competence.

From this point of view, in the last two decades, there has been a rapid growth and development of cognitive and self-regulation strategy instruction studies in students with LD (Graham & Harris, 2003; Wong, Harris, Graham, & Butler, 2003). There are a considerable number of intervention research studies based on different instructional models, such as, the Self-regulated Strategy Development Model (Graham & Harris, 2003; Harris & Graham, 1996; Eissa, 2009; in press), the Cognitive Strategy Instruction in Writing Model (Englert et al., 1991; Englert, Raphael & Anderson, 1992), the Strategy Content Learning Instruction Model (Butler, 1994; 1995; 1998b), or the Genre-Specific Writing Strategies Research study (Wong, Butler, Ficzere, Kuperis & Corden, 1994; Wong, Butler, Ficzere & Kuperis, 1996; 1997); all of which provide strong evidence of the efficacy of this type of metacognitive instruction in the improvement of writing performance in students with LD.

In general, these instructional models have been equally effective as a literature review has revealed (see the reviews and meta-analysis by Fidalgo & García, 2007; 2008; Graham, 2006; Graham & Harris, 2003; Wong et al., 2003). This could be explained be the fact that all of these models share key instructional features and techniques which may be the true cause of the improvement in the written competence in students with LD. Some of those strategies and techniques are reported in this paper.

The purpose of this article is to provide knowledge about some of the specific strategies and techniques to improve both dimensions of writing metacognition in students with LD, whose efficacy in developing writing competence of students with LD has been proved in the empirical review of instructional writing studies (Fidalgo & García, 2007; Graham & Harris, 2003; Wong et al., 2003). Furthermore, some specific examples or materials used specifically in previous researches are explained (García & Fidalgo, 2006a;


Torrance, Fidalgo, & García, 2007). But, first, we describe the background for the two metacognitive dimensions, knowledge and self-regulation used in writing.

Self-knowledge of Writing

Researchers in writing have generally defined metacognition as knowledge of the task and one’s own cognitive resources, and the ability to control and regulate one’s own thinking (Sitko, 1998), and this includes the two complementary dimensions of metacognition: knowledge and regulation of cognition.

Metacognitive knowledge of writing refers to what individuals know about their own cognition or about cognition in general. Within this dimension, three different kinds of metacognitive knowledge can be differentiated: declarative, procedural and conditional knowledge (Schraw, 2001). Declarative knowledge refers to what is known about oneself as a learner and about the influential factors of human thinking (Schraw, 2001). It corresponds with the data stored in one’s long term memory (Hacker, 1998). In writing, declarative knowledge is related to questions such as: what kind of writing strategies do you know?, what kind of textual genres do you know?, or what is planning in writing? The second type, procedural knowledge, refers to the knowledge about how to do things (Schraw, 2001). It can be described as the awareness of thought processes or the knowledge of the methods needed to achieve goals and the knowledge of how skills work and how they are to be applied. This knowledge is necessary to apply declarative knowledge effectively (Montague, 1992). In writing, procedural knowledge refers to questions such as, how do you apply different writing strategies?, how do you develop the writing process?, how do you plan a text?, or how do you revise a text? Finally, conditional knowledge refers to knowing when and why to use declarative and procedural knowledge (Schraw, 2001; Schraw & Moshman, 1995), or where to use them (Biggs, 1999), that is, their appropriate use according to the time, place and moment. In writing, conditional knowledge refers to when to use a specific writing strategy, which writing strategies are most suitable for different kinds of texts, why to use a specific writing strategy at a specific moment of writing process, or when and why to use a specific textual genre.

Specifically in writing, it is possible to establish another qualitative classification of metacognitive knowledge which is very important for differentiating the writing knowledge of students with and without LD. This classification refers to the knowledge of different cognitive processes involved in composition writing. From this point of view, it is possible to distinguish between the substantive or higher-order cognitive processes and the mechanical or lower-order cognitive processes in writing. Substantive ones include processes such as: generation of ideas, planning, or organization of ideas, which refers to a substantive metacognitive knowledge of writing. On the other hand, the mechanical processes include those such as: the mechanics of spelling, punctuation or the neatness of handwriting, which


corresponds to the mechanical metacognitive knowledge of writing (Graham et al., 1993; Wong, 1999).

Knowledge of substantive processes is more important and relevant than knowledge of mechanical processes for achieving writing competence. Several research studies have established the greater importance of substantive writing processes in the development of writing skills and in the achievement of a higher quality composition. However, teachers sometimes tend to overemphasize the mechanical writing processes, and similarly, students with LD also overemphasize these processes. For this reason, writing instruction should foster students’ substantive knowledge of writing, which involves focusing on the higher order cognitive processes of writing, in order to improve their composition writing, specifically in LD students.

Self-regulation of writing

The second dimension of metacognition, self-regulation of writing, refers to a set of procedures or strategies that help students to control and regulate their learning (Schraw, 2001; Schraw & Moshman, 1995). Self-regulation can be seen as the voluntary control people have over their own cognitive processes.

There are a considerable number of regulatory strategies described in the literature (Schraw & Dennison, 1994). Specifically, Zimmerman (2000) proposes that self-regulatory processes or strategies fall into three cyclical phases. The first phase is named forethought which refers to the influential processes that set the stage and precede the action of writing. The second phase is the performance or volitional control which involves those processes that occur during the motoric efforts and which affect both attention and action. The third phase is called self-reflection and involves those processes that occur after the performance efforts and influences the forethought phase in subsequent motoric efforts.

In the forethought phase there are two distinctive but closely linked categories of self-regulation processes, task analysis and self-motivational beliefs. The task analysis category comprises two types of self-regulation processes: 1) goal setting, which refers to deciding the specific outcomes of learning or performance; 2) strategic planning which refers to the purposive personal processes and actions directed at acquiring or displaying a skill. For a skill to be mastered or performed optimally, learners need methods or strategies that are appropriate for the task and the setting. The other category in the forethought phase, self-motivational beliefs includes a set of personal variables such as self-efficacy, outcome expectations, intrinsic interest or valuing, and goal orientation; which are linked to self-regulation strategies, because self-regulatory skills are of little value if a person cannot motivate themselves to use them (Zimmerman, 2000).

On the other hand, in the performance or volitional control phase there are two major types of performance or volitional control processes: self-


control and self-observation. The first includes a set of self-regulation processes, such as self-instruction, imagery, attention focusing and task strategies. Secondly, the self-observation processes refer to a person’s tracking of specific aspects of their own performance, the conditions that surround it, and the effects that are produced (Zimmerman, 2000). It is related to monitoring strategies which refer to the awareness of the writing task during its execution and the control of the processes.

Finally, the self-reflection phase includes two self-reflective processes: self-judgment and self-reactions. Self-judgment concerns self-evaluating one’s performance according to an evaluation criterion, such as previous performance, peer’s performance, normative performance, or mastery; and attributing causal significance to the results and the process. As for self-reactions, this category includes two processes: 1) self-satisfaction which concerns the perceptions of satisfaction or dissatisfaction regarding one’s performance; 2) adaptative or defensive inferences, which are conclusions about how one needs to alter his or her self-regulatory approach during subsequent efforts to learn or perform. Specifically, Table 1 summarizes the self-regulation processes, strategies and examples of self-instructions included in all the cyclical phases of self-regulation and which are employed in composition writing.

Table 1. Self-regulation processes, strategies and self-instructions

in writing during the three cyclical phases

Phase Sub-processes Strategies Self-instructionsForethought Task Analysis

Goal settingTo think about the purpose or aim of the textTo set oneself a goal in writing

What is the aim of this writing task?…then, what is the first thing that I must do?The first…The second…I have to remember the planning strategy…. Always, I must remember the goal of the taskI have to remember the revising strategy …

To think about the audience of the textTo aim the text at a specific audienceTo decide the features and elements of writing taskTo determine the required effort for the writing task

Strategic planning To think about the content of the textTo write a draft or an outlineTo establish an action plan

Self-Motivation BeliefsSelf-efficacy

Personal beliefs about having the means to learn or effectively perform the task

If I follow the steps of the writing strategy I will not have any problemsI feel capable of writing a good textI am sure that I will write a good

Outcome expectations Personal beliefs about the ultimate outcome of the performance


compositionI can master the writing taskNow, there are no texts which I can’t attemptI can apply this knowledge in other subjects and contexts and I will improve my compositions

Motivation Sense of intrinsic motivation

Phase Sub-Processes Strategies Self-Instructions

Performance or

Volitional Control

Self-ControlHelp learners and performers to focus on the task and optimize their effort

To include changes in the outline according to the new requirements of the taskTo bear the aim and goal of the text in mindTo bear the audience of the text in mindTo correctly link the ideas according to needs of the text

Am I following all the steps?Is this idea right? I have to bear the future readers in mindI have to read the text and continuously assess all my ideas Are there enough ideas?This paragraph includes the ideas

that…

Self-ObservationA person’s tracking of specific aspects of their own performance, the conditions that surround it, and the effects that they produce

To frequently read the text during the writing processTo frequently check the writing processes and products

I am going to read the text I have writtenI have to frequently read the text during its composition I did the first step, now the second

step will be…Phase Sub-Processes Strategies Self-

InstructionsSelf-Reflection

Self-JudgmentSelf-evaluation

To remember the aim of the text for assessing itTo read the text as if I were one of the future readersTo assess any mistakes in the textTo make a plan for revising the textTo correct first the substantive mistakes of the text, and then the mechanical mistakes

What must I do when I finish the text?I will achieve a great performanceFirst I must revise…Second I must revise…Is this word right? I am not sure, I’m going to look it up so that I can be sure

Causal attribution To promote internal and variable attributions about the results; the attribution of errors to learning strategies are highly effective in sustaining motivation.

I have made a big effort and I got a good result

I followed the steps and I wrote a great

text

Self-ReactionSelf-satisfactionAdaptative/defensive

To promote perceptions of satisfaction regarding one’s performance according to writing strategies

I am very satisfied My text is great!

My text will get a


good mark

After the conceptualization of metacognition, and its employment in writing, it is then possible to inquire as to how teachers can improve the metacognitive dimensions of writing in students with LD. In this sense, the next section summarizes and exemplifies some techniques to improve the metacognitive dimensions of writing in students with LD, which have demonstrated their effectiveness in previous writing intervention research studies.

How Can I Improve Self-knowledge of Writing in Students with Learning Disabilities?

The first step in the instructional pattern must be the development of the necessary background knowledge so that the learner can later develop the specific cognitive writing strategies and self-regulation procedures of writing. This statement is shared by the majority of instructional models reviewed, such as, the Self-regulated and Strategy Development Model (Harris & Graham, 1996) or the Cognitive Strategy Instruction in Writing Model (Englert et al., 1992).

Effective strategy instruction develops students’ declarative, procedural and conditional knowledge of writing; specifically, it focuses on the substantive knowledge of writing processes. In this sense, metacognitive knowledge of writing can be improved through several techniques, such as, discussion groups and dialogues which aim to promote students’ self-reflection, use a metacognitive knowledge evaluation matrix, and text analysis; whose effectiveness has been demonstrated in research.

Promoting Students’ Self-reflection

In order to improve students’ metacognitive knowledge of writing, providing a direct or explicit instruction program about different kinds of metacognitive knowledge is not sufficient. It is more appropriate to promote students’ self-reflection about their self-knowledge, their gaps and limits. For this reason, teachers should support interactive teacher guided dialogues using techniques, such as, discussion or reflection groups, questioning or brainstorming.

Teachers should ask students to verbalize their emerging understanding about writing. In this sense, they can use simple questions to assess metacognitive knowledge of writing, and this has been used in previous research studies (see Englert, Raphael, Fear, & Anderson, 1988; Fidalgo, Torrance, & García, 2008; Graham & Harris, 1989; Graham et al., 1993; MacArthur, Graham, & Schwartz; 1991; Wong, Wong, & Blenkinsop,


1989; Wray, 1998). Some examples of questions include: what things do you do when you write? Why some people have trouble writing? Is writing composition a hard thing for you to do? Why?

Metacognitive Knowledge Evaluation Matrix

Another effective strategy to increase metacognitive knowledge is the use of metacognitive knowledge evaluation matrices. They have been applied in different instructional researches with optimal results in students both with and without LD, following different patterns of instruction based on the Self-Regulated Strategy Development model and the Social Cognitive Model of Sequential Skills Acquisition model (see Fidalgo, Torrance, & García, 2008; García & Fidalgo, 2006a; Torrance, Fidalgo, & García, 2007).

These matrices promote explicit declarative, procedural and conditional knowledge about each writing process (Schraw, 2001). Through these matrices, students acquire the previous knowledge they need for the subsequent implementation of the specific self-regulation and cognitive strategies of writing. As an example Figure 1 shows the metacognitive knowledge evaluation matrix for the planning, according to Hayes and Flower’s theoretical model of writing (1980). The planning process is related to the purpose and goal of the text and to the draft and outline which guides the writing process. It includes three sub-processes: generating ideas, organizing ideas and goal-setting (Hayes & Flower, 1980).

The metacognitive knowledge evaluation matrix can be used in different ways, and its effectiveness has been empirically ensured (García & Fidalgo, 2006a; Torrance, Fidalgo, & García, 2007). Teachers can ask students to fill in the matrix after the training program to encourage memory and understanding. Another method is to fill in the matrix in a big group session, thus encouraging discussion, self-reflection and dialogue between students and guiding them when it is necessary, or simply through explicit teaching of filling out the matrix.

Figure 1. Metacognitive knowledge evaluation matrix of planning

What is planning? How to plan? When and why to plan?


THE FIRST STEP...

...PLANNING

- It is one of the writing processes.

- It is essential in writing.

- It is the first thing you have to do when you are writing a text.

It includes three actions:- To generate ideas for

the text: retrieving them from long term memory or looking up bibliographic sources.

- To set the aim of the text and the audience.

- To select and organize the content.

You have to plan a text:- When you are

going to write a creative text.

- When you are going to include changes in a text that you are writing

Planning is essential because:

- It guides the rest of writing process

Textual Analysis

Another technique, which has been implemented in previous research studies, such as, Englert’s studies based on the Cognitive Strategy Instruction in Writing Model (Englert et al., 1991; 1992), and concerns an ad hoc textual analysis of the elaborated texts about the different kinds of textual genres or about the same textual genre but with different quality levels.

This textual analysis improves students’ metacognitive knowledge about both the editing process and the written products. This analysis, carried out in a group session, promotes the self-reflection and participation of all students and improves their knowledge about textual genres, their main features, structures and differences, and ways in which the text could be improved, checking correct and incorrect texts, with and without mechanical, substantive or both types of mistakes, etc.

To give an example, in the García and Fidalgo (2006a) interventions four textual genres were trained through specific ad hoc texts. Moreover, in order to foster metacognitive knowledge of textual genres after this textual analysis, the evaluation matrix regarding declarative, procedural and conditional knowledge of textual genre, which is illustrated in Table 2, was employed.

Table 2. Metacognitive Knowledge Evaluation Matrix of Textual Genres

What?

How? When?

Story The first part introduces the characters, the plot, and the setting as to where and when story is told.

The second part develops the plot: what happens first, what characters’ reactions are, what they do, what the

To entertain by telling a story


Argumentative

The first part, an introduction, presents the theme and the purpose of the text.

The second part, the body of the text, includes the statements in favor and/or against a theme.

The third part is the conclusion of the text.

To convince the readers of something

Description

The first part, an introduction, presents the subject of the text.

The second part, the body of the text, organizes a series of attributes and characteristics about the subject.

To describe a series of attributes and characteristics that informs the reader about

the subject.

Compare-contrast

The first part, an introduction presents the topics to be compared and the purpose of the text.

The second part, the body of the text, includes the similarities and differences between the topics along one

or more dimensions.

The last part is the conclusion.

To show two or more topics compared according to their similarities and differences along one or

more dimensions.

How Can I Improve Self-Regulation of Writing in Students with Learning Disabilities?

The majority of students with LD have significant problems in managing, controlling and regulating the writing processes and cognitive demands of the writing task during the writing process. For this reason it is necessary to recognize the value of the different techniques and strategies which develop writing self-regulation in students with LD. Specifically, some of these techniques are: mnemonic devices for the cognitive strategies of writing, cognitive modeling, emulation and the thinking aloud technique. All of them have been proven in different types of self-regulatory and strategic instruction research studies with students with LD (Fidalgo & García, 2006a; Fidalgo & García, 2007; 2008; Graham & Harris, 2003; Wong et al., 2003).

Mnemonic Devices for Cognitive Strategies of Writing

The effectiveness of this technique in improving the writing of students with LD has been demonstrated in a great number of research studies (see, for example, the reviews of the Self-Regulated Strategy Development Model by Graham, 2006, and Graham & Harris, 2003). The technique consists of explicitly teaching specific cognitive composing strategies focusing on the kinds of planning and revising skills that are characteristic of more competent writers.

In general, these cognitive strategies allow students to manage and regulate the complex and higher level set of cognitive processes associated with planning, text production or revision processes, and could prevent a possible cognitive processing overload within the constraints of working


memory (McCutchen, 2000) particularly in students with LD who present distinct deficiencies in working memory (Mercer & Pullen, 2005). The processing demands that writing tasks involve are greater for LD students than for normally achieving peers. Given that, students with LD have to manage and regulate not only the complex set of processes associated with creative writing, but also the processes associated with the transcription process if they have not yet mastered the mechanics of writing (Graham & Harris, 2000).

The promotion of memorizing the metacognitive knowledge of writing is especially important for students who experience learning difficulties. Teachers should use explicit strategies that encourage the retention of the acquired declarative, procedural and conditional knowledge through the use of mnemonic devices or elaboration strategies. Subsequently, two specific writing strategies for planning and revising, which were designed and checked specifically by the authors in previous studies (García & Fidalgo, 2006a; Torrance, Fidalgo, & García, 2007), are presented. For further information, Harris and Graham’s book (1996) offers a great collection of writing strategies, which have also been substantiated previously in their research projects.

The example of one specific writing strategy for planning and writing an essay is named POD+THE VOWELS. This strategy comprises three general steps for planning and writing a text: POD: P = Pick ideas, the first step encourages the writer to generate ideas related to the theme of the text; O = Organize your ideas following the vowels, during the second step students follow a series of genre-specific prompts (the vowels) to organize and structure the content; D = Develop your text, the third step encourages students to use the plans already devised and to continue the planning process while writing; based on the POW strategy used in previous studies by Mason, Harris and Graham (2002). In addition, five specific steps for planning the text are THE VOWELS, in a similar way to when one first learned to write the initial step involved learning the vowels, and its application in writing a text would involve the students thinking that when you start a text the first thing that you have to remember are the vowels. The mnemonic VOWELS (O+A+I+U+E) is used to help students to remember the key words to generate, organize and structure the content in different types of text. The key words in the framework serve as a reminder to generate writing content related to: O = Objective or purpose of the text; A = Audience, suitable content according to the audience of the text; I = Ideas, generation of ideas related to the theme of text; U = United ideas, organization of ideas in a hierarchical structure of primary and secondary ideas; E = Essay draft, to develop the text (García & Fidalgo, 2006a) (See Figure 2).

Alternatively, another specific writing strategy for revising the text was RED, where the mnemonic device highlights the three main steps of the revision process: R = Read the text, students have to read their text several times and in different ways: repeated comprehensive readings where paying attention to the structure, paragraphs, and inter-intra paragraphs links is the objective, and also quick readings, which involves paying attention to the


words and the punctuation of sentences. When students are carrying out the first step of the revision process they have to coordinate the other two sub-processes of evaluating and diagnosing the different aspects of the text: E = Evaluate the different substantial and mechanical aspects of the text, to see if they are right or wrong; and carrying out the necessary tactics D = Do necessary changes.

Figure 2. POD+THE VOWELS planning strategy

WHICH IS THE OBJECTIVE OF THE TEXT?

WHO IS THE AUDIENCE OF THE TEXT?

WHAT IDEAS CAN I WRITE IN THE TEXT?


HOW DO I UNITE THE IDEAS OF THE TEXT?

WHAT ESSAY DRAFT AM I GOING TO FOLLOW IN THE WRITING ?

As for the use of cognitive writing strategies, teachers have to bear in mind that initially they offer a great deal of supporting materials but then gradually reduces their presence in order to promote the autonomous application of the cognitive strategies in the students and their self-regulation. In this sense, first, they can use graphic organizers that offer comprehensive content information about the planning and revising processes. Second, they can use mnemonic charts where the information is reduced as it only gives mnemonic devices (see Figure 2). Finally, students work alone without additional supporting materials. There are different kinds of supporting materials, which have received different names according to the instructional models, such as, think-sheets in Englert’s model (Englert et al., 1991; 1992), or plan and revision sheets (Wong et al., 1996; 1997). Specifically, Figure 3 shows an example of graphic organizers of the RED revision strategy.

It is beyond doubt that students must be guided towards a self-controlled level of self-regulatory competence through the social guidance provided by the teacher or materials. This guidance must be faded out throughout the instruction program to promote the transfer to independent practice of increased self-control and self-regulation. Through this type of supporting materials, they can improve self-awareness, self-regulation and control over their thinking and cognitive processes and can thereby improve their written products.

Together with cognitive strategies, the use of self-questioning or self-instructions during the writing process is effective in guiding students’ performance before, during and after the writing process. This self-dialogue improves self-awareness and self-control over their thoughts and improves the ability to apply and transfer the knowledge and skills students learn. Table 1 highlights different examples of self-instructions according to the different phases of self-regulation processes. Initially, this self-questioning or self-instruction should be said aloud because it permits teachers to provide feedback about the performance; although, it should subsequently become internalized. The teacher’s feedback must reinforce greater effort and persistence on the task, valuing not only the performance that is, the written text, but also the writing process.


Figure 3. Graphic Organizer of the RED Revision Strategy

R READ EEVALUATE DDO

COMPREHENSIVE READING OF THE TEXT, PAYING ATTENTION TO…

...TEXTUAL STRUCTURE

Is there an introduction?

YESNO

ContinueChange it

Is there an organized body?

YESNO

ContinueChange it

Is there a conclusion?YESNO

ContinueChange it

...PARAGRAPHS

Is there an introduction and a concluding paragraph?

YESNO

ContinueChange it

Is there organization between the paragraphs of the text?

YESNO

ContinueChange it

Are the ideas of each paragraph organized?

YESNO

ContinueChange it

...LINKS

Are there links between the ideas of each paragraph?

YESNO

ContinueChange it

Are there inter paragraph links?

YESNO

ContinueChange it

QUICK READING, PAYING ATTENTION TO…

...SENTENCESAre the sentences of the text correct?

YESNO

ContinueChange it

...WORDSAre the words correct?

YESNO

ContinueChange it


...PUNCTUATION

Is the punctuation correct?

YESNO

ContinueChange it

... PRESENTATION

Is the text neatly and clearly written?

YES

NO

Congratulations on your text!Make a neater copy

On the other hand, although the teacher primarily shows examples of pre-formulated questions, it is necessary to bear in mind that self-dialogue and self-questions created by students are more effective, for this reason, teachers should encourage students to create their own questions and to adapt their self-questions to the needs of the specific subject and task. Figure 4 shows a tool for helping the elaboration of students’ own self-instruction in the writing process, whose effectiveness has been demonstrated in previous studies (Graham, 2006; Graham & Harris, 2003; García & Fidalgo, 2006a).

Figure 4. Individual List of Self-Instructions

WHEN I AM WRITING A TEXT…

… MY THOUGHTS BEFORE STARTING MY TEXT ARE...

¡… MY THOUGHTS DURING THE WRITING PROCESS ARE...


… MY THOUGHTS AFTER THE WRITING PROCESS ARE...

… MY FEELINGS AND BELIEFS RELATED TO THE WRITING TASK ARE...

…

Cognitive Modeling

This technique is based on Bandura’s social-cognitive theory (1986) and it refers to the process whereby observers pattern their thoughts, beliefs, strategies and actions, according to those displayed by one or more models (Schunk, 1998). Modeling is an important tool for the acquisition of self-regulation skills and strategies in writing, and to encourage students to transfer their previous procedural knowledge into practice. The majority of instructional models reviewed share this key instructional technique (Fidalgo & García, 2007; 2008) and a large number of research studies have demonstrated its effectiveness (García & Fidalgo, 2006a; Graham & Harris, 2003; Torrance, Fidalgo, & García, 2007; Wong et al., 2003; Zimmerman & Kitsantas, 2002).

In writing, cognitive modeling consists of an explicit representation and explanation with verbalizations of the models´ thoughts and the reasons for performing the different actions during the writing process. Both the observer and the model must bear in mind the different aspects of cognitive modeling which are summarized in the Table 3.

In order to facilitate cognitive modeling with the thinking aloud technique teachers can elaborate a script with the self-questions, self-instructions and self-directive statements for the different stages, pre-, during and post- writing process, which improves memory and may help avoid oversights. It must take into account the need to follow all the sub-processes involved in the planning, editing and revising of a text. Furthermore, it should emphasize the thoughts that self-regulate actions and processes are related to: 1) what do you do before the writing task? (what do you do first, second, later?); 2) what are you doing during the writing task ? (monitoring the task, checking the plan, remembering and the audience of text); 3) what you have done (to assess the aim of the writing task, to check the substantive and mechanical aspects of the written text.); 4) beliefs about self-efficacy,


attributions and motivation (to increase or calibrate the students’ beliefs about their writing competence; their intrinsic motivation).

Table 3. Aspects to be Considered by Model and Observer in the

Application of Cognitive Modeling

Model Observer

To translate their thoughts into words and recite them aloud

Attend to the model following each step throughout the writing task

Verbalize aloud all the steps they go through when writing a text

Ask about misunderstood aspects such as, strange terms, unknown procedures or vocabulary items

Do not think that any thought or step is too small, easy, obvious or unimportant to verbalize. All of them must be verbalized

If the model misses step without thinking aloud, ask them to explain the missing thought

Verbalize all the thinking done before, during and after the writing process. Verbalizations must include plans of what to do, when certain steps are taken, why steps are used or not used, and how to proceed with each thought.

Not to work on the writing task independently, but, listen to and work along with the model,

Include self-questions or self-instructional directive statements because they encourage reflexive, controlled and self-regulated thinking in students.

Not to let the model get ahead of you, if it is necessary slow her or him down to be able to follow carefully, analytically and accurately

Check the model at every step, don’t wait for his or her ultimate answer, the check must be parallel to the realization

Note. These practical aspects of the thinking aloud technique have been adapted to writing based on Hartman (2001)

When the cognitive modeling by the teacher has been completed, the students and teacher, in a big group, analyze and reflect on the modeling, noting the most important actions of the writing process, the necessary steps in writing and the importance of the different actions. The teacher should encourage the students’ participation. At the end of the discussion all the participants should summarize the most relevant conclusions about the writing process performed and the self-regulation strategies and procedures which had been used and their important role in achieving a quality text.

There are two kinds of cognitive modeling, a coping and a mastery model, which provide different information. A coping model is used for events where one or more key errors are made, but which are promptly self-corrected during the execution of the writing process. It provides students with the


opportunity to observe and thus become aware of the mistakes and the strategies for recovering from them and for self-correction. On the other hand, a mastery model is executed during the writing process without missing any component throughout the modeling episode and therefore can provide positive standards of performance. It provides standards of performance which can be useful, similar to the evaluational criteria of performance. Some researchers have shown that a coping model is more effective than a mastery model (Kitsantas, Zimmerman, & Clearly, 2000; Zimmerman & Kitsantas, 2002), but both can provide specific information and therefore, teachers should employ both types of modeling.

Emulation and the Thinking Aloud Technique

After the cognitive modeling training, students emulate a mastery model of the writing process with the thinking aloud technique, following the previous cognitive modeling implemented. In this sense, different intervention programs have reported successful results through training which focused on students observing and then emulating a teacher modeling competent writing process, both in students with and without LD (Braaksma, van den Bergh, Rijlaarsdam, & Couzijn, 2001; Fidalgo, Torrance, & García, 2008; García & Fidalgo, 2006a; Torrance, Fidalgo, & García, 2007; Zimmerman & Kitsantas, 2002).

Thinking aloud is an excellent technique for developing metacognitive knowledge and self-regulation strategies. It is a method of externalizing the writer’s thought processes as one is engaged in a task that requires thinking, that is to say, the writer says out loud all of the thoughts and feelings that they experience when writing a composition (Hartman, 2001).

In general, thinking aloud helps students develop greater control and awareness about the cognitive writing processes and the self-regulation skills in writing. It helps students guide their thoughts during the writing process. It increases their self-control as writers and can also improve their writing performance. Students think more precisely, carefully and systematically when they are thinking aloud. The teacher can identify and diagnose any misunderstood or misused concepts, rules, facts, important omissions and inadequate or incomplete knowledge, approaches or skills in writing if students are thinking aloud (Hartman, 2001).

Emulation can be used individually or organized in pairs of peers, because the effectiveness of cognitive modeling for the development of self-regulation in observers depends on the perceived similarity between the person modeling and the observer. For this reason, sometimes peers can be more appropriate than the teacher in modeling, and it is considered most opportune to combine both models. Although the organization of emulation process in class will depend on the type of instruction employed. Working in pairs is suitable for small intervention groups, such as, has been applied (García & Fidalgo, 2006a), or in individualized tutoring by specialists or teachers. However, there is also empirical evidence of the application of


emulation processes in normal classroom settings with a general teacher tutored in writing process emulation (Torrance, et al., 2007; Fidalgo et al., 2008).

When working in pairs, the first student models the specific writing process modeled previously, while the second student checks the student’s modeling carefully and analytically. This student must have an active role, analyzing all the possible mistakes of the writing process emulated, and provide guidance when necessary. The students must change roles between model and observer. Teachers must observe each pair, monitor their progress, and provide feedback on the process. When the writing process is finished, all students, initially in pairs, and later in a big group, analyze and reflect on the most important actions of writing process, their need for the self-regulation strategies and procedures which had been used and their important role in achieving a quality text. Teachers should train students in how to think aloud before applying its use.

Discussion and Conclusion

The development of writing competence is a difficult task. It depends not only on the mastery of low-level transcription skills, but also of the development of metacognitive dominance of writing process as well (Graham & Harris, 2000).

In this sense, an instructional perspective of writing focusing on the automation of the low level or mechanical cognitive processes of the writing is not sufficient (Berninger, et al., 1997; Graham & Harris, 2000; Graham, Harris, & Fink, 2000). Their importance in the development of the writing competence is obvious, because if the mechanical processes of writing, such as, handwriting or spelling, are not automatized, they will hinder and interfere with the recursive nature and organization of the higher cognitive level processes of writing, and could result in a cognitive overload according to the constraints of working memory with negative consequences for the written products (McCutchen, 2000). However, mastery of these is not enough, it is also necessary to have metacognitive dominance and mastery of the high level cognitive processes of writing. The cognitive complexity of writing tasks demands the need for the development of a students’ substantive knowledge of writing, and control and self-regulation of the different processes and components of the underlying higher cognitive level in the process of composition, like the planning or revision process, in order to achieve skill in writing. At the same time, the need for metacognitive instruction in writing is still more justified if one bears in mind that writing metacognition skills have no cause to be spontaneously developed in students. They need to be explicitly and continually addressed, practiced, polished and internalized (Hartman, 2001).

In recent years, this instructional focus has enjoyed, vigorous development as concerns the improvement and teaching of writing from theoretical and empirical perspectives; with the field of intervention in writing


dominating notably in recent years. In this area, the last decades have shown a rapid growth and development of instructional studies focusing on the dominance of higher level writing processes with a metacognitive approach (Englert, Mariage, & Dunsmore, 2006; Graham 2006; Graham & Harris, 2003), especially with students who present with LD (Baker, Gersten, & Scanlon, 2002; Gersten & Baker, 2001; Fidalgo & García, 2007; 2008; Wong et al., 2003). There are different instructional models whose effectiveness in improving the writing outcomes of students with LD has been verified in different studies, such as: the Self-regulated and Strategy Development Model - SRSD (for a review see Graham & Harris, 2003); the Cognitive Strategy Instruction in Writing Model (Englert et al., 1991; Englert, Raphael & Anderson, 1992); the Strategy Content Learning Model –SCL (Butler, 1994; 1995; 1998a; 1998b); the Genre-Specific Strategies Model (Wong, Butler, Ficzere & Kuperis, 1996; 1997; Wong, Butler, Ficzere, Kuperis & Corden, 1994). In general, these instructional models share key features of effective instruction in writing (Fidalgo & García, 2007; 2008).

Specifically, this article summarizes some of these key instructional techniques that share the aim of helping students with LD to become more strategic and metacognitive learners in writing. Metacognitive knowledge of writing can be improved through the promotion of self-reflection, and the use of metacognitive knowledge evaluation matrices and textual analysis. On the other hand, self-regulation in writing can be developed by means of mnemonic devices for the cognitive strategies of writing, cognitive modeling and emulation and the thinking aloud technique. Finally, there are several practical aspects which must be highlighted. Firstly, both dimensions of knowledge and regulation of cognition are related to one another; and both dimensions should be taught in a complementary fashion. Teachers should develop a prior metacognitive knowledge of writing in students. Subsequently, teachers should develop training which focuses on the self-regulation of writing through instruction wherein the students first observe and then emulate a teacher modeling competent writing process. This allows students to transfer their declarative, procedural and conditional substantive knowledge of writing into practice. Secondly, it is beneficial to break down the complete writing process into the main writing sub-processes for training purposes as its complexity could be overwhelming for students. Specifically, according to Hayes and Flower’s theoretical model of writing (1980), writing instruction could be divided in the three main processes of writing: planning, editing and revision. Metacognitive instruction would focus on the planning, editing and revision writing process independently and successively, and finally, when students possess the knowledge and the ability to regulate all writing processes independently, training could then address all writing processes concurrently. Finally, as for the different textual genres, it would be constructive to teach the different kinds of textual genres following a progression, that is to say, from the easiest to the most difficult (narration, description, expositive, and finally, argumentative). Moreover, it is also important that the written and analyzed texts are functional. They should represent real communicative situations, with a defined purpose, which is both


interesting and realistic for LD students in order to promote their intrinsic motivation.

In summary, teachers should be aware of the importance of these instructional techniques to suit a more self-regulated or metacognitive domain, specifically in students with LD in composition writing. Furthermore, they should try to incorporate these metacognitive strategies in writing into their practice and curriculum.

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Emotional Intelligence and Ways of Coping among college Students

Gamal Al Sayed Tofaha, PhD

Vice Dean , Faculty of Education , Port Said , Egypt


Abstract

The main purpose of the present study was to explore the relationship between emotional intelligence and ways of coping among college students ( Port Said college of Specific Education Students) in Egypt . Participants were 200 students aged 18-21 years . They completed self-reported measures of emotional intelligence and ways of coping. It was found that appraisal of emotions in the self was positively correlated with plan-full problem solving and positive reappraisal coping styles. Appraisal of emotions in others was positively correlated with plan-full problem solving and positive reappraisal. Emotional regulation of the self was positively correlated with planfull problem solving, confronting coping, self-controlling, positive reappraisal and with distancing, but negatively correlated with escape avoidance. No gender differences were found in perceived emotional intelligence and ways of coping except for self-control, where males reported higher than females.

Keywords: Emotional Intelligence; Coping; College Students.

Introduction

Late adolescence is a critical transitional period in which individuals face a number of social changes, and relationship and achievement related stressors (e.g., Compas, Hinden, & Gerhardt, 1995). The dynamic relationship between the person and environment in stress perception and reaction is especially magnified in college students, so the problems and situations encountered by students may differ from those faced by their nonstudent peers (Hirsch & Ellis, 1996). The environment in which students live is quite different. While jobs outside of the university setting involve their own sources of stress, such as evaluation by superiors and striving for goals, the continuous evaluation that students are subjected to, such as weekly tests and papers, is one which is not often seen by non-students (Wright, 1964).The pressure to earn good grades and to earn a degree is very high (Hirsch & Ellis, 1996). Earning high grades is not the only source of stress for students. Other potential sources of stress include excessive homework, unclear assignments, and uncomfortable classrooms (Kohn & Frazer, 1986). In addition to academic requirements, relations with faculty members and time pressures may also be sources of stress (Sgan-Cohen & Lowental, 1988). Relationships with family and friends, eating and sleeping habits, and loneliness may affect some students adversely (Wright, 1967). We believe that that many of these sources of stress are also applicable in the urban Indian context.

Emotional Intelligence and coping with Stressful events

Does assessment of EI add anything to the practitioner’s ability to predict individual differences in stress response in performance settings? Many researchers working in the domain of EI have


accepted, seemingly uncritically, Goleman’s (1995) dictum that “keeping our distressing emotions in check is the key to emotional well-being” (p. 56). Questionnaire measures of EI have been used to demonstrate associations typically ranging from 0.2 to 0.6 between EI, stress outcomes, and coping (see Zeidner et al., 2006, for a review). Unfortunately, most of such measures have proved to be highly correlated (up to .77) with existing personality scales, especially traits of the FFM including low N, E, and C (see Matthews, Zeidner, & Roberts, 2004). Thus, it is doubtful that EI questionnaires show meaningful incremental validity with respect to existing personality measures in predicting well-being, stress responses, and coping strategies.By contrast, Mayer et al. (e.g., 2000) define EI as a form of ability measured by objective tests, akin to conventional intelligence tests. Their model places general EI at the apex of four correlated branches (or facets) of EI: identifying emotion (also known as emotion perception), assimilating emotion into thought, understanding emotion, and managing emotion (both in self and in others). Their initial test, the Multifactor Emotional Intelligence Scale (MEIS; see Mayer et al., 1999) has been superseded by the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT; Mayer, Salovey, Caruso, & Sitarenios, 2003), which includes two subtests for each branch. Correlations between the MEIS or MSCEIT and FFM factors are typically less than .30 (Lopes, Salovey, & Straus, 2003; Roberts, Zeidner, & Matthews, 2001). The MSCEIT shows correlates at about .30 with indices of wellbeing and social adjustment (Brackett & Mayer, 2003; Lopes et al., 2003), but it has not been used in experimental studies of stress and performance. Salovey, Bedell, Detweiler, and Mayer (1999) have claimed that emotionally intelligent individuals cope with stress more effectively as a result of their basic emotional skills, greater emotional knowledge, and more effective emotional regulation. High-EI persons tend to use strategies such as eliciting social support and disclosure of feelings, in place of the maladaptive coping strategy of rumination. Consistent with this proposition, Ciarrochi, Chan, and Caputi (2000) found that high scorers on the MEIS were more likely than were low scorers to retrieve positive memories during mood induction as an aid to mood regulation. In the occupational context, Jordan, Ashkanasy, and Ha¨rtel (2002) suggested that EI may be an important moderator of stress reactions to job insecurity. All four branches of the Mayer et al. (2003) model may promote more effective coping in response to this job stressor. However, the sources cited neglect to specify effect sizes for associations between EI and coping, and so it is unclear how strong such associations may be.

While Lazarus’s coping model defined coping as “constantly changing


cognitive, behavioral, (and emotional) efforts to manage particular external and/or internal demands that are appraised as taxing or exceeding the resources of a person” (cf., Lazarus & Folkman, 1984). Emotional intelligence involves the ability to perceive accurately, appraise and express emotions, the ability to access and or generate feelings when they facilitate thought, the ability to understand emotions and emotional knowledge, and the regulate emotions to promote emotional and intellectual growth (Mayer & Salovey, 1997).Matthew and Zeidner (2001) suggest that successful coping with stressful encounters is central to emotional intelligence. Successful coping forms the very bedrock of good mental and physical health. It is through the coping process that we are able to survive the many challenges that life brings and to flourish as people (Snyder & Dinoff,1999).Gohm, Corse and Dalsky (2005) examined the association between emotional intelligence as assessed by an ability measure, Mayer, Salovey & Caruso Emotional Intelligence Test (MSCEIT; Mayer, Salovey & Caruso, 2002) and stress (feelings of inability to control life events) among American students. They found that overall emotional intelligence was potentially useful in reducing stress for some people, but irrelevant or unnecessary for others.

Specifically, higher emotional intelligence was correlated with lower stress for only those individuals who are high in attention to emotion, clarity to emotion and emotional intensity. Besides, overall emotional intelligence was negatively correlated with certain coping styles, such as, behavioral disengagement and alcohol-drug engagement. Further analysis showed that managing emotion was positively correlated with certain other coping styles, such as, seeking social support- emotional, seeking social support- instrumental and religious coping styles. Carriochi, Deane, and Anderson (2002) and Salovey, Stroud, Woolery, and Epel (2002) found evidence that emotional intelligence moderates the relationship between stress and mental health. Furnham, Petrides, and Spencer-Bowdage (2002) showed that emotional intelligence is related to healthy social coping styles. Pelliteri (2002) found that college students who are emotionally intelligent tend to use an adaptive defense style.

Gender and Coping

Gender differences in the use of coping strategies have been reported in a number of studies. In general, findings suggest that females tend to favor social support, emotion focused and avoidant coping strategies relative to males (e.g., Ptacek, Smith, & Zanas, 1992; Stein & Nyamathi, 1999). A study on life stress and coping styles among teachers indicated that males are higher in their use of acceptance and females are higher in the use of self-blame as coping styles (Sahu & Misra, 1995). Gurnakova (2000) found that males tend to use problem focused coping more than females. A study done by Gupta and Murthy (1984) studied role conflict and coping strategies among Indian women, showed that the most commonly used coping strategy was personal role re-definition.The qualitative results also indicated that ‘Adjustment’ and ‘Compromise’ were most commonly used and


successful methods of coping.

Does Emotional Intelligence Depend on Gender?

There is considerable body of research on emotional intelligence and gender differences. Women have scored higher than men in emotional intelligence across the studies (Brackett & Mayer, 2003; Mayeret al., 2002; Schutte, Malouff, Hall, Haggerty, Cooper, Golden, & Dornheim, 1998; Thingujam & Ram, 2000). Interpersonal social skills, which is closely linked to EI has consistently, demonstrated a gender effect with females being more perceptive, empathic, and adaptable than males (Argyle, 1990). Further, Schutte et al. (1998) predicted and found gender differences in their measure of trait EI with females scoring higher than males. In contrast to Schutte et al. (1998), Bar-On (2000), Petrides and Furnham (2000) did not find a significant gender difference in overall trait EI. The results of their study showed that in spite of the evidence that females seem to be more socially skilled than males (Argyle, 1990; Hargie, Saunders, & Dickson, 1995) and score higher on existing EI tests (Schutte et al., 1998), their self-estimated EI scores tend to be lower than those of males. They hypothesize possible explanations for this in terms of the nature (self enhancement versus self-derogation) and source (male versus female) of the bias. It could be, for example, that males self-enhance and females self derogate; that both genders self-enhance with males more so than females; or that males are accurate and females self-derogate. It may be argued that the bias is more likely to be self-derogatory and on the side of females since, on the whole, the correlations between measured and self-estimated EI were lower for females than for males (Petrides & Furnham, 2000).

Emotional intelligence in the present study would be considered as perceived emotional intelligence. This is because Schutte et al. Emotional Intelligence Scale measures participants’ perception of emotional intelligence as against emotional intelligence as a type of intelligence or ability. Such perceived emotional intelligence could also be considered as emotional maturity (Thingujam 2002, 2004) or emotional competence (Saarni, 1999). Thus it was hypothesized that perceived emotional intelligence (appraisal of emotion in self, appraisal of emotions in others, emotional regulation of the self, and utilization of emotions in problem solving) would be significantly associated with different ways of coping (such as confrontative coping, self controlling, planful problem solving, positive reappraisal, accepting responsibility, etc.). This relationship would be examined across the gender if gender differences were found in perceived emotional intelligence subscales.

MethodParticipants :

The sample comprised of 200 participants (105 males, 95 females), between ages 18 and 21 years (mean age = 19.34 years). All participants were from the faculty of Specific Education , Port Said University .


Participants were approached individually and their co-operation was solicited for some samples and requested to respond to the test package after establishing rapport. All the participants were told that they were a part of a study and their consent to participate in the study was taken prior to the tests. They were also informed that all information given would be confidential and be used for research purpose only. They were then given the standard instructions for the tests required and were requested to indicate their responses on the response sheet.

Measures:

Emotional Intelligence Scale (Schutte et al.,1998): Based on the original Mayer- Salovey model of emotional intelligence (Salovey & Mayer, 1990), Schutte and colleagues developed a 33-item self-report Emotional Intelligence Scale (EIS). Three of the 33 items (5, 28, and 33) are reverse scored. Participants responded to the items on a 5-point Likert scale. Despite an alpha of .90 and Schutte et al.’s (1998) claim about uni-dimensionality, Gignac, Palmer, Manocha and Stough (2005) found evidence of six interpretable factors similar to those mentioned in the original literature. They derived six components via confirmatory analysis, but only those subscales (factors) with sufficient alpha coefficient reliabilities were included in this study. Namely, appraisal emotions in others (á=.81), emotional regulation of self (á=.71), and utilization of emotions in problem solving (á = .69). Higher score indicated higher perceived EI in all the subscales.

Ways of Coping Questionnaire

(WOCQ; Lazarus, & Folkman, 1984): WOCQ assesses the thoughts and actions individuals use to cope with stressful encounters of everyday living. It is derived from cognitive phenomenological theory. It measures coping processes, not coping dispositions or styles. It consists of 8 sub-scales, which include: i) Confrontative–coping (á=0.70), ii) Self controlling (á = .70), iii) Distancing (á= 0.61), iv) Seeking social support (á=0.76), v) Accepting responsibility (á=.66), vi) Escape avoidance (á = 0.72), vii) Planful problem solving (á=. 68), viii) Positive reappraisal (á = 0.79).

Results

After computing descriptive statistics the data were subjected to ANOVA and Person’s Product Moment correlations to examine gender differences and correlations, respectively (see Tables 1, 2, & 3).

Table1. Mean, SD, and F values of the subscales of emotional intelligence, Male Female Scales M SD M SD FAES 7.2 1.6 7.2 1.4 0.13AEO 25.6 4.6 25.6 3.7 0ERS 31.6 4.5 31.5 3.7 0


UEPS 15.7 2.3 16.2 4.4 1.03

Key: AES = Appraisal of emotions in self, AEO = Appraisal of emotion in others, ERS = Emotional regulation of self, UEPS = Utilization of emotions in problem solving.

Table 2. Mean, SD, and F values of the subscales of Ways of Coping. Male Female Scales M SD M SD FPPS 9.9 3.3 9.2 4 2. 09CO 7.4 3.5 7 3.3 0.45SSS 8.1 4.3 8.1 3.9 0AR 7.9 3.8 6.9 3.9 3.5(p=.06)SC 11.5 3.2 10.6 3 4*D 8.3 3.3 7.9 3.5 1.05EA 7.5 4.7 8.5 4.9 1.8PR 12.84 3.9 12.2 4.5 1.1* p< 0.05Key: CO = Confronting coping, SSS = Seeking social support, PPS = Planfulproblem solving, AR = Accepting responsibility, SC = Self controlling, D = Distancing, PR = Positive reappraisal, EA = Escape avoidance.

Table-3: Results of Pearson’s product moment correlation between subscales of emotional intelligence and ways of coping. Subscales of emotional intelligenceWays of coping AES AEO ERS UEPSPPS .13 (p =.07) 0.06 0.27** 0.09 CO 0.08 0.02 0.04 0.12 SSS 0.20** 0.18* 0.38** 0.07 AR 0.02 -0.9 0.07 -0.01 SC 0.09 0.09 0.15* -0.01 D -0.02 -0.8 0.14* 0.01 PR 0.24** 0.18* . 30** 0.11 EA -0.07 -0.1 -0.16* -0.00

** p< 0.01 * p< 0.05Key: AES = Appraisal of emotions in self, AEO = Appraisal of emotion in others, ERS = Emotional regulation of self, UEPS = Utilization of emotions in problem solving, CO = Confronting coping, SSS = Seeking social support, PPS = Planful-problem solving, AR = Accepting responsibility, SC = Self controlling, D = Distancing, PR = Positive reappraisal, EA = Escape avoidance

Discussion


The main focus of the present study was to examine the relationship between emotional intelligence and ways of coping across the gender if gender difference was observed across the variables used in the present study. However, there was no gender difference in any of the subscales of perceived emotional intelligence, hence correlation between emotional intelligence and ways of coping were not computed across the gender. On the basis of the present and other earlier studies it may be concluded that gender differences in perceived emotional intelligence cannot be generalized although, theoretical literature tends to favor women to be more emotionally intelligent. The same is the condition in the context of gender and coping too since only one subscale, self-control showed difference across the gender.

Perceived emotional intelligence and ways of coping: A number of researchers have argued that emotions create different mental sets that are more or less adaptive for solving certain kinds of problems (Palfai & Salovey, 1993). Different emotions create different information processing styles. Happy moods facilitate a mental set that is useful for creative tasks in which one must think intuitively or expansively in order to make novel associations. Sad moods generate a mental set in which problems are solved more slowly with particular attention to detail using more focused and deliberate strategies. Palfai and Salovey argue that these two information processing styles i.e. intuitive and expansive versus focused and deliberate should be effective for two different kinds of problem solving tasks- inductive problems like analogical problems like analogical reasoning and deductive logical tasks. Thus, students scoring high on emotional intelligence components may tend to use planful problem solving to cope with their stressors.

Positive reappraisal way of coping was also found to be positively and significantly correlated with three subscales of perceived emotional intelligence, that is, appraisal of emotions in self, appraisal of emotions in others and emotional regulation of the self. It may be noted that positive reappraisal way of coping used in the present study involves efforts to cope by creating positive meaning by focusing on personal growth. It also has areligious dimension. Items on this scale included, “I changed or grew as a person”, “I found new faith”, etc. This coping strategy may promote adaptive cognitive reappraisal of the stressor. Appraising emotions in one self and others as well as regulating ones emotions may produce an elaboration of the cognitive affective structure regarding a stressful encounter. It may introduce elements incompatible with the original structure. For example, the individual may realize that, negative emotion eventually subsides and that the initially associated emotions are not as threatening as initially believed. Thus, some benefit can be probably derived from adversity.

It was also found that emotional regulation of the self was positively and significantly correlated with self-controlling, which describes efforts to regulate one’s feelings and actions. Research indicates that from early age self-control is a necessary skill in all arenas of life (Strayhorn, 2002). When


people lack self-control they have difficulty in regulating their emotions (Brooks & Goldstein, 2004). It is then conceivable that, regulating ones own emotion is a crucial ability while using self-control as a coping strategy. Confrontative coping, which includes aggressive efforts to alter the situation and suggests some degree of hostility and risk taking was also found to be positively and significantly associated with emotional regulation of the self. Changing the problem situation requires a good degree of self regulation, because it involves direct and active coping efforts. It also includes potential for conflict or unpleasantness, which requires the person trying to confront and alter the problem situation to stay alert to the subtle as well as obvious changes in his or her own emotions. Students with higher emotional regulation of self are probably more confident of handling the possible reactions from others while entering into any confrontative situation.

Emotional regulation of the self was found to be negatively correlated with escape avoidance way of coping, which involves wishful thinking and behavioral efforts to escape or avoid the problem; it differs from distancing which suggests detachment. Avoidance types of coping typically work against people rather than to their advantage (Zeidner & Saklofske, 1996); however, cognitive avoidance may be an effective way to cope with short-term stressors (Suls & Fletcher, 1985). According to Suls and Fletcher (1985), escape avoidance based strategies fail to resolve the underlying problems that are generating stress; they can be expected to lead to greater long-term distress than more active approaches. Avoidant coping strategies lead people into activities (such as alcohol use) or mental states (such as withdrawal) that keep them from directly addressing stressful events. Generally speaking, active coping strategies, whether behavioral or emotional, are thought to be better ways to deal with stressful events, and avoidant coping strategies appear to be a psychological risk factor or marker for adverse responses to stressful life events (Holahan & Moos, 1987). Seiffge-Krenke (1995) notes that a dysfunctional coping style may include efforts to withdraw from or deny the existence of the stressor, avoiding seeking solutions and attempting to regulate the emotions. According to Mayer and Salovey (1995), high conscious levels of emotional regulation operate at a reflective or meta level. It involves extended self-observation, requires attention, involves thoughts of the self and can be often recalled. As a coping style, escape avoidance is the very opposite of this process. Hence, they are found to be negatively associated with each other.

Distancing way of coping was positively associated with emotional regulation of the self. Pearlin and Schooler (1978) found that distancing strategies were most successful for dealing with stressful impersonal situations, but committed and engaged strategies with relevant others were most successful in reducing emotional distress in more personal situations. Emotional regulation of the self includes “the ability to reflectively engage or detach from an emotion depending on its judged in formativeness or utility” (Mayer & Salovey, 1997). This is consistent with the present findings. It seems that the coping process of distancing and confrontative require a


good amount of emotional regulation. So, students with more capacity to regulate emotion of the self are arguably smarter in deciding whether they should confront or stay away from a stressful situation. Thus, it seems that coping processes used by students depend in part, on one or more of emotional skills although emotion regulation of the self is the component of emotional intelligence which is related to most of the ways of coping with stress and utilization of emotions in problem solving is unrelated to any ways of coping included in the present study. An intervention becomes possible if we know when and at what level the emotional skills are weak or lacking. For instance those students, who cannot appraise or regulate their own emotions properly, may fail to recognize the origins of their problems. This can adversely affect the coping process, by either delaying it or rendering it inadequate.

The use of student population as a basis of drawing the sample may have limited the study. However, the present results should be treated as preliminary because alpha coefficient reliabilities of the Ways of Coping are low in our data. It is important to improve the alphas and re-examine the coping perceived emotional intelligence linkage. Besides, in future research the coping process-emotional intelligence relationship could also be re-examined by using ability measure of emotional intelligence, such as Mayer-Salovey Caruso Emotional Intelligence Test (MSCEIT; Mayer et al., 2002). MSCEIT is to a great extent different from Schutte Emotional Intelligence Scale since the correlation between the two measures is just, r=.18 (Bracket & Mayer, 2003).

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The Effect Of The Jigsaw Technique On Prospective Teachers’

Achievement

Kerim GÜNDOĞDU, Ceyhun OZAN., Adnan TAŞGIN

Atatürk University, K.K. Faculty of Education, Educational Sciences Department

Abstract

This study investigated the effects of the jigsaw technique on the achievements of sixty-four freshman students in an Educational Psychology course. The jigsaw method is a cooperative learning method that was applied to the experimental group, while the traditional learning method was applied to the control group. The subjects were all prospective teachers taking the Educational Psychology course in Turkish Language Education department in a public university in Turkey during the second term of the 2008 -2009 academic year. According to the results of the study, the test group appeared to be more successful than the control group in terms of post-test and knowledge retention scores. Key words: Jigsaw technique, educational psychology, cooperative learning,

prospective teachers

Introduction

Individualized learning practices have been utilized for decades at all levels of education, from primary grades to higher education classes. Intellectual ability is seen as a characteristic of the individual, according to both Piagetian and behaviorist theory. However, in recent years a greater emphasis has


been placed on the social development of the individual. Research findings show that social interaction within learning environments has a great effect on cognitive development (Hill & Hill, 1990).

Cooperative learning is not a new phenomenon and much has been written about the effects of it on student achievement, student motivation and attitudes. We understand from the overwhelming studies of D. Johnson, Slavin, Farivar, Holubec, Hollifield, Schmuck, Sharan and Aronson (cited in De Ligny, 1996) that cooperative techniques positively affects the acquisition of knowledge, the development of social relations of students and improves self-esteem What is cooperation? Cooperation in the learning environment is the interaction of at least two individuals, to achieve the same goals. In this interaction, positive interdependence and goal similarity are the two key essentials (Hill & Hill, 1990). Cooperation or cooperative skills can be learned by engaging in a process that allows groups to reach common goals and to understand that they will be more successful if they work together. As Gillies explains (2007), the cooperative learning process requires that students work together to accomplish common goals.

This process facilitates socialization of the learner from kindergarten through university.

In the learning-teaching process, when techniques and methods to make students participate in the lesson are used, the students learn in the best way, and they remember more fully and enjoy what they do. The cooperative learning method, which was developed from theoretical and applied surveys (Oral 2000), facilitates student participation.

The cooperative learning method is defined as a learning approach in which students form small mixed groups to help each other to learn an academical lesson; they share identical aims, and the success of the group is awarded in different ways (Gömleksiz, 1997). The group members cooperate by teaching each other or doing a part of the work. This is called “subordination of the inward” or “subordination of purpose.” Each student’s learning in the group is affected by the learning or the endeavors of the other students in the group. Because of this, everybody in the group is responsible for each other’s learning, and abilities can be shared (Açıkgöz 1993). This style provides an alternative to decrease the weight of traditional, teacher-based teaching methods (Sharan & Sharan, 1999).

According to Gillies (2007), the success of the cooperative learning method depends on the group’s possession of positive interdependence and cooperation, individual accountability, promotive interaction, and ability to evaluate and improve. Johnson, Johnson, and Smith (1998) further explained these crucial factors: each member must be consciousness of his/her responsibility for the learning of the others. Every student in the group must be aware of the fact that his/her own effort is beneficial to everyone in the group, and also that every other member’s effort is beneficial to him/her. The success of the group depends on each one of the group members striving to fulfill their common learning aims. Slavin (1990) states that all studies on


cooperative learning indicate the importance of team rewards and individual accountability. The theory is that positive interdependence motivates the whole group to do the best they can. The most important aim of the cooperative learning groups is to ensure that each member is accountable for his/her behavior, performance, and success. All learners in groups are responsible to try to do their best. Each member of the group should also be aware that unique contributions are important. Group members should explain to each other how they solve the problems that they face, discuss the ideas that they get, and encourage, support, and help one another. They help to promote and to improve their mutual success through continuous interaction. One of the goals of cooperative learning is that the learners’ social skills will increase in such an atmosphere. The last element of cooperative learning is group processing. This allows group members to obtain self-evaluation skills. Such evaluation not only helps the group members to work with maximum efficiency in their learning activity, but also further encourages the habit of working together in groups.

Student teams and success divisions, team-game-tournaments, cooperative integrated reading and composition, team-supported individualization, “let’s ask and learn together,” integration, and mutual questioning can be regarded as techniques of the cooperative learning method (Baykara 2000).

Implementation of the Jigsaw method

One of the most effectively used cooperative learning techniques is the jigsaw method. It was originally developed by Elliot Aronson and his colleagues, specifically to solve the school desegregation problem. The interaction problem between the black and white students was solved through Jigsaw by placing students in small heterogeneous groups and assigning tasks so that students could make their own contributions to the groups with extreme interdependence (Abrami et al., 1995; Kagan, 1997).

The technique requires that every student in the group share knowledge in every part of the course. Also, students in each group should feel responsible for the success of the other members. It is possible to generate cooperation between individual Jigsaw groups. A key feature of this technique is pointing out that the students’ individual grades depend on each member’s performance. Therefore, there is no group award for success. Though members of a group, each student is personally responsible for studying the whole lesson (Knight & Bohlmeyer, 1990).

Although the Jigsaw approach has been flexible in its implementation, all learners who work in small groups must understand that mutual trust is required in this approach. Every learner in the group becomes an expert on the topic studied and contributes by helping his/her classmates. The name Jigsaw reflects a metaphor that means putting all the pieces a puzzle together to see the whole picture. Although the Jigsaw approach can be applied flexibly in learning environments, it has four major stages in all applications (Clarke, 1999):


Introduction stage: The teacher organizes the students into heterogeneous original groups. Then s/he introduces the theme and the rationale of the theme to be studied. It is crucial to generate interest in the lesson among the students. Learning and assessment procedures are finally explained.

Focus group stage: New focus groups are organized by the students from the original groups to study and learn the specific topic in detail. In this stage, the teacher encourages the students by allowing them to think out loud in a free atmosphere. The students are directed to explore the main ideas and the ideas of others in the focus groups.

Reporting and reshaping: The students return to their original groups to explain what was learned and generated in the focus groups. Discussing, asking questions, interacting, and explaining are encouraged by the teacher. Thus, the students begin to understand the topic as whole, as they understand the work done by their peers.

Integration and evaluation: The students are encouraged to design an activity in their original groups to demonstrate what they have learned from others.

Aronson’s original model was redesigned by Slavin (1990) and his colleagues in what they called Jigsaw II. In this model, the students should revisit the studied material ‘through the lens of different perspectives to deepen conceptual understanding of significant themes, frameworks, or central ideas’ (p. 37). In Jigsaw II, the extrinsic reward structure is also benefited. Heterogeneous teams generated on the basis of their performance levels teach each other and are assessed individually by means of quizzes on all the themes. The scores from these quizzes are averaged into one team score. Then, the winning teams are declared, to build a competitive spirit among the teams and to encourage them to cooperate to increase their team scores (Slavin, 1990). Although several variations were created by educators within the stages of the method (Kagan, 1997: Reid, Forrestal, & Cook, cited in Clarke, 1999), the idea of highlighting the cooperation, contributions, and peer teaching remains the same.

Research on cooperative learning and Jigsaw

Theory and experimental studies conducted in learning environments suggest that cooperative activities should be taken into consideration if educators wish to enhance the intellectual and social development of students. Twenty-one of the twenty-six studies conducted by Johnson and Johnson that investigate academic achievement clearly show that co-operative learning activities overwhelmingly promote higher academic achievements more effectively than other training methods. In addition, according to a meta-analysis by Johnson, Maruyama, Johnson, Nelson, and Skon on 122 cooperative learning studies conducted between 1924 and 1981 (1981, cited in Hill & Hill, 1990), the overall trends clearly indicate that cooperative learning methods generate higher academic achievements than individualized learning experiences.


In response to this meta-analysis, Slavin compiled and investigated 46 studies on cooperative learning activities which measured individual achievement and concluded that a vast majority of the studies showed positive effects on achievement. Slavin also found that increase in self-esteem was another crucial achievement of cooperative learning activities. Johnson and Johnson’s analysis of a further study showed that positive interdependence, which means interacting with and depending on one another to be successful, is the key requirement in cooperative activities, rather than simply rewarding individualistic behaviors (Aronson & Patnoe, 1997).

A team of educators launched a longitudinal project to restructure the teaching and learning process to reduce the competitive ethos based on the “win” or “lose” concept that was pervasive in schools in 1972. They attempted to develop equal opportunities and to support an affective environment through more collaborative work, interaction, and mutual trust (Clarke, 1999). The Jigsaw technique was originally developed to bridge the gap between different ethnic groups of children. However, its results are not limited to multicultural learning environments. Aronson and Patnoe (1997) stated that while individualized instruction benefits from independent activities, developing the social skills of the child is neglected. Employing jigsaw activities in a learning environment may provide a balance against the competitive classroom environment. It is a way of building a classroom community where all learners feel valued (Clarke, 1999).

After a full-scale jigsaw study, Aronson and Patnoe (1997, p. 92) concluded that “a strong, positive pattern of behaviors, feelings, and abilities could be attributed to jigsaw groups.” They also found a difference in performance between jigsaw and competitive classes in favor of jigsaw classes, after an experimental study.

There are many additional studies on the positive effects of cooperative learning in the academic success of learners throughout the world (Açıkgöz, 1993; Avşar & Alkış, 2007; Baykara, 2000; Bilgin & Geban, 2004; Cooper & Mueck, 1990; Delen, 1998; Dougherty, et al., 1995; Doymuş, Şimşek, & Bayrakçeken, 2004; Erdem, 1993; Gömleksiz, 1993; Gömleksiz & Onur, 2005; Gömleksiz & Tümkaya, 1997; Gömleksiz & Yıldırım, 1996; Johnson, et al., 1981; Johnson & Johnson, 1974; Karaoğlu, 1998; Kıncal, Ergül, & Timur, 2007; Leung & Chung, 1997; Oral, 2000; Öner, 1999; Özder, 1996; Özkal, 2000; Pala, 1995; Potthast, 1999; Quarstein & Peterson, 2001; Sarıtaş, 1999; Sezer & Tokcan, 2003; Slavin, 1990; Sharan, 1980; Tarım & Akdeniz, 2008; Tok, 2008). But few studies have been conducted on Jigsaw as a cooperative learning method. The achievement rates of students in Jigsaw classrooms are higher than those in traditional instruction classrooms (Avşar & Alkış, 2007; Beckett, 2009; Frazee, 2004; Gencdogan, 2007; Kılıç, 2008; Stepka, 1999). Most of the studies in the literature on cooperative learning are quantitative. However, there are some qualitative studies reflecting the effect of the cooperative learning techniques. For example, Jefferies (1987) contends that students enjoyed learning through planned student interaction, especially peer teaching in a qualitative investigation.


On the other hand, the results of a study (De Ligny, 1996) showed that although the Jigsaw technique did not have a significant impact on the achievements of students, a significant improvement was observed in peer respect, motivation, positive interdependence and self-esteem. Regarding changing the attitudes and achivement, Webb’s (1992) study clarified that Jigsaw did not significantly reduce prejudicial attitudes, and did not increase academic achievement in college students.

As seen in the literature, most of the studies are related to secondary school level and few of them are administered at higher education level. After all, there are numerous of studies approving the positive effect of the cooperative techniques on student achievement, and a few studies that did not create any difference on student achievement or on their attitudes. The literature show that cooperative learning strategies generally result in positive affective and cognitive outcomes. On the other hand, some studies run contrary to previous researches. For example, Anderson (1985) found that although further research is suggested to determine the reliability, the attitudes and achievement of the students did not significantly changed after an experimental study involved Jigsaw technique. As parallel to this finding, Webb (1992) concluded that the Jigsaw did not significantly reduce prejudicial attitudes or increased the academic achievement of college students.

The purpose of this study is to investigate the effects of the Jigsaw cooperative learning method on the academic success of prospective teachers.

Problem Statement

Is there a significant difference in the academic achievements of prospective teachers who are taught according to the Jigsaw cooperative learning technique and the traditional methods and techniques?

Methods

Research Design

A pre-test/post-test, control grouped quasi-experimental design was used in this study (Büyüköztürk, Çakmak, Akgün, Karadeniz, and Demirel, 2008). Two randomly selected groups were employed as the study groups. One of these was designated the experimental and the other the control group. The experimental group received the Jigsaw cooperative learning method of instruction, and the control group received the instructor-based traditional method. In order to avoid researcher bias, different instructors delivered the instructions in both groups. At the beginning of the academic year, both researchers were trained in the delivery of the course in two different ways while preparing the outline of the course. In the study, quantitative data were collected, and statistical analyses were performed.

Study Group: This study was conducted with 68 freshman students of the Turkish Education Department enrolled to the Educational Psychology course at Atatürk University in the 2008 -2009 academic year in Turkey. Group A was the experimental group (received Jigsaw technique), while Group B (received


traditional lecture technique) was the control group. Each consisted of 34 students, selected randomly.

Data Collection Procedures

In the study, both the experimental and control groups received two weeks of instruction (six hours) about “contemporary teaching strategies.” In order to evaluate their initial knowledge

of the subject, a pre-test with 25 multiple choice questions was administered. Beginning the week after the pre-test, both groups were trained for three hours a week over two weeks. At the end of this period, a post-test containing 25 questions was administered to both groups. In order to prevent the students from studying for the post-test, they were not informed that the test would be repeated. Three weeks after the post-test application, in order to evaluate their retention of the acquired knowledge, the same post-test was given as the retention test again.

The steps of the jigsaw technique that was used in this study are described below:

1. The classroom was divided into seven groups, each one containing five students. There were four students in one of the groups.

2. Each group was assigned one of the seven subjects of the overall educational psychology lecture course. Then that group was named after the name of the subject it received.

3. In each group, a leader was chosen to learn and teach the subject to that group.

4. Each member except the group leader was sent to the other groups for two classes, in order to learn the other subjects. So new groups were formed, but the group leaders were fixed.

5. The group members who learned the subjects of the other groups returned to their own group at the end of the course.

6. Each group member who came back to his/her own group explained the subjects that s/he learned to the other members of the group.

7. Seven different subjects of the Educational Psychology course were studied in this way during two weeks.

Findings

The standard deviations and arithmetic means derived from the pre-test, post-test and retention test are given in Table 1. Table 1. Pre-test, post-test and retention-test mean scores and the standard deviations of the experimental and control groups.

Pre-test Post-test Retention

N X sd X sd X sd

Experimental 34 60.35 12.78 74.88 9.25 72.06 8.53


Control 34 57.88 13.00 65.18 11.03 63.41 10.89

As can be seen from the table, while the mean score of the experimental group in which Jigsaw instruction employed was 60.35; this mean score increased to 74.88 in the post-test and found to be 72.06 in the retention test. The mean scores of the control group in which traditional methods employed were 57.88, 65.18 and 63.41 respectively. According to these findings, pre-test and post-test mean scores increased both in experimental and control groups. However, considering the retention test scores, some decreases were observed in the mean scores of the candidate teachers after the administration of retention tests in both experimental and control groups after three weeks. In order to understand whether pre-test, post-test and retention test mean scores of the prospective teachers in both groups were significant, 2X3 two-way ANOVA for mixed measures was done. The results are presented in Table 2.

Table 2. ANOVA results for the experimental and control groups concerning the pre-test, post-test and retention-test scores. Source Sum of

Squares S.D. Mean Squares F p

Between groups 16566.352 67(Group) Jigsaw / Traditional 2457.176 1 2457.176 11.494 .001Error 14109.176 66 213.775Within Group 15037.333 136Measurement (Pre–Post-Retention) 4501.451 2 2250.725 29.660 .000

Group * Measurement 519.176 2 259.588 3.421 .036Error 10016.706 132 75.884Total 31603.685 203

The results show that there are significant differences before and after the treatment program among the pre, post and retention test scores of the candidate teachers (F(1-66)11.494, p<.05; ɲ2=0.078 ). This finding shows that the mean scores of prospective teachers in the experimental and control groups differentiate regardless of considering pre and post measurements. Related to the measurement main effect, it can also be understood from the table that there was a .significant difference between the mean scores of the candidate teachers in both groups from the beginning to after-treatment (F(2-132)=29.660, p<.05). These findings show that there is a significant difference between the mean scores of two groups without making group and measurement separation.

It is also observed that the attitude mean scores of the subjects participating in two different treatments, Jigsaw and traditional, significantly differs from the beginning to after-treatment. So, this finding indicates that being in different treatment groups and repeated measure factors have significant common effects on the human rights education attitudes of the prospective teachers (F(2-132)=3.421, p<.05). This finding shows that the changes in the test mean


scores of the candidate teachers in the experimental group in which Jigsaw technique employed were significantly different from the changes in the test mean scores of the candidate teachers in the control group in which traditional lecture technique employed. So, receiving cooperative (Jigsaw) and traditional instructions have different effects on increasing the achievements of candidate teachers. However, the Jigsaw instruction is more effective in retention of the knowledge gained in teacher training process, than traditional instruction. Figure 1 briefly shows and summarizes the effects of treatment program with regard to pre-test, post-test and retention scores of the prospective teachers.

Figure 1. Changes of the pre, post and retention scores in the experimental and control groups.

Discussion In this study, the experimental group which was trained with the jigsaw

technique was more successful than the control group trained with the traditional teaching-learning methods. This suggests that the jigsaw technique allowed the students to reach a maximum level of learning, by participating in the learning-teaching process personally and teaching each other. This conclusion supports the findings of a majority of other studies that show the jigsaw technique affects students’ academic accomplishments positively (i.e.. Avşar and Alkış. 2007). Jigsaw technique was also implemented in different courses and settings. In the Oscoz`s (2003) study, the Jigsaw task produces significantly more accurate language and negotiation of meaning than free discussion. In the study of Wang (2006), students learning cooperatively had higher final course grades and made more integrative statements on the measure of orientation toward learning English than students who learned using the traditional Chinese methods. In a very different learning setting, Frazee (2004) found that students in the Jigsaw class perceived more strengths and fewer weaknesses with the WebQuest than the No Jigsaw class. They also shared more positive and fewer negative remarks regarding overall satisfaction with the WebQuest experience.


321

80

70

60

50

GROUPS

Control Group

ExperımentalGroup

Literature indicates that the educators aware of the impact of cooperative activities in schools. For example,in the study of Basamh (2002), the overall attitudes of principals and teachers towards implementing cooperative learning methods were positive. The majority of the principals evaluated cooperative methods as a beneficial, %87 were willing to implement cooperative methods, %83 believe that their teachers could implement such methods, and most of them would support the implementation of cooperative learning methods.

Although the applications of the post-test and retention-test period seem to be short, a significant difference was found between the knowledge retention mean scores of the two groups in this study. Therefore, it can be concluded that although the jigsaw technique has a positive influence on the learning of materials in the educational psychology course, and it does have a more effective influence than the traditional method on retention of knowledge level of the prospective teachers. However, it is suggested for the future researchers that the period between the post-test and retention test should be longer.

Conclusion and implications Educators throughout the world accepted the positive effects of the cooperative instruction especially on learners’ social skills, as well as achievements. Many studies showed its effect on student achievement, and most of the studies specifically focused indicated its effect on the attitudes and appreciation process in learners. According to these results, jigsaw technique is suggested as a useful cooperative learning method for teaching the subjects comprising the educational psychology course, as well as other teacher training courses. But, the method may only be effective if the teachers know the cooperative learning- specifically the jigsaw technique well, and the physical educational setting is suitable to apply this technique. Since the researchers had certain difficulties with transforming the traditional environment into the cooperative one , the learning environment should be designed around the cooperative learning requirements to be more effective prior to instruction.

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A third generation personality test

Lennart Sjöberg, Ph.D.

Stockholm School of Economics Stockholm, Sweden,

And Psykologisk Metod AB Djursholm ,Sweden

Abstract

The development of personality testing in the workplace has undergone three phases. The first generation of tests, such as Cattell’s 16 PF and the British test OPQ, was characterized by complex systems for the description of the personality. These systems were simplified in part by the following generation of the test, which was based on the five factor model but that model was simple only at the horizontal level. Beneath the five main factors were a large number of ancillary factors, usually 30-40 in number. No tests of the first and second generation could effectively handle the problem of impression management, nor did they take into account the effects of mood on the test responses. These and a number of other problems were solved to a great extent in the UPP test, which therefore is proposed to represent the third generation of personality tests. The test features focusing on “narrow” and work-relevant traits, inclusion of a few aggregated variables with the same focus, including two variables especially fitted to the requirement of any given application, an effective and validated method for correction for impression management, extensive treatment of quality of data from each tested person to yield a “warning signal” when results should not be trusted, measurement of current mood at the time of testing which can give another “warning signal”, measurement of attitude towards the test (“face validity”), two types of narrative reports both to the person taking the test and the recruiter/psychologist – one based on normative comparisons and the other on ipsative (within-person) comparisons, measures of work related attitudes which are of value in themselves but can also be used as proxy criteria, greatly facilitating validation work.

Key words: personality test, impression management, mood


First generation: 1920-1990

Self-report tests of personality go back to the First World War. Until the 1960’s the American tradition was represented by factor tests such as Cattell’s 16pf - 16 factors - or Eysenck’s much simpler MPI, which only had 3 factors. The American tradition, however, came to dominate. Complex tests were most common. But Cattell, creator of the 6pf, based his test on factor analysis of small data sets. The results have never been possible to replicate (Cooper, 2002). That the first generation of personality tests resulted in a very complicated test structures was therefore probably in part - maybe entirely – due to the fact that there was no access to effective statistical and psychometric methodologies.

Some older British tests are very often used in Sweden: PPA and OPQ. They are based on older and, in the case of the OPQ, quite complex models. OPQ32r measures 32 personality variables with relatively few data, a total of 104 blocks with 3 statements in each block. The reliability of the 32 scales is doubtful. A meta-analysis of British research on the OPQ (Robertson & Kinder, 1993) showed that the test had a predictive validity of around 0.2, which is significantly worse than most other personality tests that usually lie at 0.3. In the latest development of the OPQ it has been shown that the test has a five factor (“Big Five”) structure (Brown & Bartram, 2009).

The practical application of tests is changing only slowly. The most widely used test in Sweden, PPA, is an adjective list with roots in the 1920s (Marston, 1989/1928). It measures possibly some important dimensions, but far from all of potential importance in industrial psychology applications. Another old test is MBTI is based on Jung's personality theory from the early 1920s. See a critical discussion of MBTI elsewhere (Sjöberg, 2005) or Paul’s lucid review (Paul, 2004).

Most of the first generation tests were flawed in that they resulted in an extremely complex picture of personality. They placed great demands on the experience and intuitive ability of the psychologists who used them. Validation research showed that the validity was low, around 0.3.

0.3 is a number that Mischel draw important conclusions from in his classic book from 1968 (Mischel, 1968), but already in 1921 the brothers Allport reported data at the same low level (Allport & Allport, 1921). They speculated then that it would be possible to obtain much stronger results in better tests. It has become apparent that they were wrong.

One of the basic problems of the first generation of personality tests was that it was the concern with prediction. This is in itself a worthy goal, but it is frequently unrealistic. Even if we have very effective and relevant measures of the personality dimensions there can be no guarantee that we can make predictions of how a person will succeed in a certain environment or with a specific task. There are many aspects other than his or her personality that


come into play. We do not even know how much of behavior, or job success, which in principle can be predicted on the basis of individual factors - the question is rarely discussed.

Second generation: 1990 - 2010

Around 1990 the notion of the “Big Five” was suggested (McCrae & Costa, 1987). It seemed to be a very attractive notion to apply just five factors to describe personality. American tests such as NEO-PI-R (Costa & McCrae, 1992) and HPI (Hogan, 1992) are based on this model. The international database IPIP has released test items, which may be translated and used. It also gives measures of the overall Big Five personality dimensions. These are:

Extraversion Emotional stability Conscientiousness Openness Agreeableness

The Big Five tests are the second generation of personality tests. They are less complex than the first generation tests in the sense that they focus on relatively few over-arching dimensions. But complexity is still left in the form of sub-scales, so-called facets. In the NEO-PI-R, there are 32 such subscales and complexity is therefore significantly higher than in similar tests of the first generation such as the 16pf, not to mention the structurally simpler MBTI and PPA.

Second-generation Big Five tests have had a strong impact, especially in basic research. It is often claimed that new tests should be evaluated against the Big Five to see if they add some value to the prognostic power of the tests. Extensive studies have now been made of the Big Five dimensions regarding their practical value in the workplace. The results have been disappointing, however (Morgeson, et al., 2007a, 2007b). Big Five dimensions have not produced an improved predictive power.

Second generation tests also did not solve the problem of impression management (IM) in high-stakes testing.

The third generation

The first and second generations of personality tests were facing problems that they did not manage to solve and which can be managed effectively only in a new generation of significantly enhanced tests. I shall now deal with these problems and start with impression management. My examples come from the UPP-test. UPP stands for Understanding Human Potential.


The second-generation tests, the Big Five tests, created a paradoxical difficulty: they are both too general and too detailed. On the overall Big Five-level the test are very weak in relation to the relevant criteria, but the detailed level, such as "facets" of the NEO-PI-R, gives a number of scales which are hard to manage effectively. Thirty or forty scales are too much to handle cognitively and doubts arise if all of these scales can indeed be measured reliably with a test period of 30-40 minutes.

The UPP test

UPP is a personality test intended for applications in industrial and organization settings. The test has been developed by Professor Lennart Sjöberg at the Stockholm School of Economics (SSE) and Psykologisk Metod AB, a consulting firm in applied psychology1.

The test consists of 232 items. Most are self-report items but some are of the performance type. It takes about 40 minutes to respond to all items. It is possible to respond to only some of them at one time and then return to the place in the test where responding was temporarily interrupted.

There is a norm group consisting of about 1200 persons. All scales are reliably measured and have been concept validated. External criteria have also been used with success (manager career). It is very hard to fake test results on UPP because impression management (IM) scales are used to correct for attempts to exaggerate the results.

The test is continuously improved in further research.

UPP measures a number of personality traits of importance in applied work:

Social ability Emotional intelligence Will to cooperate Endurance Positive attitude Self-confidence Creativity Perfectionism

It also measures the usual Big Five personality dimensions: Emotional stability Extraversion Conscientiousness Openness Agreeableness

1 Sjöberg was a professor of Psychology at SSE 1988-2006. He was previously a professor at the University of Göteborg and Visiting Professor at Stanford University, and University of

California, Berkeley. For further information, please see http://www.dynam-it.com/lennart/.


http://www.dynam-it.com/lennart/

http://www.dynam-it.com/lennart/

These 13 (8+5) basic scales are used to construct aggregate measures of:

Ego strength Stress sensitivity Managerial ability

Aggregate scales can also be constructed for special applications to measure both the presence of desirable traits and the absence of undesirable traits.

UPP also measures adjustment to the current work situation of the test taker. The factors measured are:

Willingness to work Work interest Job satisfaction Willingness to work with changes Result orientation Work-life balance

These dimensions are used as proxy criteria in validating the test. Dimensions such as willingness to work are credible proxies for job performance. Proxy criteria greatly simplify and encourage test validation.

Most of the scales use a self-report format. However, a special section includes the task of identifying emotions in facial expressions of the type depicted in Fig. 1.

Fig. 1. Types of facial expressions used in the UPP test. The facial expressions are judged on 8 emotion scales; consensus is used to define the “correct” answer (Sjöberg, 2001, 2008b). Relations between self-report and performance scales of emotional intelligence are fairly weak, much like the situation in research on these topics (Joseph & Newman, 2010). However, both types of scales carry important information (Engelberg & Sjöberg, 2005). The concept has many interesting implications (Engelberg & Sjöberg, 2004; Engelberg & Sjöberg, 2006; Sjöberg & Littorin, 2005).


The test also creates a narrative report about each test taker, based on explicitly described principles.

UPP has a number of unique advantages:

The effect of impression management (IM) are very salient but can be eliminated by about 90 percent. Correction for IM is done for each scale separately and is empirically based.

The 8 focused scales (see above) make possible a dramatically improved validity when compared to the traditional Big Five, about 8 times better.

The scales measuring adjustment to the current work situation can also be used as proxy criteria for the evaluation of UPP or other tests, and in co-worker studies, giving a unique chance to get a psychologically more informative view than in usual surveys.

Each test taker is assessed normatively, in relation to a norm group, and intra-individually, in relation to his or her data only.

The test assesses aggregate variables such as ego strength.

The test also assesses the quality of test data and mood, and gives a warning signal when quality is low and a re-testing is called for.

Data are collected on the test takers’ evaluation of the test, giving a measure of “face validity”

UPP is available in 7 modules:

A. The complete testB. Personality scales only (8+5 scales)C. Screening test. Five of the scales are used for a quick and efficient

screening of many applicants.D. Adjustment to the current work situation, 6 scales.E. Social and emotional ability.F. Ego strength, short scale.G. Traditional Big Five dimensions.

All modules include our method for correcting for IM. In the following sections we give selected results for some of the advantages of the UPP test.

Correcting for IM in the UPP test

A social desirability scale, or lie scale, can be used in a selection situation for weeding out those that have high value, but that strategy does not imply that the effect of impression management disappears, it is only slightly mitigated (Sjöberg, 2008a). The lie scale is typically used globally for an entire test,


while research has demonstrated that impression management is of very different importance depending on the test variable being studied. Table 1 gives an example from a study of a large data set2 from job seekers who had taken the UPP test (the screening module) in connection with applying for a job (Sjöberg, 2009). Correlations between personality variables and a measure of impression management are apparently quite variable. Hence, a global approach towards correcting for IM will fail.

Table 1. Proportion of variance accounted for by social desirability responding, N=2202.Test variable Proportion of variance explained by

tactical respondingExtraversion 0.213Endurance 0.398Will to cooperate 0.419Positive basic attitude 0.381Creativity 0.089

In the UPP test, a regression model is fitted to each test variable separately and residuals are used to estimate corrected scale values. Fig. 2 shows the results on the same data set as Table 1. Before correction there was a large difference between job applicants and norm data. After correcting for IM the difference was dramatically reduced. In several studies, we have found that about 90 percent of the effect of IM is eliminated in this manner. The approach has been validated both experimentally and on real job application data.

Figure 2. Mean values of personality dimensions before and after correction for IM, high-stakes and norm data.

Fig. 3 gives corresponding results from an experimental study where some participants were instructed to fake good, others just to answer in an honest manner.

2 These and subsequent results summarized in the present paper come from studies documented in (Sjöberg, 2008a) and the UPP test manual, available for download at http://www.psykologisk-

metod.se/files/manual%20komplett%20februari%202010.pdf.


http://www.psykologisk-metod.se/files/manual%20komplett%20februari%202010.pdf

http://www.psykologisk-metod.se/files/manual%20komplett%20februari%202010.pdf

Figure 3. Mean values of personality dimensions before and after correction for IM, experimental study.

It is interesting to note that gender differences in applications for management jobs, favouring men over women, are greatly reduced due to IM correction, see Fig. 4.

Figure 4. Raw and corrected scores in emotional stability of men and women applying for management jobs,

Clearly, if women answer in a more honest way than men do they will be at a disadvantage in career contexts. The UPP test counteracts the drawbacks of female honesty. No other test does so, as far as is known. In one study it was also found that immigrants were at a similar disadvantage when having taken a personality test, a disadvantage which was eliminated by our method for correcting for IM.

Mood and test results

It is likely that responses on a personality test are affected by the current mood state of the testee, but this is seldom attended to in practical testing. Table 2 shows correlations between Big Five test dimensions and mood state at the time of testing. Mood was measured with a scale constructed by


Sjöberg, Svensson and Persson (Sjöberg, Svensson, & Persson, 1979), which has been widely used. The data are from testing applicants to the Stockholm School of Economics.

Table 2. Correlations between Big Five personality scales and current mood state, high-stakes testing, N=210.

Mood dimensionPersonality scale Happy-sad Alert-tired Calm-tense Pooled

measure of mood

Agreeableness 0.09 0.11 0.08 0.11Emotional stability 0.50** 0.35** 0.38** 0.50**Openness 0.38** 0.50** 0.21** 0.41**

Extraversion 0.43** 0.37** 0.22** 0.39**Conscientiousness 0.01 0.30** 0.03 0.11** p<0.01

The table shows that three of the five dimensions were rather strongly correlated with mood. Extreme groups show the results even more clearly, see Fig. 5, where the 10 percent worst mood cases are compared with the rest of the testees in standardized scores.

Figure 5. Mean personality scales values for the 10% of the test takers who were in the worst mood, compared to all others. Data from a high-stakes situation.

The data suggest that a low mood can lead to distorted values on a personality scale. For this reason, the UPP test includes scales for measuring mood. This is an aspect of data quality and a low mood constitutes a warning signal. Possibly, it should lead to repeated testing at a later occasion, or to caution in interpreting the test results. Other aspects of data quality are treated in the subsequent section.


Data quality

Data quality is important for using the results of a personality test. Some people are not careful when responding, others do not understand the task and the items as intended. Impression management is ever present.

UPP uses the following quality indices:

Acquiescence (negative indicator)Intra-individual variability (positive indicator)Similarity of responses in relation to group means (positive)Social desirability scales, overt (negative)Social desirability scale, covert (negative)

These indices were correlated, suggesting that they could be used to construct a pooled measure of data quality. It was found that data quality was:

Higher for women than for men Higher for older than younger people Higher for test takers with a higher level of education Higher under high-stakes testing than low-stakes testing

Fig. 6 shows the relationship between mean data quality and level of education, separately for men and women.

Figure 6. Mean data quality for men and womenat different levels of education.

Errors in predicting a pooled measure of the proxy criteria (absolute scores) from the personality scales (multiple regression) are plotted against the index of data quality in Fig . 7.


Figure 7. Mean absolute prediction error plotted against data quality (percentile groups).

A low value of data quality is a warning signal and the test should be taken anew, or disregarded.

Attitude towards the test: “Face validity”

It is important to know about the test takers’ attitudes towards the test, which is sometimes called face validity. A negative evaluation of the test by the test taker is an indication that something went wrong and should be followed up in an interview and possibly a renewed testing. The UPP test therefore is concluded with 8 questions measuring attitude towards the test; these questions are correlated and are used to estimate a pooled measure of attitude. The distribution of attitude ratings for 103 test takers is provided in Fig. 8.

5,004,504,003,503,002,502,00

Attitude towards the UPP test

25

20

15

10

5

0

Freq

uenc

y

Figure 8. Distribution of mean ratings of attitudes towards the UPP test.

The figure shows an overwhelmingly positive attitude towards the test.


Validation of the UPP test

External criteria

Social job skills were measured in one study and related to the UPP, see Table 3.

Table 3. Hierarchic regression analysis of social job skills related to the UPP tests.Block of independent variables

R2adj Δ R2 F for

ΔR2df p

Step 1: The FFM model

0.105 - - 0.006 (The FFM model)

Step 2: FFM + emotional intelligence and social ability

0.323 0.221 17.320 2,99 <0.0005 (Added explanatory power)

The level of explained variance reached, 32.3 %, corresponds to a correlation of 0.57 with the criterion. The two pertinent UPP variables contributed dramatically better than the FFM model. A gender difference in emotional intelligence is illustrated in Fig. 9. It is well known that women tend to have a higher emotional intelligence than men (Joseph & Newman, 2010).

Figure 9. Gender and emotional intelligence


Figure 10. Civil status and emotional intelligence.

Management career was related to the UPP test, see Table 4. The criterion was binary: manager or not manager.

Table 4. Hierarchical binary regression analysis of manager responsibility against the UPP test. N=107. Block R, Cox

& SnellR, Nagelkerke

χ 2 df p

The entire UPP test 0.412 0.516 18.968 3 <0.0005The FFM model variables

0.045 0.055 0.172 1 0.678

UPP variables beyond FFM

0.410 0.507 18.280 2 <0.0005

The criterion validity of the UPP is very satisfactory in these data. A final validation of the test is reported here, using proxy variables. See Table 5.

Table 5. Validation against 6 proxy criteria (squared multiple correlations). Criterion The FFM model The UPP testWillingness to work with changes

0.137 0.274

Job satisfaction 0.008 0.454Willingness to work 0.010 0.475Result orientation 0.106 0.212Work interest 0.054 0.389Balance life/work 0.045 0.097

Mean 0.041 0.317

The improvement in validity beyond the FFM was highly statistically significant in all cases, and dramatically large. A mean explained variance of 0.317 corresponds to a criterion correlation of 0.56, very close to other data


presented in this paper and much better than the common results for tests of the first and second generations, which tend to lie in the interval 0.2 – 0.3.

Conclusion

Personality testing has developed slowly over almost a century. Some still widely used tests (first generation, 1920-1990) are based on notions from the 1940’s or even earlier. In the second generation (1990-2010) of tests, Big Five dimensions dominated, but they are too broad to be of practical value. The UPP test solved these and a number of other problems. The original Swedish version is now being translated and standardized for a number of other languages.

References

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Cooper, C. (2002). Individual differences. 2nd edition. London: Hodder Education.

Costa, P. T., Jr, & McCrae, R. R. (1992). NEO PI-R professional manual. Odessa, FL: Psychological Assessment Resources, Inc.

Engelberg, E., & Sjöberg, L. (2004). Internet use, social skills, and adjustment. Cyberpsychology & Behavior, 7(1), 41-47.

Engelberg, E., & Sjöberg, L. (2005). Emotional intelligence and interpersonal skills. In R. D. Roberts & R. Schulze (Eds.), International handbook of emotional intelligence (pp. 289-308). Cambridge MA: Hogrefe.

Engelberg, E., & Sjöberg, L. (2006). Money attitudes and emotional intelligence. Journal of Applied Social Psychology, 36(8), 2027-2047.

Hogan, R. (1992). Hogan Personality Inventory. Psychological Test Bulletin, 5(2), 130-136.

Joseph, D. L., & Newman, D. A. (2010). Emotional intelligence: An integrative meta-analysis and cascading model. [doi:10.1037/a0017286]. Journal of Applied Psychology, 95(1), 54-78.

Marston, W. M. (1989/1928). Emotions of normal people. Ormskirk, Lancs.: Thomas Lyster.

McCrae, R. R., & Costa, P. T., Jr. (1987). Validation of the five-factor model of personality across instruments and observers. Journal of Personality and Social Psychology, 52, 81-90.

Mischel, W. (1968). Personality and assessment. New York: Wiley.Morgeson, F. P., Campion, M. A., Dipboye, R. L., Hollenbeck, J. R., Murphy,

K., & Schmitt, N. (2007a). Are we getting fooled again? Coming to terms with limitations in the use of personality tests for personnel selection. Personnel Psychology, 60(4), 1029-1049.

Morgeson, F. P., Campion, M. A., Dipboye, R. L., Hollenbeck, J. R., Murphy, K., & Schmitt, N. (2007b). Reconsidering the use of personality tests in personnel selection contexts. Personnel Psychology, 60(3), 683-729.


Paul, A. M. (2004). The cult of personality. How personality tests are leading us to miseducate our children, mismanage our companies, and misunderstanding ourselves. New York: Free Press.

Robertson, I. T., & Kinder, A. (1993). Personality and job competences: The criterion-related validity of some personality variables. Journal of Occupational & Organizational Psychology, 66(3), 225-244.

Sjöberg, L. (2001). Emotional intelligence: A psychometric analysis. European Psychologist, 6, 79-95.

Sjöberg, L. (2005). En kritisk diskussion av Myers-Briggs testet. (A critical discussion of the Myers-Briggs test). Organisational Theory & Practice. Scandinavian Journal of Organisational Psychology, 15(1), 21-28.

Sjöberg, L. (2008a). Bortom Big Five: Konstruktion och validering av ett personlighetstest. (Beyond Big Five: Construction and validation of a personality test) (SSE/EFI Working Paper Series in Business Administration No. 2008:7). Stockholm: Stockholm School of Economics.

Sjöberg, L. (2008b). Emotional intelligence and life adjustment. In J. C. Cassady & M. A. Eissa (Eds.), Emotional Intelligence: Perspectives on Educational & Positive Psychology (pp. 169-183). New York: Peter Lang Publishing.

Sjöberg, L. (2009). UPP-testet: Korrektion för skönmålning. (The UPP test: Correction for impression management). Stockholm: Psykologisk Metod AB.

Sjöberg, L., & Littorin, P. (2005). Emotional intelligence, personality and sales performance. In K. B. S. Kumar (Ed.), Emotional intelligence. Research insights (pp. 126-142). Hyderabad, India: ICFAI University Press.

Sjöberg, L., Svensson, E., & Persson, L.-O. (1979). The measurement of mood. Scandinavian Journal of Psychology, 20(1), 1-18.


Relationship Between Senior Secondary School Students’ Computer Literacy

Skill And Science Achievement

Olatoye, R.A. (PhD)1 , E. Mosunmola Aanu (M.Ed),2

1.Department of Science, Technology and Mathematics Education,College of Education, Ipetu-Ijesa Campus, Osun State, University,Osogbo, Osun State, Nigeria, E-mail: [email protected].

2.Faculty of Education, Department of Curriculum Studies and Instructional Technology, Olabisi Onabanjo University, Ago-Iwoye, Ogun State, Nigeria. E-mail: [email protected]

Abstract

This study investigated relationship between Senior Secondary School Students’ Computer Literacy Skill and Science Achievement. It also attempted to find out how computer literacy predicts achievement in the various science subjects. Two hundred students randomly selected from the Senior Secondary Schools in two Local Government Areas in Ogun State were used for the study. Computer Literacy Skill Test and Science Achievement Test were administered on the students. There was a significant positive relationship between computer literacy skills and science achievement (r = +0.701, p<0.05). Computer Literacy skill also accounted for 49.2% of the total variance in science achievement (R Square = 0.492, p<0.05). In order to facilitate the use of Computer Assisted Instruction in schools, students and teachers should be encouraged to improve their computer literacy skills.

Key Words: Computer Literacy, Computer Literacy Skill, Science Achievement, Nigeria

Introduction

The introduction of computer is the major and most influential technology of the millennium. This has made the impact of technology greater felt in all sectors of a nation’s economy (Abimbade, Aremu & Adedoja, 2003). Through the introduction of this technology, the world today is reaping the benefit of Information Technology. Crompton (1989) observed that the use of computer can help to facilitate almost all learning experiences like problem-solving, reasoning and retention. The use of computer and computer software no doubt has helped in the area of reading skill and mathematical problem-solving. Students with high level of computer skill are likely to perform better academically.



The Federal Republic of Nigeria (1989) National Policy on Computer Education states the objectives of Computer Education at Secondary School level as following:

(i) Show the impact of Information and Computer Technology on today’s society.

(ii) Develop rudimentary knowledge about information systems, information processing techniques and the role of computer in this regard.

(iii) Understand the historical overview and the development of modern day computer basic components.

(iv) Know the use of which computers are put in everyday life.(v) Explain how computer works(vi) Understand the basic principles of computer operating systems.(vii) Use pre-programmed packages which are relevant to the

interest of the students as teaching aids in different subjects.(viii) Introduce the concept of different computer language and their

application; and(ix) Appreciate problem-solving techniques as they apply to the

computer programme design, coding and documentation. One of the general policy objectives of computer literacy according to

Federal Republic of Nigeria (1989) National Policy on Computer Education is to enable the school children at different levels of education appreciate the potential of the computer and be able to utilize it in various aspects of life and later occupation. This is very important because of the modern-range application of computers. Muideen (2004) asserted that the introduction of computers in industries, universities, homes, offices, business ventures and so on and increase in computer application in most of our daily activities have made it mandatory to search for the basic knowledge of computer.

Award (1988) described the involvement of computer in a range of human activities from the biggest project such as space exploitation, survey and air travels to medicine, telecommunication, accounting, homes,, offices and agriculture down to security, crime detection, radio and television services. Afuwape (2004) noted that computers have found applications in education, more importantly in the teaching of some difficult concepts in Integrated Science. These are the concepts teachers and students in Nigeria perceive difficult to teach. To really prove the effectiveness of Computer-Assisted Instruction (CAI) in supporting teaching of some difficult concepts in science, a study conducted by Abimbola and Egunjobi (2003) recommended that learners and teachers should be computer literate. Also, particular attention should be paid to the adoption and utilization of the Computer-Assisted Instruction (CAI) in various school subjects.

Many studies have been carried out on effect of CAI on students’ achievement in science and other subjects. CAI has been found to improve students’ achievement in computer science (Raji & Ayoade, 2004), Integrated Science (Afuwape, 2004), general teaching and learning (Jegede, Okebukola & Ajewole, 1990). However, much cannot be achieved in the use of CAI if


teachers and students are not computer literate (Abimbola & Egunjobi, 2003), hence there is need for a study that will find out how level of computer literacy skill influence science achievement. If positive relationship exists between level of computer literacy and science achievement, then

(i) Using CAI will further enhance the teaching of science.(ii) Students’ ability to use computer skill to source for materials on

science on the web would be enhanced. (iii) Use of computer tutorial lectures for personal study of science

would be enhanced.(iv) There is justification for demanding credit pass in the science

subjects in order to study computer science in the University.

This is an era where innovation is highly necessary in science teaching. Monk and Osborne (2000) noted the deplorable levels of science achievement in schools has necessitated the call by government and several researchers for some positive action to be initiated in order to put science achievement back on track. Olagunju, Adesoji, Iroegbu and Ige (2003) opined that without introducing changes and innovations, our educational systems could not meet the challenges and solve problems of modern society. As innovations are being introduced in science teaching in form of CAI, a question needs to be answered. “Does student level of computer literacy skill influence achievement in science?” It is expected that the more a student becomes computer literate; the better should be his/her ability to use the higher level of literacy to enhance achievement in science. This study therefore sought to find out relationship between Senior Secondary student level of computer literacy skill and achievement in science in Ogun State, Nigeria.

Research Questions

1. What is the relationship between student computer literacy skill and science achievement?

2. To what extent will student achievement in computer literacy skill predict science achievement?

3. To what extent will student computer literacy skill predict achievement in biology?

4. To what extent will student computer literacy skill predict achievement in chemistry?

5. To what extent will student computer literacy skill predict achievement in

physics?6. What percentage of variance (R2) does computer literacy skill accounts

for in achievement in each of the science subjects?7. What is the relationship between computer literacy skill and

achievement in each of the science subjects?8. Is there any significant difference in female and male student:

(i) Computer literacy skill(ii) Science achievement?


Methodology

Target Population and Sample

The target population for this study was all the Senior Secondary Students offering computer science in public schools in Ogun State. Two Local Government Areas (LGAs) were judgmentally selected for the study. They are Ijebu-Ode and Ikenne LGAs. These two LGAs were chosen because they are in different zones in the state. Also many schools in the LGAs have been established for many years and therefore have computer teachers and facilities. One of the problems encountered while carrying out this study was that quite a number of schools do not have computer teachers and/or facilities and they are not offering computer science. Five secondary schools were therefore purposely selected from each LGA. The schools selected had:

(i) Students offering computer science at SS 3 level(ii) Students that were willing to participate in the study and

teachers who were also willing to co-operate.(iii) Students that have been introduced to computer science for at

least two years.(iv) Students that are offering all the three science namely biology,

chemistry and physics.

Twenty students offering computer science and all the three science subjects (biology, chemistry and physics) in SS3 class were randomly selected from each of the ten schools. In other words, two hundred SS 3 students participated in the study.

Instrumentation

Two instruments were use to collect data.(i) Computer Literacy Skill Test (CLST) and (ii) Science Achievement Test (SCAT)

Computer Literacy Skill Test (CLST)

CLST is divided into two sections. Section A elicits information from the respondents on demographic variables such as gender and school location. Section B contains a 25-item multiple-choice objective test with options A to E. The maximum obtainable mark was 25. Students were asked not to write their names on the answer sheets in order to make responses anonymous. The researchers had earlier visited the schools to collect topics that had been covered in computer science in order generate items only on those topics. This was done in order to ensure content validity of the test. The CLST also contains items that required the students to demonstrate practical knowledge of computer. The items in the test covered different topics in the syllabus. The researcher gave the test to experienced computer science teachers to comment on the suitability of each item. Modifications were made based on suggestions given. All these precautionary measures were taken to ensure the context validity of the test. Cronbach alpha reliability co-efficient is 0.751


Science Achievement Test (SCAT)

SCAT contains three sections namely biology, chemistry and physics. Each section has 25 items. The maximum obtainable mark therefore was 75 on SCAT. Like the construction of CLST the researcher had earlier visited the schools to collect scheme of work in various science subjects. Almost all topics in the syllabus had been covered because the selected students were about to write the Senior Secondary School Certificate Examinations. The items in the test covered different topics in the syllabus. The researcher gave the test to experienced science teachers to comment on the suitability of each item. Modifications were made based on suggestions given. All these precautionary measures were taken to ensure the content validity of the test. Cronbach alpha reliability co-efficient is 0.789.

Data AnalysisData analysis was done using Pearson product-moment correlation, t-

test and regression analyses.

Results.

Research Question 1: What is the relationship between student computer literacy skill and science achievement?

Table 1: Relationship between student computer skill and science achievement

N Mean StandardDeviation

r P value

Remark

Computer Skill 200 14.21 4.33

+0.701 0.000 *

Science

Achievement 200 40.00 10.50

*Significant (p<0.05).

There is a significant positive relationship between student computer literacy skill and science achievement (r = +0.701, p<0.05). This implies that the higher the computer skill, the greater the science achievement. A student who has a very good computer literacy skill is also likely to have good science achievement. A student who has poor computer literacy skill is likely to be poor in science.


Research Question 2: To what extent will students’ computer literate skill predict science achievement?

Table 2: Student Computer Skill as a predictor of Science Achievement

R = 0.701

R Square = 0.492

Adjusted R Square = 0.489

Standard Error = 7.519

Analysis of variance

Source of

variation

Sum of

Square

Df Mean

Square

F Sign

value

Remark

Regression

Residual

Total

10830.106

11192.849

1007.373

1

198

199

10830.106

56.530

191.583 0.000 Significant

(p<0.05)

In Table 2 above, students’ computer literacy skill significantly predicts science achievement. Computer literacy skill accounts for 49.2% of the total variance in science achievement (R Square = 0.492, p<0.05). This percentage is high and significant. In predicting science achievement, computer literacy skill is very important. A student that has a high level of computer literacy skill is also likely to have high science achievement.Research Question 3: To what extent will students’ computer skill predict achievement in biology?

Table 3: Student computer skill as a predictor of achievement in biology

R = 0.569

R Square = 0.324




F P Remark

Regression

Residual

Total

1033.193

2158.002

3191.195

1

198

199

1033.193

10.899

94.797 0.000 *

(p<0.05)

*Significant


Table 3 shows how computer literacy skill predicts student achievement in biology only. While computer literacy skill accounts for 49.2% of the total variance in science achievement (Table 2), it accounts for 32.4% of the total variance in biology achievement (Table 3). This percentage is also high and significant (R Square = 0.324, p<0.05). In predicting biology achievement, therefore, computer literacy skill is very important. A student that has a high level of computer literacy is also likely to have high science achievement.

Research Question 4: To what extent will student computer literacy predict achievement in chemistry?

Table 4: Student computer literacy as a predictor of achievement in chemistry

R = 0.603

R Square = 0.363




Source of

variation

Sum of

Square

Df Mean

Square

F Sig.

value

Remark

Regression

Residual

Total

1184.259

2075.021

3259.280

1

198

199

1184.259

10.480

113.003 0.000 *

* Significant (p<0.05)

In Table 4 above, student computer literacy skill accounts for 36.3% of the total variance in chemistry achievement (R Square = 0.363, p<0.05). This percentage is high and significant. In predicting chemistry achievement, therefore, computer literacy skill is important. Students with high computer literacy skill are also very likely to have high scores in chemistry.Research Question 5: To what extent will student computer literacy skill predict achievement in physics?


Table 5: Student computer literacy skill as a predictor of achievement in Physics

R = 0.604

R Square = 0.365




Sum of

Square

Df Mean

Square

F P Remark

Regression

Residual

Total

1407.106

2452.394

3859.500

1

198

199

1407.106

12.386

113.606 0.000 *


In Table 5 above, student computer literacy skill accounts for 36.5% of the total variance in physics achievement (R Square = 0.356, p<0.05). This percentage is high and significant. In predicting physics achievement, therefore computer literacy skill is important. Students with high computer literacy skill are also very likely to have high scores in physics.Research Question 6: What percentage of variance (R2) does computer literacy skill

accounts for in achievement in each of the science subjects?

Table 6: Co-efficients of Determination (R2) of computer skill on each of the science subjectsSubject R2 Rank F P Remark

Biology

Chemistry

Physics

Science

0.324

0.363

0.365

0.492

4th

3rd

2nd

1st

94.792

113.003

113.606

191.583

0.000

0.000

0.000

0.000

Significant (p<0.05)




Table 6 is a summary of coefficients of determination (R Squares) in Tables 2 to 5. Computer literacy skill accounts for the highest variance of 49.2% (R


Square = 0.492) in general science achievement. Science achievement is the total score of each student in biology, chemistry, and physics. The lowest variance is in biology where the variance accounted for in biology achievement is 32.4% (R Square = 0.324). The order is Science> Physics> Chemistry> Biology.

Research Question 7: What is the relationship between student computer literacy skill and achievement in each of the science subjects?

Table 7: Correlation Matrix of student computer literacy skill and achievement in the science subjects

Biology Chemistry Physics Computer Science

Biology 1.000

Chemistry 0.518* 1.000

Physics 0.553* 0.634* 1.000

Computer 0.564* 0.603* 0.604* 1.000

Science 0.811* 0.847* 0.873* 0.701* 1.000


In Table 7 above students’ overall achievement in science has high significant positive relationship with achievement in every other subject. The highest relationship is between student overall achievement in science and physics (r = +0.873). The lowest is between chemistry and biology achievement (r = +0.518). There is high positive relationship between computer literacy skill and science achievement as earlier reported in Table 1 (r= +0.701).Research Question 8: Is there any significant difference in female and male students’ (i) Computer Literacy Skill and (ii) Science Achievement?

Table 8: Comparison of female and male students’ computer literacy skill and science achievementSubject Gender N Mean Standard

Deviation

Standard

Error

Df t p Remark

Computer

skill

Female 91 14.418 4.475 0.469

198 0.826 0.409 NSMale 109 13.908 4.213 0.404

Science

achievement

Female 91 39.747 10.049 1.054

198 -0.328 0.743 NSMale 109 40.239 10.938 1.048

NS = Not Significant (p>0.05)

In Table 8 above, there is no significant relationship between levels of female and male students’ computer literacy skill (t = 0.826, p<0.05). There is


also no significant relationship between male and female student science achievement.

Discussion of Findings

There is positive significant relationship between computer literacy skill and science achievement. Computer literacy skill also significantly predicts science achievement. These findings show that the use of Computer-Assisted Instruction (CAI) in the classroom will facilitate science teaching. CAI has been found to improve student achievement in computer science (Raji & Ayoade, 2004), in integrated science (Afuwape, 2004) teaching and learning (Jegede, Okebukola & Ajewole, 1990). The barrier of lack of computer skill that may be posed in trying to use CAI will be minimal if there is already high relationship between computer literacy and science achievement.

This study also proves that high positive relationship is not only for science achievement in general but for each science subjects also. Hence, CAI will be very useful in teaching biology, chemistry and physics. This is an era when innovation is highly needed in order to revolutionalise teaching of science (Olagunju, Adesoji, Iroegbu & Ige, 2003). In this study, there is no significant different between computer literacy skill and science achievement of male and female students. On gender and computer literacy skill, Workforce on Computer Education (2004) reported that women are more in computer operation and data entry, they are however grossly under-represented as electrical and electronic engineers, computer system analysts and scientists, operation and system researchers/analysts and programmers. Adebanjo (2004) reported that there is no significant difference in the level of utilization of computer between male and female students. However, Shashasi (1997) observed that female students are less interested in computer and less confident in the operation of computer than their male counterparts are. Adebanjo (2004) also reported that science students had better attitude to computer and utilize computer systems more frequently than the social science students.

Conclusion and Recommendations

A good exposure of students to computer literacy skill will facilitate science teaching in an era when computer is being used to assist learning. The first challenge therefore is to ensure that both teachers and students are well disposed to the use of computer so that there could be full realization of the benefits accrued in its use. A student who is highly computer literate is also able to search for course for materials on the internet, complete his/her assignment on time, make use of tutorial facilities on computer and cope with the challenges of understanding scientific concepts taught using Computer Assisted Instruction (CAI).

In order to facilitate the use CAI in schools, students and teachers should be encouraged to improve on their computer literacy skills. Stakeholders in education should be encouraged to provide enough computers for students in


order to improve level of science achievement, which will in turn improve our technological development.

References

Abimbade A. & Egunjobi A.O. (2003): Efficacy of two Computer-Assisted in Structural modes on Secondary School Students’ Achievement in Practical Geography in Ibadan Metropolis, Nigeria, Nigeria Journal of Computer Literacy,Vol. 4, 102-112.Abimbade, A. Aremu, A. & Adedoja, G. O. (2003). Providing Information Communication Technology (ICT) Environments for Teaching and Learning in the Nigeria Educational System. In: O.A. Bamisaiye, I. A .Nwazuoke & A. Okediran (Eds). Education This Millennium –Innovations in Theory and Practice. Lagos: Macmillan Nigeria Publishers Limited.Adebanjo, A.A. (2004). The attitude and gender difference in the utilization of computer among undergraduates. Nigerian Journal of Computer Literacy. 5(1). Pp. 171-183.Afuwape, M.O. (2004). The effect of Computer-Assisted Instruction on students’ attitude towards Integrated Science Nigeria. Journal of Computer Literacy. 5(1). Pp.40-51.Award, E.M. (1988). Management Information System: Concepts Structure and Application California; The Benjamin Cummings Publishing Company Inc.Crompton, R(Ed) (1989). Computer in Primary Curriculum 3-B ,UK: The Falmer Press.Federal Republic of Nigeria (1989). National Policy on Computer Education, Lagos: Federal Ministry of Education.Federal Republic of Nigeria (1998). National Policy on Computer Education. Lagos: Federal Ministry of Education.Jegede, O.J., Okebukola, P.A.O., Ajewole, G.A. (1990). Attitude to the use of the computer for learning biological concepts and achievement of students in an environment dominated by indigenous technology. Paper presented at the 63rd Annual Meeting of the National Association for Science teaching (NARST), Atlanta, G.A, U.S.A. Monk, M. Osborne, J. (2000).Good practices in science teaching Burkingham: Open University Press.Muideen, B.A. (2004). Computer Instruction: An Approach that expedites the system of Education. Nigeria Journal of Computer Literacy. 5(1). Pp. 21-31.Olagunju, A.M. Adesoji, F.A., Iroegbu, T.O. & Ige, T.A. (2003). Innovations in science teaching for the millennium. In: O.A. Bamisaiye, I.A. Nwazuoke & A. Okediran (Eds). Education This Millennium – Innovations in Theory and Practice. Lagos: Macmillan Limited.Raji, M.O. & Ayoade, O.B. (2004). Effect of the use of Traditional Teacher Directed Instruction (TTDT) and Computer-Assisted Instruction(CAI) on students’ academic achievement in computer science. Nigeria Journal of Computer Literacy 5(1). Pp. 1-10.


Shashasi, L. (1997).Gender Differences in Computer Attitude and Use Among College Students. Journal of Educational Computing Research, 16(1). Pp.37-51.Workforce on Computer Education (2004). Women in computer operation. Visit: http://www.itaa.org/workforce.


http://www.itaa.org/workforce

Communication Skills In Children With Autism: The Effect Of The Social Stories Technique

Mohamed Ali , Abdullhamid, PhD Head of Educational Psychology Dept., Suez University, Al Raish , Egypt

Abstract

Introduction. This study explores whether or not Social Stories Intervention

Strategy have positive effects on communication skills of children with

autism.

Method. Thirty children diagnosed as having autism disorder participated in the study. The study followed the pretest-post-test control group design to examine the effectiveness of the social stories Intervention Strategy on communication skills of children with autism.

Results. Findings from this study indicated the effectiveness of the social stories intervention employed in improving communication skills of children with autism.

Discussion. On the basis of the findings, the study advocated for the effectiveness of the social stories intervention employed in improving communication skills of children with autism.

Keywords: Social stories, social communication , Social Stories Intervention

Strategy, autism

INTRODUCTION

Communication is the basis of all human interaction. The ability to communicate and process communication varies from person-to-person. The more sophisticated this ability, the greater the learning capacity and vice versa. From the most primitive to the most modern society communication is seen as a vehicle for taking personal and social needs forward.

Communication includes the spoken and written word, signal, sounds, gestures, signs, pictures, symbols, music and body language. Communication is a powerful tool, an eloquent weapon, a manipulative agent, a distinctive attribute and as recognizable for each individual as is appearance. Disordered


communication can prevent a person from realizing his or her potential. A communication disorder is an impairment in the ability to receive and/or process a symbol system; represent concepts of symbol systems; and/or transmit and use symbol system.

Autism is a disability characterized by impaired social interactions, limited verbal and nonverbal communication, and restricted and repetitive patterns of behavior. Children with autism may not make friends, spend more time alone than with others, and may not develop empathy or other forms of social reciprocity. They may exhibit stereotypical behaviors to the exclusion of all other activities, may engage in echolalia if any speech at all, and may also engage in dangerous behaviors such as aggression or self-injury (National Institutes of Child Health and Human Development, 2006).

Autism is one of several developmental disorders that falls along what has become known as the autism spectrum. Other disorders on the “spectrum” are Asperger Syndrome, Pervasive Developmental Disorder, and Childhood Disintigrative Disorder. Incidence rates of Autism Spectrum Disorder (ASD) are varied depending on the source. The most recent assessment from The Centers for Disease Control (2006) estimates that Autism Spectrum Disorder (ASD) affects one in 150 children.

Social Stories

As a special education teacher Carol Gray worked with children with autism for a number of years before coming up with the idea of social stories. Social stories are generally promoted as a quick and easy way to produce dramatic behavior change in children with autism. Social stories are actually short “stories” written to describe specific social situations that have been identified as troublesome for children with autism. The story, written from the child’s point of view and at the child’s level, describes appropriate behaviors and the appropriate “cues” or stimuli to set the occasion for these behaviors (Gray, 1995). Gray bases this on evidence from empirical research conducted by developmental experts in Theory of Mind (ToM). Social stories have been used, with varying degrees of success, to teach specific social skills, provide instruction on appropriate behavior during specific activities (e.g., bedtime, trips to the dentist, lunch time), to prepare subjects for new routines or activities, and to teach behaviors as replacements for targeted inappropriate behaviors in children with autism (e.g., decrease inappropriate “staring”, chair tipping, calling out) (Ivey, Heflin, & Alberto, 2004; Thiemann & Goldstein, 2001; Burke, Kuhn, & Peterson, 2004; Sansosti & Powell-Smith, 2006; Scattone, Wilczynski, Edwards, & Rabian, 2002).

Much of the literature on social stories actually indicates that while social stories are antecedent interventions intended to identify social cues for appropriate behavior, reports from many authors indicate that teacher prompts and possibly even reinforcers may be the contributing factor when social stories are successful (Crozier & Tincani, 2005; Norris & Dattilo,1999;


Sansosti & Powell-Smith,2006; Scattone, Wilczynski, Edwards, & Rabian, 2002).

Theory of Mind.

Gray and Garand (1993) proposed that social stories are appropriate and effective interventions for people with autism because they are specifically designed to address deficits in Theory of Mind (ToM). Gray surmises that children with autism may behave more appropriately if they understand all of the social nuances of various situations. Social stories are designed to teach the child about how those social situations work. Relative to autism and other ASD, the Theory of Mind hypothesis suggests that individuals with autism lack the ability to understand mental states in themselves and others (Yirmiya, Erel, Shaked, & Solomonica-Levi, 1998). This involves an individual being able to propose the existence of mental states in another person and then using these mental states to explain and predict another person’s behavior (Baron-Cohen, 1996).

This specific attribution to children with autism (as opposed to children with any, non-specific developmental disorder) arose out of research that demonstrated that many children with autism (but not all), in direct contrast to children with mental retardation or typical children, were unable to attribute false belief to others or to be able to identify someone’s “intention” when looking at picture stories. In a recent meta-analysis of literature comparing the performance of typical individuals, those with autism, and those with mental retardation on Theory of Mind tasks, the authors found than in 17 of 24 opportunities individuals with mental retardation performed better than those with autism on ToM tasks and in 15 of 22 opportunities typically developing individuals performed better than those with autism (Yirmiya et al., 1998). In a more recent study, Pellicano (2007) compared scores on ToM tasks with those of Executive Function in children with autism and typically developing children. She found that 40% of children with autism demonstrated impairments in both ToM and Executive Function and 17% showed impaired ToM with no deficits in Executive Function. One third of children with autism had no deficits in ToM or Executive Function. She also found that children with a higher verbal IQ were less impaired than those with a lower verbal IQ. Her results are commensurate with those of earlier researchers.

In a typically developing child, ToM develops in a relatively stable and predictable sequence. For example, by 18 months a typical child begins to engage in symbolic play. By 3 years, children begin to understand that there are differences between their own mental states and others, especially with regards to perception. Three-year-olds can differentiate between perceptions, desires and beliefs, which are based on reality and images and dreams, which (according to a three-year-old) are not. Four-year-olds first begin to conceptualize false beliefs and can pass the false belief tests on which much of the ToM research with autism has been based (Yirmiya et al 1998).


Common false belief tests include the Sally and Anne test in which the experimenter uses two dolls, "Sally" and "Anne". Sally has a basket and Anne has a box. Experimenters show children a play, where the Sally doll puts a marble in her basket and then leaves. While Sally is away, the Anne doll takes the marble out of Sally's basket and puts it into her box. The children are asked where they think Sally will look for her marble when she returns.

Children are said to "pass" the test if they understand that Sally will most likely look inside her basket before realizing that her marble isn't there. Typical children under the age of four, along with most children with autism (of any age), will answer "Anne's box," apparently unaware that Sally does not know her marble has been moved (Yirmiya et al, 1998). As this test demonstrates, tests of ToM are scored as passing or failing, which seems to indicate that ToM is singular and that one has it or doesn’t. However there is much disagreement in the ToM research over when it actually emerges and to what extent false belief is a global measure of ToM (Tager-Flusberg, 2001).

Tager-Flusberg (2001) posits the following as a more developmental perspective of ToM in children with autism, “deficits in theory of mind in autism need to be defined as differences in the rate of developmental change in this domain…more emphasis should be placed on individual differences in the degree of impairment”. Using this as a guideline, one might hypothesize that ToM could be taught to children with autism. Several studies have been published in which participants were taught to pass tests of ToM, however the generalization of those skills to real life social situations was limited (Hadwin, Baron-Cohen, Howlin, & Hill, 1997; Ozonoff & Miller, 1995). For example, Ozonoff and Miller (1995) demonstrated that children with autism with IQs above 70 were able to pass false belief tests after training. However, parent and teacher ratings of social skills indicated no change after intervention. Hadwin et al (1997) measured conversation skills in children with autism after providing training in one of three areas: pretend play, understanding emotions, or understanding belief. They found that participants could be taught belief and emotions, but that play skills did not increase with teaching. In addition, they found that increases in understanding emotions and beliefs did not result in subsequent increases in conversational skills. In contrast, Chin and Bernard-Opitz (2000) taught children with autism specific conversational skills and then measured performance on false belief tests to determine if acquisition of social skills would impact ToM. They found that while conversation skills did increase with training for two of three subjects, performance on ToM tasks did not.


It is possible that teaching social skills may indeed impact ToM, but that false belief tests are inappropriate for measuring socially valid gains in ToM. Social stories may impact ToM in children with autism, however there is not yet an appropriate measure of social interactions as they relate to ToM. One additional objection to Theory of Mind as a theoretical basis for social stories as an intervention is that as a cognitive construct it should not lend itself to reversibility in single subject designs. Changes in cognition should be relatively permanent, and therefore should not respond to a withdrawal of treatment, however some of the studies to be discussed in this article do demonstrate experimental control with reversal designs.

Gray and Garand (1993), the seminal article. Gray and Garand first described social stories in 1993. In their paper the authors provided a rationale for using social stories and some anecdotal evidence supporting their usage. They proposed that a child with autism has specific impairments in the area of perspective taking. That is, a child with autism is assumed to lack the ability to “assume the perspective of another person” (p. 2). They felt that social stories could be used to teach this skill and other deficits in the areas of social cognition. They postulated that social stories provide a child with autism with “accurate understanding of the situation” in which specific behaviors occur (p. 2). They continued, “social stories seek to minimize potentially confusing instructional interactions, to provide students with autism direct access to social information” (p. 2). They claimed that once the “accurate” information is presented the new skills can be practiced in the target situation if needed, but that minimal support should be provided.

What Makes a Social Story?

Initially social stories consisted of a combination of “descriptive”, “perspective”, and “directive” sentences with a ratio of one directive sentence for every two to five descriptive or perspective sentences (Gray & Garand, 1993; Gray, 2000). These recommendations have not yet been evaluated in any empirical study to date and there is no evidence to support the use of this ratio or any other. At least one researcher admits to varying both the ratio of sentence types as well as Gray’s general guidelines (i.e., to avoid statements such as “I always wash my hands after using the restroom”) (Crozier & Tincani, 2005).

Scattone, Wilczynski, Edwards, & Rabian (2002) provide a good description of basic sentence types: “descriptive sentences describe what people do in a given social situation, why they are doing it, when and where the event will take place, and who will be involved; perspective sentences describe the thoughts and feelings of other individuals; and directive sentences state the goals of the story by listing the responses the student is expected to provide during a given situation” (p. 536). Perspective sentences often describe the consequences for appropriate and inappropriate behaviors.

Recent publications have expanded the criteria for development of a “good” social story to include affirmative statements, typically opinion statements


such as “it’s always a good idea to…” that enhance the meaning of statements before and after them and also to include control and cooperative sentences. Control sentences are written by the subject and include reminders about when to use the strategies outlined in the social story (Gray, 1995). Cooperative sentences identify how others will provide help to the subject (Gray, 2000). It appears that these guidelines are based more upon Gray’s preferences than upon any empirical evidence that all sentence types should be present (Kuoch & Mirenda, 2003).

When choosing the right words for a social story, Gray and Garand (1993) suggest that authors should refrain from using statements such as “I will not talk in the library” and should instead write, “I can whisper in the library”. According to Gray, this difference may be crucial in teaching the child and may decrease possible side effects, such as a child not asking for help in the library because asking for help would be an example of talking.

Social stories may contain photographs of the target child engaging in some specified behavior, however in 1993, Gray and Garand recommended against using illustrations or pictures. According to the authors, illustrations may be a distraction or may actually lead to an inaccurate interpretation. They provide an example to demonstrate this point. A picture of a boy tying his shoe, sitting on blue carpet, next to a cat might indicate to the child that shoes should only be tied on blue carpet when cats are present. In 1995, Carol Gray revises this viewpoint and allows that photographs could be used in some stories if the overall situation consists of many parts, such as free time or center time in school were many options are available. At this point, none of these recommendations is based on any research. Research on Social Stories

Several reviews on the effectives of social stories and the relative value of the research conducted thus far. Refer to those reviews and a critical literature reviewed written by the author (Appendix G) for a more thorough appraisal of the social stories literature (Rust & Smith, 2006; Sansosti, 2008; Sansosti, Powell- Smith, & Kincaid, 2004). Research on the effectiveness of social stories can be broken into four basic categories: studies where social stories were the only programmed independent variable, studies in which prompts were combined with the social story, studies where consequences were combined with the social story, and studies where social stories were part of a package of interventions.

The following studies represent a sample of studies from each of these areas.In a study conducted by Scattone, Wilczynski, Edwards, and Rabian (2002), three students of varying ages participated. All were capable of communication using speech and all were in self-contained classrooms. The authors utilized a multiple baseline across subjects design to evaluate the impact of the social stories on the percentage of intervals in which staring, shouting, and chair tipping were observed by the experimenters. Two subjects read the story aloud to an adult and one subject had the story read to him


each day by an adult in the classroom. In addition, the stories were available for the students to look at or re-read throughout the day. A visual examination of the results showed that two of the three subjects decreased inappropriate behaviors during the social stories intervention condition. The third subject displayed such a low percentage of inappropriate behavior during baseline that minimal change was seen during the treatment, and initial decreases in inappropriate behavior were actually seen prior to implementation of the social story. In the discussion to this paper, the authors report that teachers were observed to provide prompts for behaviors related to the targets in the social stories. This additional variable, not controlled for in any way, completely invalidates the results of the study. This is a problem described by several authors. Treatment integrity was reportedly very high, although anecdotal reports appear to contradict this (e.g., one student was observed to be reading another student’s story, a second student read the story multiple times per day, a third student was incredibly resistant to the story and refused it on several occasions). While the classroom staff may have attempted to implement the intervention consistently, the authors actually report quite a bit of variability in terms of frequency of contact with the stories.

Adams, Gouvousis, VanLue, and Waldron (2004) utilized a reversal design to evaluate the effectiveness of a social story intervention to decrease crying, falling, screaming, and hitting in a seven-year-old male with autism. One story was written, following the social story formula, in which the subject was encouraged to engage in behaviors intended to alleviate the motivating variables responsible for the target behaviors. For example, the story instructed the subject to ask for help or a break. Baseline and intervention data overlap with great variability for all four conditions with no demonstrable change in the dependent variables. Data on acquisition of the “replacement” behaviors of asking for help and requesting breaks would have been beneficial to this study given the lack of response to intervention for the behaviors targeted for reduction.

Delano and Snell (2006) utilized a multiple baseline across subjects research design to evaluate the use of social stories to increase the duration of social engagement and frequency of four separate appropriate social responses for three children with autism. This study employed peer confederates for the intervention (one peer for initial intervention and a second peer for generalization). Prior to baseline the authors conducted brief preference and academic assessments. The reinforcer assessment was needed to identify preferred play activities for the intervention sessions. The academic assessments were conducted to evaluate the comprehension level of each subject to assist in development of the stories and to determine the most appropriate delivery method. The authors report that all stories adhered to the basic social story ratio suggested by Gray and Garand (1993).

Delano and Snell used a more innovative baseline method in which nonrelated stories were read to the subjects and confederates and a question and answer period followed in which comprehension questions were asked of


the subjects. This procedure set the stage for a similar practice during intervention. During both baseline and intervention, after story time, the subject and confederate were allowed to play for 10 minutes. During this time, data were collected on the duration of a variety of social behaviors. Additional probe data were collected in the time immediately prior to story time. In addition to the unusual baseline, the authors actually programmed fading criteria for limiting the frequency of story sessions and conducted generalization probes with lesser known peers.

Visual analysis of the data indicates that the intervention was effective for one subject, with increases in social engagement increasing from about 50 seconds in ten minutes to 450 seconds throughout the treatment condition, and maintaining at about 200 seconds across the fading and generalization conditions. Data for the other two subjects appear to be far more variable and therefore more difficult to interpret. One of the two remaining subjects demonstrated a steady increase in social engagement during the training condition, but fading and maintenance data are not as convincing as the first subject. Similar results are found with the third subject, with the exception that social engagement did not generalize to the novel peer. The steady increase in duration of social engagement is interesting and indicates that some other factor, such as increased reinforcement from the peer as a result of social engagement, may be influencing the target behavior. Additionally, the authors report that two of the three subjects (1 and 3) received additional discrete trial training on language and social skills.

Kuoch and Mirenda (2003) examined social stories without prompts for two subjects and compared social stories to prompts for a third subject. Subjects were between 3 and 6 years of age, representing some of the youngest subjects studied thus far. Three very different target behaviors were identified for each subject (i.e., aggression, spitting food out or other disruptive mealtime behaviors, and sharing/cheating), requiring three different social stories, one for each subject. For two subjects, an ABA design was used and for the third subject an ACABA design was used. The social story condition (B) consisted of the story being read by an adult sitting behind and to the side of the subject. No comprehension questions were asked. The target behavior was “corrected” by an adult if it occurred in the session time immediately following the social story. This correction procedure was in place during baseline. The prompts condition (C) was designed in a manner intended to rule out the effects of individual attention that naturally accompanies reading a social story. The authors designed this condition so that a fiction story was read to the subject and then a prompt was delivered related to the target behavior. For this subject, the experimenters incorporated a prompt regarding the target behavior at the end of the reading of the social story as well.

Story construction for the first two subjects generally adhered to the social story guidelines, but the third story was generally more complex than recommended by Gray and Garand (1993). Visual analysis of the data for the two ABA subjects indicates a lack of experimental control as neither subject


showed a reversal in responding rates when baseline was reintroduced. In addition, rates of the target behavior were already decreasing in the initial baseline for subject two before intervention began. Analysis of the data for subject three (ACABA) indicated that the prompts plus fiction story condition produced rates of responding similar to baselines one and two. Inappropriate behaviors reduced in the social story condition and remained low when the third baseline was introduced. Kuoch and Mirenda (2003 found that prompting alone was insufficient for behavior to change, however the prompts delivered were separated from the target behavior by time and space. The following section evaluates studies where reinforcement, another key variable in behavior analytic intervention, is added to the social stories protocol.

Crozier and Tincani (2007) examined the effectiveness of three different social story interventions for three preschool children with autism. Sitting appropriately during circle time, talking appropriately with peers during snack time, and increasing appropriate play (while decreasing inappropriate play) were addressed with three separate stories; one story (target behavior) per participant was evaluated. A simple reversal design (ABAB) was used for two participants and an ABCACBC design was used for the third. This design was chosen after the participant did not respond to the social story when presented alone. Visual analysis of the data for each participant indicates that the authors were able to show that social stories alone increased engagement in target behaviors for two participants, however shortcomings should be noted. First, for the participant whose story addressed sitting nicely in circle, a slight uptrend in the behavior was observed in the initial baseline. However, the behavior did increase dramatically and remained stable when the social story was implemented. However, the sitting behavior did not completely return to baseline levels during the reversal. In the case of the second participant who experienced a simple reversal design, increases in appropriate play (along with concurrent decreases in inappropriate play) were observed in the initial social story condition, however the behavior did not completely reverse and much higher rates of appropriate play weren’t seen until the second social story alone condition. These results challenge the hypothesis that social stories alone could have been completely responsible for the behavior change observed. The third participant experienced the ABCACBC design. For this subject, responding in the social story alone was almost identical to the initial baseline condition. The experimenters added prompts, delivering then to the participant on a variable interval schedule averaging about 2 prompts per minute. In a tenminute session approximately twenty prompts were delivered. Frequency of talking to peers increased to about five to six occurrences per session in this condition. A successful reversal followed, followed by a much more successful social story plus prompts condition (about 10 episodes of talking to peers per session were recorded). However this condition lasted only two sessions. The social story alone was attempted again, with baseline-like responding observed. A final social story plus prompts condition occurred, once again with only two sessions, with 4 and 8 episodes of the target behavior being recorded respectively. This study does include a maintenance phase, where the experimenters trained the classroom staff on the social story intervention and


turned the treatment over to the teachers. Data from two maintenance probes shows responding similar to the treatment condition for one of the three subjects. The other two subjects’ data were much closer to baseline levels during the maintenance probes. Observations and questions from the experimenters showed that only one of the three students frequently accessed his story during the maintenance phase. This subject was the one for whom the maintenance data showed high rates of the target behavior. This study adds to the social story literature by comparing social stories plus prompts to a condition without prompts. Further analysis is needed by the authors of this study to closely examine what it was about their subject that made the social story alone ineffective, when at least moderate results were seen for the other two subjects.

Kuttler, Smith Myles, and Carlson (1998) focused on decreasing precursors to tantrums in a single participant with autism. They used a reversal design in two different settings to evaluate the effects of the story on a variety of behaviors that had been observed to occur before tantrums. The authors report that tantrums were more likely to occur during transitions, when the subject had to wait, and during free time. While this is clearly not a comprehensive assessment, the authors did at least attempt to identify antecedent variables to the target behaviors. Two different social stories were written that addressed appropriate behaviors for different times of day (morning work and lunchtime). The stories differ from the traditional story in that they identify a specific reinforcer for appropriate behavior during the activities identified in the stories. The authors do not report the length of observation sessions, however the data indicate a functional relationship between the social story intervention and the decrease in precursor behaviors. In fact, graphs for both settings (lunch and work time) show an immediate decrease in inappropriate behaviors to zero or near zero levels. Expected changes in behavior across conditions were seen for both reversals. These data question to what extent behavior change could be attributed to the story or to the reinforcement. One final obvious limitation to this study- the use of only one subject- does present additional problems for external validity.

Barry and Burlew (2004) examined social stories as an intervention to increase play skills in two elementary students with autism. The authors measured the number of prompts required to get each student to engage in play skills and the duration of play time for each subject. A multiple baseline across subjects with three different treatment conditions design was used to evaluate the intervention (ABCD). In this study, social stories were not presented as a single intervention until the last phase. In Phases B and C varying levels of teacher intervention accompanied the social stories (prompts, practice, and praise). In Phase D, stories were available for the students to look at, and were read to the participants once each morning. Visual analysis of the data indicates that the intervention package was successful as the number of prompts required to start play decreased across conditions and duration of play increased across conditions. The obvious flaw in this study is less a design flaw than a problem in being able to determine the value of social stories in the intervention.


The objectives of the study were:(i) To determine the effect of social stories training on development of communication skills in children with autism.(ii) To compare the development of communication skills of children with autism who received social stories training with those who did not.

METHOD

Participants

The sample of children with autism was randomly drawn from 3 schools in Kafr EL Sheikh Governorate . The children within the age of 5-10 years, attended special classes. From the school records the authors identified 38 children with autism . A total number of 30 children were randomly selected from the 38, and assigned to treatment and control groups, so that both groups had 15 children each.

Design

The study followed the pretest-post-test control group design.

Instrumentation

The Scale for Communication Skills , a measurement instrument was specifically developed for the study to measure acquisition of receptive and expressive language skills.

The Scale for Communication Skills was sub-divided into three parts (1) General functioning skills (2) Receptive Language skills (3) Expressive Language skills.

(1) General Functioning skills: This section comprised of those behaviours that are critical for development of communication. Behaviours such as making eye contact, sitting in one place, responding to sound, own name and greetings, were included here.

(2) Receptive Language Skills: (a) Identification of objects of daily use (b) Following 2 wordinstructions and (c) Following simple sentences.

(3) Expressive Language Skills : This section too, was sub-divided into (a) Labeling or naming objects of daily use, (b) Describing actions when pictures are shown and (c) Pragmatic use through maintenance of eye contact and joint attention during communication, and expressing choice when more options are presented, taking turns in conversation and so on.

The Scale for Communication Skills used the following patterns to record responses:(1) General functioning skills were recorded as ‘yes/no’ denoting either the presence or absence of a behaviour.

(2) The receptive skills and expressive skills were measured on the scale of Correct Response


(CR), Response with Visual Cue (RVC), Verbal Response (VR), Non- Verbal Response (NVR) and No Response (NR). The scale employed the recording procedure appropriate to each segment. Hence, receptive skills were recorded as CR, RVC and NR, and within expressive skills some behaviours were recorded as VR, NVR and NR, some on CR, RVC and NR. The scoring followed a 3, 2, 1 pattern in which a CR or a VR was scored as 3, a RVC or NVR received a score of 2 and NR was scored as 1. The assessment of general functioning skills was done after observation of the subject in his/ her environment. The presence or absence of a functioning skill was scored as 1 and 0. The instrument was content validated and subsequently pilot tested on 6 children with autism, who were similar to the children of the study in age and socio-cultural background. The Scale for Communication Skills was used as pre and post-test for this study.

Procedure

Communication level of each child was measured on The Scale for Communication Skills. The assessment was done in an environment familiar to the children and during their usual intervention time. Treatment consisted of communication skills training using social stories . The pretest scores were analyzed to ensure parity among the children (t = 1.58, df = 28, p > 0.05).

Each child in the treatment group received 14 individual teaching sessions. The duration of each session would be from 20 minutes to 30 minutes, depending on each individual child’s capacity. Rewards and reinforcers were regularly used during the session for motivation. While treatment group children received communication training using social stories , the control group continued with usual special classroom interventions. At the completion of the treatment session, children from both groups were tested again on The Scale for Communication Skills.

Results

Social stories and development of communication skills

The first objective of the study was to determine the effect of social stories on the development of communication skills in children with autism. The treatment consisted of communication training through use of social stories . The children’s performance on communication skills was measured pre and post intervention. The composite mean score (60.40) attained by the children at the pre intervention phase was compared with that at post intervention (85.30). This difference was found to be statistically significant (t = 7.06, df = 14, p < 0.01). This indicates that use of social stories had a positive effect on development of communication skills in children with autism (Fig. 1).

Figure 1.


This effect was seen across the selected components (receptive and expressive aspects) of communication skills. The difference in mean scores on receptive language (Fig. 2) from pre (34.13) to post intervention (48.73) was significant statistically (t = 6.81, p<0.01).

Figure 2.

Similar positive changes were observed in acquisition of expressive language where a difference (10.33) between pre and post intervention mean scores was found to be significant (t = 4.68, p < 0.01) as seen in Figure 3.

Figure 3.

Since the age group of children ranged from 5 to 10 years, the data were further analyzed using ANOVA to determine if age as a variable had any effect on development of communication skills. The resultant F-ratio value (0.15) was not


significant. This indicates that social stories training benefited all children, and age as a concomitant variable had no significant effect on their post intervention performance.

Comparison of performance of treatment and control groups

The second objective of the study was to determine if use of social stories would be more effective for the treatment group compared to the control group . For this purpose, the post intervention scores of both treatment and control groups were analyzed. The data analysis showed that mean scores of the treatment group (85.30) was higher than that of the control group (61.33). This difference was found to be statistically significant (t = 8.08, df = 13, p < 0.01). This indicates that use of social stories had a positive effect on development of communication skills in children with autism in the treatment group . (Fig.4)

Figure 4.

050

100

1 2

Comparison of composite Mean Scores of Ex. and Con. groups at

Post Intervention

Experimentalgroup - post-intervention

control group postintervention

These findings indicate use of social stories to be as an effective intervention for development of communication skills in children with autism.

Discussion

Autism is frequently accompanied by additional developmental problems such as specific language impairment and/or intellectual impairment. Issues become complex when these additional problems are accompanied by communication difficulties specific to autism . Given the importance communication has as a prognostic indicator of future, social and educational development and later quality of life, it is imperative that intervention programmes for children with autism stress on alternative means of communication for those who have deficits in receptive and expressive language.

Conclusion


The purpose of the present study was to investigate the effect of social stories on communication skills of children with autism. The social story intervention is said to decrease a variety of undesirable behaviors exhibited by children diagnosed with autism (Gray & Garand, 1993; Kuttler, Myles, & Carlson, 1998; Norris & Dattilo, 1999; waggart et al., 1995). Social story intervention is a technique addressing the acquisition of new social skills and improving existing social behaviors (Gray & Garand, 1993; Swaggart et al., 1995). Studies conducted to measure the effectiveness of the social story intervention have targeted behaviors such as self-talking, singing, lack of or inappropriate greeting behaviors, and tantrum behaviors (Kuttler et al., 1998; Norris & Dattilo, 1999; Swaggart et al., 1995).

Evaluation of the results indicated that communication skills improved significantly after the implementation of the technique; social stories intervention . Significant differences between pre- post testing for experimental group , and at post testing between the control group and treatment group in favour of treatment group.

In conclusion, the social story intervention was successful in improving communication skills in the target children with autism .

References

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Baron-Cohen, S. (1996). Mindblindness: An essay on autism and theory of mind. MIT press, Cambridge, Massachusettes.

Barry, L. M., & Burlew, S. B. (2004). Using social stories to teach choice and play skills to children with autism. Focus on Autism & Other Developmental Disabilities, 19(1), 45-51.

Burke, R. V., Kuhn, B. R., & Peterson, J. L. (2004). Brief report: A "storybook" ending to children's bedtime problems--the use of a rewarding social story to reduce bedtime resistance and frequent night waking. Journal of Pediatric Psychology, 29(5), 389-396.

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Crozier, S. & Tincani, M. (2005). Using a modified social story to decrease disruptive behavior of a child with autism. Focus on Autism & Other Developmental Disabilities, 20(3), 150-157.

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Gray, C. (2000). The new social story book. Arlington, TX. Future Horizons, Inc.

Gray, C. A., & Garand, J. D. (1993). Social stories: Improving responses of students with autism with accurate social information. Focus on Autistic Behavior, 8(1), 1- 10.

Hadwin, J.A., Baron-Cohen, S., Howlin, P., & Hill, K. (1997). Does teaching theory of mind have an effect on the ability to develop conversation in children with autism? Journal of Autism and Developmental Disorders, 27, 519-537.

Ivey, M. L., Heflin, L. J., & Alberto, P. (2004). The use of social stories to promote independent behaviors in novel events for children with PDD-NOS. Focus on Autism & Other Developmental Disabilities, 19(3), 164-176.

Kuoch, H., & Mirenda, P. (2003). Social Story interventions for young children with autism spectrum disorders. Focus on Autism and Other Developmental Disabilities, 18, 219-227.

Kuttler, S., Smith Myles, B. S., & Carlson, J. K. (1998). The use of social stories to reduce precursors to tantrum behavior in a student with autism. Focus on Autism & Other Developmental Disabilities, 13(3), 176-182.

Norris, C., & Dattilo, J. (1999). Evaluating effects of a social story intervention on a young girl with autism. Focus on Autism & Other Developmental Disabilities, 14(3), 180-186.

Ozonoff, S. & Miller, J.N. (1995). Teaching theory of mind: A new approach to social skills training for individuals with autism. Journal of Autism and Developmental Disorders, 25, 415-433.

Pellicano, E. (2007). Links between theory of mind and executive function in young children: Clues to developmental primacy. Developmental Psychology, 43, 974- 990.

Rust, J., & Smith, A. (2006). How should the effectiveness of social stories to modify the behaviour of children on the autistic spectrum be tested? Lessons from the literature. Autism, 10(2), 125-138.

Sansosti, F.J. (2008). Teaching social behavior to children with autism spectrum disorders using social stories: Implications for school-based practice, The Journal of Speech-Language Pathology and Applied Behavior Analysis, 2.4-3.1, 36- 45.

Sansosti, F. J., & Powell-Smith, K. A. (2006). Using social stories to improve the social behavior of children with asperger syndrome. Journal of Positive Behavior Interventions, 8(1), 43-57.


Sansosti, F. J., Powell-Smith, K. A., & Kincaid, D. (2004). A research synthesis of social story interventions for children with autism spectrum disorders. Focus on Autism & Other Developmental Disabilities, 19(4), 194-204.

Scattone, D., Wilczynski, S. M., Edwards, R. P., & Rabian, B. (2002). Decreasing disruptive behaviors of children with autism using social stories. Journal of Autism & Developmental Disorders, 32(6), 535-543.

Swaggart, B., Gagnon, E., Bock, S. J., Earles, T. L., Quinn, C., Smith Myles, B., & Richard Simpson. (1995). Using social stories to teach social and behavioral skills to children with autism. Focus on Autistic Behavior, 10(1), 1-16.

Tager-Flusberg, H. (2001). A reexamination of the theory of mind hypothesis of autism. In J. Buwack, T. Charman, N. Yirmiya and P. Zelazo (Eds.), The development of autism: Perspectives from theory and research (pp. 173- 193). Mahwah, NJ, US: Lawrence Erlbaum and Associates Publisher.

Thiemann, K. S., & Goldstein, H. (2001). Social stories, written text cues, and video feedback: Effects on social communication of children with autism. Journal of Applied Behavior Analysis, 34(4), 425-446.

Yirmiya, N., Erel, O., Shaked, M., & Solomonica-Levi, D. (1998). Meta-analyses comparing theory of mind abilities of individuals with autism, individuals with mental retardation, and normally developing individuals. Psychological Bulletin, 124(3), 283-307.

Using Computerized Games As A Computer- Assisted Instruction


Format To Enhance Helping Behaviour In Kindergartners At- Risk For Learning Disabilities

Adel Abdulla Mohammed,PhD

Professor of Special Education, Faculty of Education, Zagazig UniversityZagazig, Egypt

Abstract

Computer- assisted instruction (CAI) has been recently provided in various formats from kindergartens on. It brings several potential benefits as a teaching / learning medium. Computerized games, as a CAI format, are in themselves a very important means of instruction for children in particular because of their unique characteristics. This study investigated the effectiveness of a computerized games program on enhancing the helping behavior in kindergartners at- risk for learning disabilities. Participants were fourteen 5- 6 year- old- kindergartners from Zagazig, Egypt. They were divided into two matched groups (experimental& control) with 7 participants each. Experimental method was used, and results indicated that use of computerized games enhanced helping behavior. It is concluded that those computerized games are practical tools to facilitate training and instruction to children at- risk for learning disabilities, and help them be school ready to learn .

Key words; computerized games, CAI; helping behavior; at- risk for LD;

kindergartners. Introduction

Most children with learning disabilities (LD) and their peers at- risk for LD often experience problems in the social arena. Such problems might impede communication and establishing social interactions with others (Hallahan& Kauffman, 2007). Computer and computerized materials in any computer- assisted instruction (CAI) format specially games might be beneficial in this respect because children like them most, and are always attracted to them, and captured by them (Gee, 2003). Therefore, using such a CAI format, and presenting computerized games to those children that might capture them, might be beneficial because it is likely that those games might enhance the development of communication, and reduce their social problems.

Rationale


computer has played an important role in children`s life, computer- assisted instruction (CAI) plays a similar role, too. It could be used to help them in all the academic fields. It has been recently used with those children with learning disabilities, and even with their peers who are at- risk for learning disabilities whether to help them in school or in daily life as a whole. Computerized games as a CAI format always have the great effect on those children. It can mainly be used to achieve school readiness in those children which in turn might help them start school ready to learn. Therefore, we are in dire need to formulate a goal like this in Egypt where there is not a sufficient number of kindergartens to determine children who are at- risk for LD, achieve behavior modification, and help them be school- ready to learn. Also, we need to determine the original indicators or criteria for those children to enter school in Egypt, and to establish a clear empirical base to indicate the merits of using computerized games as a CAI format in this respect from either a psychological, developmental, or educational perspective.

Purpose of The Study

The purpose of this study was to develop a computerized games program as a computer- assisted instruction format to be used with kindergartners at- risk for learning disabilities, and to examine the effectiveness of such a program on enhancing the helping behavior in those children. A secondary purpose of the study was to examine the continuing effectiveness of the program during the follow- up period.

Literature Review

Learning disabilities according to The National Joint Committee on Learning Disabilities (NJCLD) is, of course, a general term that refers to a heterogeneous group of disorders manifested by significant difficulties in the acquisition and use of listening, speaking, reading, writing, reasoning, or mathematical abilities. These disorders are intrinsic to the individual, presumed to be due to central nervous system dysfunction, and may occur across the life span. Problems in self- regulatory behaviors, social perception and social interaction may exist with learning disabilities but do not by themselves constitute a learning disability (Hallahan& Kauffman, 2007; Hallahan et al., 2005). When we are speaking about testing preschool children for learning disabilities, we are really talking about prediction rather than identification as those children are not ordinarily engaged in academics. Hence, the most accurate predictors are preacademic skills (Foorman et al., 1997; Lerner, 2000). These skills are behaviors that are basically needed before formal instruction can begin, such as identification of numbers, shapes, alphabets, and colors in addition to phonological awareness which is important for reading (Torgesen, 2001).

When we think of computerized games, we usually reel to images of exploding targets, flashy graphics, sometimes violent mayhem, pulsing


repetitive music and sound effects, in short, everything that makes preschoolers spend long hours losing themselves in an exciting, mesmerizing, pleasurable virtual world. Using such a game as an educational tool, however, is enough to make some educators think of using a computerized game, or even any game, as a learning tool.

Computer-assisted instruction (CAI) most often refers to instruction, whether remedial or not, presented on a computer, and allows drill-and-practice, tutorial, games, or simulation activities offered either by themselves or as supplements to traditional, teacher- directed instruction (Hallahan& Kauffman, 2007). CAI is an interactive instructional method that uses a computer to present material, and track learning. It also enhances the teaching process, usually by focusing on one particular learning task and aiming to improve it (Levy, 1997). Hence, computer programs are interactive and can illustrate a concept through attractive animation, sound, and demonstration allowing students to progress at their own pace and work individually, or problem solve in a group (Smaldino et al., 2004). Computers offer a different type of activity and a change of pace from teacher-led or group instruction (Fuchs et al., 2006).

Although CAI programs in games mode tend to be entertaining and challenging, gaming is too often seen by educators as a problem activity that unless tightly restricted, is ultimately distracting and even harmful to sound learning practices (Gee, 2003; 2004). In this respect two generalizations emerge from more recent research. First, it is the content of the game that is critical. Successful game programs, whether video games or other formats, have tapped into high levels of motivation and interest. As motivation dies, so learning dies and the extrinsic desire to continue stops (Gee, 2004). Consequently, where content is relevant, gaming should be encouraged as a means to reinforce a wide variety of learning values. Second, the methods and design of games have much to be considered by educators and curriculum developers (Gee, 2003). Good games allow multiple solutions to problems, differential rewards for different levels of play, and regular feedback about the player's progress (Hallahan et al., 2005; Seferian, 2000) because they often do a masterful job of presenting the basic elements in such a way that the player sees how the game works as a whole system, not as discrete, unrelated units. Basic skills are always practiced, not in isolation, but in sets that go together. In such a way they might form strategies to accomplish goals and carry out activities (Gee, 2003). Hence, CAI formats, especially games, might arouse cooperation and acceptable social behavior in those children, and might be of great importance to the skill deficiencies they often experience as they allow multiple representations of information, and challenge (Hallahan et al., 2005; Hallahan& Kauffman, 2007), they might arouse the development of social behavior in general, and helping behavior, in particular, which can be seen as some sort of cooperation between children. Therefore, the child may assist his peers in various situations, and the number of his social relations and interactions increased. According to literature (Fuchs et al., 2006; Hall et al., 2000; Hughes& Maccini, 1997; Seferian, 2000; Segers& Verhoeven, 2004), computer and computerized


instruction can help reduce the negative effect of being at- risk for learning disabilities, and promote the positive effect that might result in such a strategy as those children are basically attracted to computer, and to what is presented on it.

Campion (1995) saw that a computerized game is preferable by children to traditional education because it has been considered a "fun" activity. The only positive aspect these programs add is the use of the computer itself. With a computer, math problems can at least be displayed with large colorful numbers, and immediate feedback can result from each problem attempted. Thus games themselves have a real educational value as many games do indeed help to develop basic reading, writing and arithmetic skills. The games which do this in the most structured way, and are usually the most accepted in educational circles, often rely on the interpersonal dynamics of game play. In other words, the game itself is not really much fun to the student participants, but the interactions of the students during play is reinforcing. On the other hand, computerized games always provide stimulation necessary for learning, and using a computer in a game eliminates lengthy computations and board updating, and it allows a game with very complex rules to be started quickly and played by people who do not have to know the intricacies of the rules. They may have to learn the application of the rules to play the game well, but nobody actually has to know the administration of the rules (Campion, 1995 p.175)."

Since most computerized games often appear to become enjoyable, and capture learners` attention most of the time, better instruction can be introduced through them leading to better results as a review of research studies reveals that it has many benefits for children with learning disabilities as an effective medium for mathematics instruction (Hughes& Maccini, 1997), and prereading skills instruction (Hall et al., 2000). It might increase social acceptance to those children which in turn helps to increase the students' willingness to engage in social contact with other students, and enhance communication of non-native speakers of English involved in real time interaction (Peterson, 2008). Furthermore, computerized games, especially those dedicated for language, might in fact deal with specific language impairment (SLI) and could develop phonological awareness skills (Segers& Verhoeven, 2004). It could also lead to significant improvement in attention (Solan et al., 2003), and help children feel more competent to complete the required tasks after training ( Seferian, 2000), and enhance problem- solving, and self- management (Miller et al., 2007).

Hypotheses

The present study tries to answer four questions manipulated in the form of the following hypotheses :

1. There are statistically significant differences between mean ranks of experimental and control groups in the post- test of helping behavior favoring the first.


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2. There are statistically significant differences between mean ranks of pre- and post- test of helping behavior for experimental group favoring the post- test.

3. There are no statistically significant differences between mean ranks of pre- and post- test of helping behavior for control group.

4. There are no statistically significant differences between mean ranks of helping behavior in post- test and follow- up for experimental group.

Methodology

Participants

Participants were 14 male children at- risk for learning disabilities. All of them were from second year kindergarten (KG- II) bearing in mind that kindergarten is not included in the Egyptian hierarchy of education. They were from Zagazig city situated in Sharkiya Governorate, Egypt. They were ranging in chronological age from 5- 6 years with a mean age of 5.65 years, and SD of 1.31 years. They were divided into two equal groups ( experimental & control) with 7 participants each. Furthermore, they were matched in age, intelligence (average IQ), socio- economic and cultural status ( average level ) in addition to the helping behavior level as indicated by the pre- test results. Meanwhile, Neurological scanning results indicated that they were neurologically deficient. School teachers` reports, on the other hand, excluded any other impairment suffered by them. Table (1) below shows the results of such matching between both groups. A process of informed consent was used to make sure that parents of the participants know what would happen in the experiment and understand that they were allowed to quit the experiment at any time, and that no harm would be done to the participants.

>Table ( 1 ) …. Here <

Instruments

As well as the computerized games program as a CAI format, instruments used in the study were diagnostic and measuring in nature where an Arabic version of Stanford- Binet Intelligence Test- IV was used to select participants with an average IQ, and a socio- economic/ cultural status form was also used to select participants with an average level. Furthermore, a test battery for preacademic skills (Mohammed, 2005) was used to make sure that they were deficient in such arena, and according to the results of the Arabic version of Quick Neurological Screening Test such deficiencies were of a neurological basis.

A scale for helping behavior tasks was developed by the author where it was anticipated that participants would cooperate with each other, and help each other to some extent. It was anticipated also to evaluate such behavior if


that scale was used. Hence, six tasks were developed to constitute the whole scale with three questions each. There were 3 options before each of them ranging in scores from zero ( for not being able to help) to 2 ( always helps others). Therefore, each task has got from zero to 2 scores which in turn indicated that the scores dedicated for the scale as a whole ranged from zero to 12 . The higher the score a participant gets, the better. Tasks included in the scale dealt with real situations that always took place in school or in daily life in general i.e. (1) a student had too many books to carry, (2) during play a child was injured and wanted help to stand up and walk, (3) a child lost his pen and found that he had no money to buy a new one, (4) a student could not do his homework because of misunderstanding of the instructions, (5) some one needed money to get a sandwich to eat, and (6) a child felt ill and wanted some one help him go back to home. To ensure reliability of the scale it was readministered ( n = 25 participants other than those ones in the study final sample ) two weeks after the first administration of the test ( r = 0.793 > 0.01 ), and results of internal consistency indicated that ( r ) values for the item- task correlations ranged from 0.437 > 0.05 – 0.715 > 0.01 . To test the scale validity, a scale for children outdoor social relationships (Mohammed, 2004) was used as a criterion, and ( r= 0.708 > 0.01) . A computerized games program as a CAI format contained 60, 4 times a week sessions with a duration of 30 minutes each was developed by the author. Participants were trained by the author to play the group and social games presented. The program consisted of three main phases of which the first contained 6 sessions, and aimed to create familiarity between the author and participants in addition to qualifying them to receive instruction and training presented through games. It was anticipated that both parties i.e. author and participants would be familiar with the other, and participants would clearly understand what should be done. The second phase in which instruction and training were presented through 48 sessions was distributed to six group and social games that required cooperation of all the group members. Each game was presented through five sessions until participants mastered it, then they were trained to apply what they learned practically in two sessions, and participants were evaluated in the last session. Therefore, each game was presented in eight sessions. Modeling, manual guidance, repetition, and reinforcement were used. The six games included were :

(1)Math mission: It includes working with pattern blocks, counting change, weighing and measuring, and sorting. It helps children strengthen early mathematical thinking skills in an unusually fun environment.

(2)Clifford the Big Red Dog (Phonics): It is a phonics program that is intimidating or overwhelming. It contains solid free-play activities, as well as a likable theme that are this program's strengths. Although appropriate for any emergent reader, this game is especially useful for children who are reluctant to go further simply because it is pressure-free and encouraging. It is used with children aged 4-6.

(3)Alice In Vivaldi's Four Seasons: It is a creative arts game that aims to looking for something different, fun, and educational. It works children's brains in fantastic ways as they learn to distinguish sounds and musical


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instruments. Featuring musical puzzles and games based on Vivaldi's Four Seasons, this fresh software title allows children to play and learn about music and musical instruments in innovative ways. It is also used with children aged 6-up.

(4)Blue's Room (Blue Talks): It is a graphically-rich early learning software game. It has activities that offer preschoolers the chance to exercise their deductive reasoning skills in simple but effective ways. It is used with children aged 3-5.

(5)Star Flyers Alien Space Chase: It is especially entertaining and does require some thinking skills. It features plenty of arcade action that is never intimidating, some logic puzzles, and a fantastic story line. It is used with children aged 6-up.

(6)Adventure Workshop 5 (Preschool-1st Grade): It is a virtual playhouse for young children that is educational as well as fun. It is an excellent early logic program that is used with children aged 3- 6.

The final stage aimed to make quick revision on the content of the games included using the same format in 6 sessions with only one session for each game. To test the effectiveness of the program, it was implemented in a pilot study of 3 participants other than those of the study final sample, and results revealed that ( W= 0.00, and Z= - 1.631 > 0.05) which in turn indicated its effectiveness.

Research Method

Experimental method was used with the computerized games program as an independent variable, and the helping behavior as a dependent one. On the other hand, the experimental design of two groups (experimental& control) was used.

Results

Results of the study were summarized in the following table; >Table ( 2 ) …. Here <

The table shows the presence of statistically significant differences between experimental and control groups in post- test of helping behavior at 0.01 favoring the experimental group as values were all > 0.01. There were also similar statistically significant differences between pre- and post- test of helping behavior for the experimental group favoring the administration with the greater mean i.e. the post one as U, W,& Z values were all > 0.01. The results did not indicate the presence of any statistically significant differences between pre- and post- test of helping behavior for the control group as U, W,& Z values were < 0.05 . There were no statistically significant differences in helping behavior between post- test and follow- up for the experimental group as U, W,& Z values were all < 0.05 . Discussion


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To examine the 4 hypotheses, U, W,& Z values were calculated, and the results indicated the effectiveness of the computerized games program used. Such results might be interpreted in the light of the fact that CAI formats in general and computerized games in particular may in fact be of great importance to the skill deficiencies of the children with learning disabilities, or even their peers at- risk for such learning disabilities ( Hallahan et al., 2005; Hallahan& Kauffman, 2007). This of course may be attributed to several reasons that can be identified as follows; (1) CAI in its all formats including computerized games mode provides opportunities to individualize programs and to delineate specific skill deficits far more quickly and with more clarity than can a teacher whose time and resources may be limited, (2) it can also provide an immediate and ongoing feedback to the child on his / her performance, (3) the opportunities for practice can be far greater than can be provided through direct instruction from resource teachers who serve large numbers of children, and (4) most newer CAI formats provide in fact a large array of lessons which focus on specific skills (Fuchs et al., 2006; Gee, 2003, 2004; Hall et al., 2000; Smaldino et al., 2004). Such programs are always designed to ensure that computers do not create further barriers for the learners they are intended to assist, and that computer design and implementation address computers' potential for learners with disabilities in general and those with learning disabilities in particular (Hallahan et al., 2005; Smaldino et al., 2004).

In fact computerized games have undeniable educational values for many reasons i.e. (1) where the learning to take place is specific, (2) learning in such a case is measurable, and (3) it is capable of incorporation into a curriculum, tasks, or activities whether curricular or intracurricular activities. Using the techniques referred to in the present training program, the author could achieve many of those educational goals that participants were anticipated to achieve as most of them have socially behaved in a desirable way that they were previously intended to behave. Their social skills were enhanced as a result of such games which in turn affected their helping behavior in a positive and statistically significant way. Campion (1995) saw that there are games which incorporate some of the best educational designs. With few chances for failure, the player/learner is lead progressively from his or her current knowledge base to an expanded one. There are even some of these educational games which students will choose to play, not as the least of several evils, but for fun. Very few computer programs fall into this category. Hence we might say that games included in the present study fall into such a category which helped to attain the results revealed.

There are four principles of universal design for digital media that might assist to achieve the desired educational goals; (1) allow for multiple representations of information; (2) provide for multiple means of expression and control; (3) provide customizable support and challenge; and (4) allow customizable content (Gee, 2003; Smaldino et al., 2004). This of course is found in all computerized games included in the program used which in turn makes them enjoyable, and draw learners` attention most of the time. Such capture of attention could be carefully exploited, and by choosing good games


we could introduce better instruction to those children enabling ourselves to address all deficiencies those children might have, and achieving good results (Miller et al., 2007) as a review of research studies on computer- assisted instruction CAI reveals that it has many benefits for children with learning disabilities as an effective medium for instruction (Miller et al., 2007; Peterson, 2008; Seferian, 2000 ), and that the best-supported finding in the research literature is that the use of CAI, in its all formats, as a supplement to traditional, teacher-directed instruction produces positive effects superior to those obtained with traditional instruction alone (Hallahan& Kauffman, 2007).

Generally speaking, this finding holds true for students of different ages and abilities because a well- designed and well implemented computerized games format program used in this respect, might produce an educationally significant improvement in child's final performance (Gee, 2003). What helped to achieve such goals is that according to Campion (1995) in order for a child to choose to play a game, whether educational or not, it must be perceived as fun. So, games were carefully chosen, and children were effectively taught to perceive such games as fun, and to master them. As a result, participants played and interacted with one another, and experienced fun which helped to enhance their helping behavior.

Capper and Copple (1985) argued that CAI users sometimes learn as much as 40 percent faster than those receiving traditional, teacher-directed instruction. Also, student scores on delayed tests indicate that the retention of content learned using computer, games, or any CAI format is superior to retention following traditional instruction alone (Fuchs et al., 2006; Miller et al., 2007). Furthermore, the use of computerized games as a CAI format leads to more positive student attitudes toward education, content, quality of instruction, school in general, and self-as-learner than the use of conventional instruction (Smaldino et al., 2004) which might help them to be school ready to learn.

On the other hand, the variety of computerized games could enhance various abilities in those children. Thus they were also anticipated to be school ready. Elkind (2008) pointed that intellectual ability which is positively affected by such games was seen to reflect readiness before it was changed to be only cognitive readiness. The child must have a good memory and be able to learn, think, observe and communicate. He/ She must be able to understand instructions. The child must also show that he/ she wants to learn which is known as hunger for knowledge. Language development is also necessary for child in primary 1 as he/ she needs to be able to speak, to understand and to express himself/ herself. The child also needs to be emotionally ready, he/ she must be able to fit into the new environment and show consideration for others. He/ She must be able to control his/ her emotions.

Hence the experimental group children who received the computerized games program as a CAI format have become able to cooperate with one another, and help each other on a practical basis while their control peers


were still unable to do so. This observation explained the result that shows the presence of statistically significant differences between both groups in the first hypothesis favoring the experimental group, and the presence of similar differences between pre- and post- tests for the experimental group in the second hypothesis favoring the post- test. Meanwhile, no statistically significant differences were found between pre- and post- tests for the control group. Because such a group did not receive instruction as the experimental one, no change has occurred, and this fact indirectly supported the importance and effectiveness of the program used. Also, no statistically significant differences were found between post- test and follow- up for the experimental group children, and that result went back to what happened during the last phase of the program as the author could reteach them to perform the tasks determined which in turn led to transmission of training through such a period that lasted for two months without any drawbacks . Limitations

Although it is apparent that the issue of computerized games is one of critical importance especially for children at- risk for learning disabilities so as to help them to be school ready, it is one for which there is little substantive empirical knowledge especially in the Arabic environment to guide our present efforts. There is little agreement about the optimal design principles of such games, the skills that are critical for determining readiness, how such skills might be facilitated for readiness to occur, and how we might accurately assess the various dimensions involved. Also, participants involved in the study were not of a large number that can be accounted on because the great number mentioned to here requires other procedures and efforts, and therefore it needs a team of work to conduct.

Conclusions

Perhaps even beginning to consider kindergartens the first step in the educational hierarchy in Egypt is an impossible task nowadays, as it needs to generalize such kindergartens, and a public decision should be issued to do so. It also seems critical that kindergarten might enhance a range of knowledge and skills related to entering kindergartners' social interactions with their peers, i.e. ease in joining others in play, ability to make and keep friends, and positively interacting with peers. Here lies the helping behavior we should aim to enhance. Finally, it was concluded and recommended to use computerized instruction mainly through games with those children at- risk for LD to enhance their social, emotional, and preacademic skills. It could also be used to help those children to be school ready as those goals are closely related to school readiness, and as a result, children are anticipated to achieve progress later in school.

Reference


Campion, M. (1995). A historian and his games. Simulation and Gaming, 26, 168-178.

Capper, J.,& Copple, C. (1985). Computer use in education: Research review and instructional implications. Washington, DC: Center for Research into Practice .

Elkind, D. (2008). Some misunderstandings of school readiness. Exchange: The Early Childhood Leaders' Magazine Since 1978, 180, 49-52 .

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Table 1 . Results indicating the two groups are matched

Variables GroupMean rank

Sum of ranks

U* W Z Sig.

Chronological age

ExperimentalControl

7.437.57

52.0053.00

24.0 52.0 - 0.065 N. Sig.

Intelligence ExperimentalControl

7.297.71

51.0054.00

23.0 51.0 - 0.195 N. Sig.

Social levelS

ExperimentalControl

8.436.57

59.0046.00

18.0 46.0 - 0.846 N. Sig.

Economic level E

ExperimentalControl

7.797.21

54.5050.50

22.5 50.5 - 0.263 N. Sig.

Cultural level C

ExperimentalControl

8.296.71

58.0047.00

19.0 47.0 - 0.715 N. Sig.

Total SEC ExperimentalControl

8.296.71

58.0047.00

19.0 47.0 - 0.711 N. Sig.

Neurological scan

ExperimentalControl

7.797.21

54.5050.50

22.5 50.5 - 0.263 N. Sig.

Helping behavior

ExperimentalControl

7.437.57

52.0053.00

24.0 52.0 - 0.065 N. Sig.

* Letters included refer to non- parametric methods; (U) is Mann- Whitney value, (W) is Wilcoxon value, and (Z) is z value.

Table 2. U, W,& Z values for the differences between experimental and control groups in all measurements of helping behavior


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Measurement&Group Mean Mean

rankSum of ranks

U W Z Sig.

Post- test ExperimentalControl group

8.274.41

11.004.00

77.0028.00

0.00 28.00 - 3.134 0.01

ExperimentalGroup

Post- test Pre- test

8.274.53

11.004.00

77.0028.00

0.00 28.00 - 3.141 0.01

Control group Post- testPre- test

4.414.48

8.296.71

58.0047.00

19.00 47.00 - 0.543 N. Sig.

Experimentalgroup

Post- testFollow- Up

8.278.32

8.296.71

58.0047.00

19.00 47.00 - 0.541 N. Sig.

AUTHOR

Dr. Adel Abdulla Mohammed, Professor of Special Education, Faculty of Education, Zagazig University, Zagazig, Egypt. PO Box 532 Zagazig, Egypt. E- mail; [email protected]

The effects of learning- styles intervention on achievement in and attitudes towards Mathematics in elementary school students with learning disabilities


Mourad Ali Eissa , PhD

The Scandinavian University , [email protected]

Abstract

The main purpose of this study was to investigate the effects of a learning styles intervention on achievement in and attitude towards mathematics in elementary school students ( six graders ) with learning disabilities. Sixty – one students identified with LD were invited to participate. An experimental Pretest-Posttest Control-Group design was used in this study. The results show that students who studied mathematics with prescriptions based on their learning-style preferences achieved statistically higher achievement and attitude test scores than their counterparts in an equivalent group who studied with prescriptions based on conventional study methods.

Keywords. learning- styles intervention, achievement , attitudes, learning disabilities

Introduction

During the past decades ,educators became increasingly aware that individual learners approach academic tasks with different learning styles .According to Hughes ( 1985) " we have come to recognize that varying styles can mean that some students , teachers and administrators will be far more successful than others with particular tasks , situations an people ." This was supported by Volk ( 1987) who wrote that learning styles do affect the achievement of students .He concluded by stating that the effect is real , and to ignore it by neglecting learning styles hinders educational improvement. Additionally, Falzano (2003), Mourad Ali ( 2006) strongly suggested that learning styles become an integral part of instruction to help middle-school teachers meet higher standards.

Dunn et al ( 1981, P. 226) insists that " As we learn more about the scope and complexity of individual differences and how they affect academic progress , we become increasingly convinced that many individuals who do not read well do not because the instructional method used to teach them does not complement their learning styles characteristics."


A meta-analysis of 42 experimental studies conducted with this model between 1980- 1990 at 13 different universities revealed that eight variables coded for each study produced 65 individual effect sizes (Dunn et al., 1995). The overall, unweighted group effect size value (r) was .384 and the weighted effect size value was .353 with a mean difference (d) of .755. Referring to the standard normal curve, this suggests that students whose learning styles are accommodated would be expected to achieve 75% of a standard deviation higher than students who have not had their learning styles accommodated. This indicated that matching students' learning style preferences with educational interventions compatible with those preferences was beneficial to their academic achievement, attitudes (Fathi Abdul Hamid &Mourad Ali, 2006) .

Accordingly, this recent study is to investigate the effect of learning style – interventions on middle school students' achievement in and attitudes towards Mathematics. Literature review

The Dunn and Dunn Learning Style Model

Of the three comprehensive learning-style models available (Dunn & Dunn, 1972; Hill, 1971; Keefe, 1991), only the Dunn and Dunn Model provides instrumentation for identifying and specific approaches for teaching middle-school students. It is one of the most reliable and valid models (Curry, 1987; DeBello, 1990). Because it is comprehensive, it identifies a wide range of learning-style preferences including 21 environmental, emotional, sociological, physical, and psychological elements. Therefore, it was chosen for this investigation.

A meta-analysis of 42 experimental studies conducted with this model between 1980- 1990 at 13 different universities revealed that eight variables coded for each study produced 65 individual effect sizes (Dunn et al., 1995). The overall, unweighted group effect size value (r) was .384 and the weighted effect size value was .353 with a mean difference (d) of .755. Referring to the standard normal curve, this suggests that students whose learning styles are accommodated would be expected to achieve 75% of a standard deviation higher than students who have not had their learning styles accommodated. This indicated that matching students’ learning style preferences with educational interventions compatible with those preferences was beneficial to their academic achievement.

Achievement and learning styles

A number of studies have demonstrated that when students’ learning styles were congruent to the instruction they received, they achieved significantly higher test scores than students who were not matched . Dunn et al.( 1995) analyzed the effects of matching and mismatching students’ learning style perceptual preferences with auditory, visual, and tactual instructional


resources on the science achievement of 30 seventh-graders who had been classified according to their perceptual preferences as determined by the Learning Style Inventory (Dunn, Dunn, & Price, 1989). Students "were randomly assigned to two groups based upon their perceptual preferences" (Martini, 1986 , 76). No control group was used. She utilized three instructional strategies; cassette, computer, and printed materials. Pre-tests and post-tests were used to assess achievement. This study revealed that auditory, visual, and tactual learners achieved significantly higher gains when instruction matched, rather than mismatched, their perceptual preferences. Crampton (1990) revealed that students who were referred for discipline because of behavior exhibited a significant difference in visual preferences from students who were not referred for these behaviors. Referred students preferred auditory, tactual and/or kinesthetic learning to visual learning.

Nations-Miller (1993) analyzed at-risk, gifted, and vocational students for similarities and differences in learning style preferences among the groups. At-risk students disliked learning tactually, visually, or auditorially,while vocational students could learn auditorially, tactually, and kinesthetically. The gifted students werekinesthetic, disliked visual and tactual learning, but could learn auditorially.

Researchers including Martini (1986), Crampton (1990), Nations-Miller (1993), and Peshkin & Tauber-Scheidlinger (1976) have all concluded that when instruction is matched to student learning styles, the students achieve significantly higher than when instruction is not matched to the students’ learning style.

Learning Style Dunn and Dunn (1993) maintain that learning style refers to each person’s: (a) immediate environmental preferences (sound, temperature, light, and seating design); (b) emotionality (motivation, persistence, responsibility (conformity/non-conformity), need for structure) when concentrating on, processing, and retaining new and difficult information; (c) sociological preferences (learning alone, with a partner, in small groups, or with an adult, or in a variety of groupings); (d) physiological characteristics (perceptual strengths, time-of-day energy levels,and need for intake and/or mobility); and (e) psychological processing (global/analytic). The Dunn, Dunn, and Price Learning Style Inventory (LSI)(1989) provides scores in all of the elements. Learning style is defined in this study as students who utilize perceptual preferences — auditory, visual, kinesthetic, and tactual.

Mourad Ali (2005) investigated the effect of teaching eighth- graders through their preferred learning styles on improving their reading comprehension . students' preferred learning styles was determined by the Learning Style Inventory (Dunn, Dunn, & Price, 2004). Pre-tests , post-tests and sequential tests were used to assess gains .This study revealed that there were great gains for the experimental group in their cognitive and metacognitive reading comprehension .


Attitudes A meta analysis of experimental research based on the Dunn and Dunn Learning- Style Model identified 32 studies that had assessed attitudes – towards – learning as an outcome variable ( Lovelace , 2005). More recent studies (Fathi, Abdel hamid & Mourad Ali, 2006; Fadlon. , 2007) demonstrated increase in positive attitudes towards learning when implementing learning style - based intervention .

METHOD

Participants

Sixty – one students identified with LD were invited to participate. Each student participant met the following established criteria to be included in the study: (a) a diagnosis of LD by teacher's references, and learning disabilities screening test (Kamel, 1990) (b) an IQ score on the Mental Abilities Test (Mosa, 1989) between 90 and 114 (c) low scores on Mathematical achievement and attitude tests (d) absence of any other disabling condition. The sample was randomly divided into two groups; experimental (n= 31; 28 boys and 3 girls) and control (n= 28, 20 boys, 2 girls).

The two groups were matched on age , IQ , achievement and attitude tests . Table 1. shows means, standard deviations ,t- value , and significance level for experimental and control groups on age ( by month) , IQ , achievement and attitude tests ( pre-test)

Table 1. Pretest Scores Means , standard deviations ,t- value , and significance level for experimental and control groups on age ( by month) , IQ , achievement and attitude tests.

Variable Group N M SD T Sig.

Age Experimental

Control

31

30

145.51

145.23

2.42

2.45

0.453 -

IQ Experimental

Control

31

30

109.19

109.80

7.44

8.05

-.305 -

Achievement Experimental

Control

31

30

12.129

12.100

1.14

1.18

0.097 -

Attitude Experimental

Control

31

30

20.61

21.50

0.91

1.90

-2.32 -


Table 1. shows that al t- values did not reach significance level . This indicated that the two groups did not differ in age , IQ , achievement and attitude tests ( pre-test) .

Procedures

All 24 students in the experimental group were administered the Arabic version of the Learning Style Inventory (LSI)( Mourad Ali, 2008). Before they were administered the LSI, the Arabic version of "Mission From No Style" ( Mourad Ali , 2006)was read to each of the students to help them understand the concept of learning styles. All students were given the achievement and attitudes pre-tests during the first week of instruction and learning style instruction began that same week.

During the first week of October, students in the experimental group received their LSI computer printouts. They were given an explanation of their LSI printouts and were told which learning- style preferences were important to their learning.

Students in the experimental groups received their individual Learning Style Profile and a chart was mounted in their classroom indicating their learning styles. Each student was told their preferred learning styles and guided toward the appropriate instructional resource.

Each student in the experimental group was given his/her instructional resources to accommodate his or her preferred learning style. There were separate prescriptions for each preference. Learning style strategies were taught prior to the six- week instructional period. The researcher modeled the use of the resources and engaged the students in the activities for the experimental group. Students in the control group were taught using traditional methods; that is ,they did not receive such an intervention. At the end of the two months, the measures ( post- tests) were administered again.

Experimental Design

An experimental Pretest-Posttest Control-Group design was used in this study. In this mixed design, two groups are formed by assigning 24 of the participants to the experimental group and 23 to the control group. Both groups were pretested and posttested in the same manner and at the same time in the study. The bivalent independent variable was the learning- styles intervention and it assumed two values: presence versus absence of the learning- styles intervention. The dependent variables were the gains in scores on achievement in , and attitude towards Mathematics tests.


Results

Mathematics Achievement

Table 2. shows data on ANCOVA analysis for the differences in post- test mean scores between experimental and control groups in Mathematics Achievement. The table shows that the (F) value was (416.92 ) and it was significant value at the level (0.01).

Table 2. ANCOVA analysis for the differences in post- test mean scores between experimental and control groups in Mathematics Achievement

Source Type 111

sum of squares

df Mean

square

F Sig.

Pre

Group

Error

Total

3.894

6327.64

880.277208.85

1

1

58

60

3.894

6327.64

880.27

416.92 0.01

Table 3. shows T. test results for the differences in post- test mean scores between experimental and control groups in Mathematics Achievement. The table shows that (t) vale was (20.54). This value is significant at the level (0.01) in the favor of experimental group. The table also shows that there are differences in post- test mean scores between experimental and control groups in Mathematics Achievement in the favor of experimental group.

Table 3. T. test results for the differences in post- test mean scores between experimental and control groups in Mathematics Achievement

Group N Mean Std. deviation T Sig.

Experimental

Control

31

30

35.97

15.59

2.58

4.85

20.54

0.01

Attitude Toward Mathematics

Table 4. shows data on ANCOVA analysis for the differences in post- test mean scores between experimental and control groups in Attitude Toward Mathematics . The table shows that the (F) value was (244.722) and it was significant value at the level (0.01).


Table 4. ANCOVA analysis for the differences in post- test mean scores between experimental and control groups in Attitude Toward Mathematics

Source Type 111

sum of squares

df Mean

square

F Sig.

Pre

Group

Error

Total

.128

5538.336

1312.607

7375.73

1

1

58

60

.128

5538.336

22.631

244.722 0.01

Table 5. shows T. test results for the differences in post- test mean scores between experimental and control groups in Attitude Toward Mathematics. The table shows that (t) vale was (16.75 ). This value is significant at the level (0.01) in the favor of experimental group. The table also shows that there are differences in post- test mean scores between experimental and control groups in Attitude Toward Mathematics in the favor of experimental group.

Table 3. T. test results for the differences in post- test mean scores between experimental and control groups in Attitude Toward Mathematics

Group N Mean Std. deviation T Sig.

Experimental

Control

31

30

41.74

21.80

6.46

1.42

16.75 0.01

Discussion

The main objective of the present study was to explore whether there were differences in post – test scores mean between control and experimental groups on Mathematics achievement and in attitude toward Mathematics .

The results of this study as revealed in tables 3 , 5 show that students who studied mathematics with prescriptions based on their learning-style preferences achieved statistically higher achievement and attitude test scores than their counterparts in an equivalent group who studied with prescriptions based on conventional study methods.

The data from this investigation corroborated those of previous studies in which students followed procedures for studying that complemented their individual strengths(Cook,1989;Lenehan et al.,1994; Nelson et al.,1993; Ogden,1989; Turner,1993,Fathi&Mourad,2006).The difference herein was that students demonstrated that they, too, could assume responsibility for their learning by focusing on their unique learning-style strengths rather than on traditional study practices.


References Cook, L. (1989). Relationships among learning style awareness, academic achievement,and locus of control among community college students. (Doctoral dissertation, University of Florida, 1989). Dissertation Abstracts International, 49(03), 217A.Crampton, N. A. S. (1990). Learning style (modality preferences) for students attending private residential alternative schools (at risk). (Doctoral dissertation, University of South Dakota, 1990). Dissertation Abstracts International, 52/02A, 407Curry, L. (1987). Integrating concepts of cognitive or learning style: A review with attention to psychometric standards. Ottawa, Ontario, Canada: Canadian College of Health Service Executives. DeBello, T.C. (1990).Comparison of eleven major learning styles models: variables, appropriate populations ,validity of instrumentation and the research behind them. Journal or Reading, Writing, and Learning Disabilities, 6: 203-222. Dunn, K., & Dunn, R. (1993). Teaching secondary students through their individual learning styles: Practical approaches for grades 7-12. Boston, MA: Allyn & Bacon.Dunn, R., Price ,G & Sanders, W. (1981). Reading achievement and learning style characteristics. The Clearing House, 54, 223-226Dunn R., Dunn, K., & Price, G. E. (1989). style inventory. Lawrence, KS: Price Systems.Dunn, R., Griggs, S. A., Olson, J., Gorman, B., & Beasley, M. (1995). A meta- analytic validation of the Dunn and Dunn model of learning-style preferences. Journal of Educational Research, 88, 353-361.Fadlon,S. ( 2007) The effect of a program based on the Dunns learning styles model on improving reading skills of reading disabled student . Journal of Education and Psychology , Kafr EL Sheik University , Vol.39(2), pp.312- 343Falzano, C. (2003).Effects of traditional instruction versus teacher- constructed and student-constructed tactual and kinesthetic resources on the short-and long-term vocabulary achievement and attitudes and behaviors of sixth-grade students (Doctoral dissertation, St. John's University).Fathi Abdul Hamid &Mourad Ali (2006). The effectiveness of a learning – styles intervention on improving achievement in mathematics attitudes , and disruptive behaviour of learning disabled students. Journal of Education and Psychology , Tanta University , Vol.35(2), pp.197-223.Hill, J. E. (1981).The educational sciences: A conceptual framework. West Bloomfield Hills, MI: Hill Educational Sciences Foundation.Hughes ,C.( 1985).Foreword , Marching to different drummers, Alexandria : ( ASCD) Association for supervision and Curriculum Development.

Kamel ,M. ( 1990). Student behaviour rating Scale.Al Anglo Al Masrya .


Keefe, J. W. (1991). Learning style: Cognitive and thinking skills. Reston, VA: National Association of Secondary School Principals.Lenehan, M.C., Dunn, R., Ingham, J., Murray, W., & Signer, B. (1994). Learning style: Necessary know-how for academic success in college. Journal of College Student Development, 35, 461-466.Lovelace, M. K. (2005). Meta-analysis of experimental research based on the Dunn and Dunn model. The Journal of Education Research, 98(3), 176- 183. Martini, M. (1986). An analysis of the relationships between and among computer-assisted instruction, learning style, perceptual preferences, attitudes, and the science achievement of 7th grade students in a suburban N.Y. school district. (Doctoral dissertation, St. John’s University, 1986). Dissertation Abstracts International, 47, 877-03AMosa, F.( 1989). Mental abilities test.Al Nahda Al Masrya .Mourad , Ali .E. ( 2005). Effects of learning styles preferences intervention on improving reading comprehension of middle school poor readers students . Journal of Education and Psychology , Tanta University , Vol.34(2), pp.213-233Mourad , Ali .E. ( 2006) . Poor reading and learning styles. Alexandria , Dar Al Wafaa. Mourad , Ali .E. ( 2008) . The Arabic version of the Learning Style Inventory (LSI), Alexandria , Dar Al Wafaa.Nations-Miller, B. L. R. (1993). A profile analysis of the learning styles of tenth- through twelfth grade, at-risk vocational and gifted students in a suburban Georgia public school. (Doctoral dissertation,Georgia State University, 1993). Dissertation Abstracts International, 53(8), 2784Nelson, B., Dunn, R., Griggs, S.A., Primavera, L., Fitzpatrick, M., Bacilious, Z., & Miller, R. (1993). Effects of learning style interventions on students’ retention and achievement. Journal of College Student Development, 34(5), 364-369.Ogden, D. (1989). Student application of learning styles and modality preferences as shown in achievement and attitude. (Doctoral dissertation, Northern Arizona University). Dissertation Abstracts International, 51-05A, 1496.Peshkin, A., Tauber-Scheidlinger, A. & R. (1976). Let them learn their way . Academic Therapy, 11(3), 301-311Volk, K.H. ( 1987).Celebrating students diversity through learning styles. OSSC Bulletin ( ED 284 321)


ABOUT THE JOURNAL

The Scandinavian Journal for Human and Applied Sciences was founded in 2009 and is published jointly by THE SCANDINAVIAN UNIVERSITY . Three issues are published annually , in January , April , and July .

We accept manuscripts of original , primary research ( theoretical and empirical papers ) as well as practical applications (reflections, professional experiences , technological innovations , teaching materials, assessment and intervention materials). The selection and review process follows international standards of equality , anonymity and quality . Referees are reputed within their academic or professional setting , and come from many countries around the world.

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The main objectives of the Journal are :

- To initiate , conduct , and support research in all fields of knowledge ;- To assemble all who are interested in these fields for an exchange of

ideas and experiences ;- To disseminate research findings ;- To provide a database for members and researchers .

COLLABOTARORS

Dr Fares, M( Algeria)

Dr. Salah, M( Jordan)

Dr. Gamil , Sh. ( Syria)

Dr. Addullwahab, S. (Algeria)

Dr. Mohammed, Kh.( Syria)

Dr.AbdullAziz, H.( Algeria)

Dr. Fathi Abdullhamid, A. ( Egypt)

Dr. Nabil , K. ( Syria)

Dr Nabil , M. ( Jordan)

Dr . Helal , D. ( Lebanon )

Dr. Raquel Fidalgo ( Spain)


Dr. Sally M. Reis( USA)

Dr. Paul Bell ( USA)

Dr. Seth Parsons(USA)

Dr Svjetlana Kolić-Vehovec(Croatia)

Dr Anneke Vrugt (The Netherlands)

Dr. Stella Vázquez (Argentine)

Dr. DESOETE, Annemie(Belgium)

Dr. Kerim GUNDOGDU( Turkey)

ADVISORY BOARD

Dr Deeb , L. ( Norway)

Dr. Adel Abdullah, M.( Egypt)

Dr Morhaf,A.( Syria )

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ADVERTISING WITH THE SJHAS

Editing Board of The SJHAS opens a door for advertising with the Journal starting from the third issue , which will be published " In Sh'a Allah " in July 2010 , according to the following:

1. The material advertised should be that of knowledge (e.g. books, journals, conferences , websites , school materials, charities , institutes ….etc).

2. The advertisement should not include any immoral picture, photo , or word .

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Editor –in – chief

Prof. Dr . Samer Kantakji ( Scandinavian University Chairman)

Editor .

Dr . Mohamed Babaammi ( Scandinavian University)

Assistant Editor .

Dr. Mourad Ali Eissa ( Scandinavian University)


the scandinavian journal for humanandapplied sciences

Documents

autism adel abdulla

introduction autism

keywords music therapy

effectiveness of music

social behaviors

social play hallahan

college students pp

learning disabilities