Impact of Scratch Programming on Students Understanding of Their Own Learning Process

Download Impact of Scratch Programming on Students Understanding of Their Own Learning Process

Post on 27-Dec-2016

213 views

Category:

Documents

1 download

TRANSCRIPT

  • Procedia - Social and Behavioral Sciences 46 ( 2012 ) 1219 1223

    1877-0428 2012 Published by Elsevier Ltd. Selection and/or peer review under responsibility of Prof. Dr. Hseyin Uzunboylu doi: 10.1016/j.sbspro.2012.05.278

    WCES 2012

    Impact of Scratch programming on students understanding of their own learning process

    Teresa Ferrer-Mico a *, Miquel ngel Prats-Fernndez b, Albert Redo-Sanchez c a,b Department of Education, FPCEE Blanquerna-Universitat Ramn Llull, Cster 34, Barcelona 08022, Spain

    c Physics Department, Rensselaer Polytechnic Institute, 110 8th Street, Troy 12180, USA

    Abstract

    This research study analyses the students competence of self- directed learning introducing in the mathematics curriculum an activity related with computer programming using Scratch. We worked with two groups of pupils; one group is in an earlier stage of Scratch use, while the other one is more advanced. The methodology used is an explanatory mixed method research approach where quantitative and qualitative data complement each other. We used a semantic differential scale questionnaire, (Self Directed Learning with Scratch Scale) adapted from Teo et al. (2010) to test students self-directed learning management and intentionality, and focus groups to retrieve qualitative data. There is a secondary academic goal for this investigation: correctly define and compare self-regulated and self-directed learning concepts adding insights on current literature issues. 2012 Published by Elsevier Ltd.

    Keywords: Interactive Learning Environment, programming, secondary education;

    1. Introduction

    With this paper we would like to clarify some misunderstandings related with the concepts of self-regulated learning and self-directed learning. We also would like to introduce the qualitative findings of the research performed with young users of an Interactive Learning Environment named Scratch and its impact on the self-directed learning capability. A second article will add quantitative data to the study.

    2. Self-directed and self-regulated concepts: synonyms or complements

    Historically, students own learning process may refer to two different conceptual approaches, sometimes used as synonyms in the literature: self-directed and self-regulated learning (Rauner & Maclean, 2008). The first goal of this present study is to clarify both concepts and to justify the one that we have chosen to use in our study: self-directed learning.

    The concept of self-regulated learning has been evolving since the first proposed model (Zimmerman, 1989; Winne, 1997), when it was thought as an individual and cyclical-constructive activity aimed to construct knowledge within a social context. Since then, new studies are suggesting that the context is the most important part of the

    * Teresa Ferrer-Mico. Tel.: +0-518-418-6889 E-mail address: teresafm1@blanquerna.url.edu

    Available online at www.sciencedirect.com

    2012 Published by Elsevier Ltd. Selection and/or peer review under responsibility of Prof. Dr. Hseyin Uzunboylu

  • 1220 Teresa Ferrer-Mico et al. / Procedia - Social and Behavioral Sciences 46 ( 2012 ) 1219 1223

    and because new online contexts are appearing, the model is also evolving and starting to measure self-regulation within a real online context (Zimmerman, 2008; Hadwin, Oshinge, Cress & Winne, 2008). Although broad research has been done in the field, there are still some gaps that should be covered, for example assessment and its authentic measurement of the learning processes (Schunk, 2008; Zimmerman, 1990).

    On the other hand, the concept of self-learning (Hartley & Bendixen, 2001) and presents different perspectives and models related with different authors (Song & Hill, 2007). Can -directed learning: personal autonomy, self-management, learner control and autodidaxy, while Brockett aself- different variables like self-management, self-monitoring and motivation. The most recent investigations are developing new models for self-directed learning relating them with online learning contexts (Song & Hill, 2007).

    Once we have revised both concepts, and although sometimes are used as synonyms, we understand that a self-directed learner needs to be self-regulated, therefore self-regulation is an important skill for a self-directed type of

    -directed concept, because we understand that is more general, inclusive with some other competences, and it adds extra value to the study of new learning environments.

    3. Methodology

    Our main objective of this paper is to add qualitative data to previous and more descriptive researches performed within the same field. Choi and Clark (2006), did not find statistical differences in their study when relating multimedia environments with learning outcomes, suggesting the analysis of more empirical and qualitative data for future researches. Following this idea, we would like to assess how one of these uses of technology (Scratch

    -directed learning. The reader could find more information about Scratch revising the following papers (Ferrer- Monroy-

    3.1. Participants

    The target population was limited to first grade students of compulsory secondary education (12-13 years old) from a British School in Barcelona, Spain. Within this sample, we chose two groups that were involved in the study (beginners N=19 and advanced, N=22). These two groups started as equivalent as possible, to avoid new variables not controlled by the research. Participants own characteristics, past experiences and initial capabilities were as similar as possible.

    3.2. Instruments

    We collected information from differ

    (Marzano & Kendal, 2008). We used a matrix to assess the level of consensus between mini-focus groups, two or three students per mini-group as suggested by Onwuegbuzie, Leech and Collins (2010). This type of analysis guarantees that each individual viewpoint will have an impact on the final result. Just using a one-focus-group

    single p , 1993). By using a matrix we minimize bias and the researcher interpretations as much as possible (Cohen, Manion & Morrison, 2000)

    3.3. Procedure

    Both groups of students have 5 hours per week of mathematics, once a day. The groups (advanced and beginners) had 4 hours a week of standard mathematics classes and 1 hour per week of Scratch Computing. The teaching

    -c R. Liu, Qiao & Y. Liu, 2006), and it took place during the spring semester of 2011.

  • 1221 Teresa Ferrer-Mico et al. / Procedia - Social and Behavioral Sciences 46 ( 2012 ) 1219 1223

    3.4. Data description

    Below we present a brief and descriptive analysis of three sessions using data from and informal conversations.

    On the other hand, we present the analysis of the level of consensus within the focus groups using a matrix adapted from Onwuegbuzie et alt. results obtained in the quantitative part of this study, which will be presented in another paper. Although when using focus groups we may have the issue that the outcomes are unique to that particular group, we could also have interesting findings because the participants are really focused on the present subject (Cohen, Manion & Morrison, 2000), therefore we believe that the use of focus groups is appropriate for our main purpose.

    4. Results

    4.1. Computing with Scratch

    During the starting lessons the students annotated in their journals questions and situations that were surprising, but not what they could do to change them. For example, these are comments from some students, (where a sprite is a computer graphic that can be programmed and manipulated):

    turn180 degrees block

    stume of this sprite so many times that I learned how to do it

    Some other comments were just complains about the difficulty of using come blocks:

    These type of comments show that the students were just focusing on how to use this new tool and not confident enough to use it to create new situations and knowledge. We found a different situation in the following sessions.

    During the sharing sessions the students shared their projects with the rest of the classmates and asked them for advice. It was interesting to notice that some students had very good ideas to share, for example:

    quickly and is difficult to follow, you could use less steps in the

    Other suggestions related with backgrounds and music or sounds were also very popular.

    During the last sessions where students were programming their own video games, the students visited and revised other videogames made using Scratch to use ideas form them, this is, to get inspired. The programming style started to get a little bit more sophisticated by adding variables and loops. One student pointed out that:

    programming using blocks and loops and understanding the whole program. I have

    In this sense, it is clear to us that the students change their sense of understanding, as they are exposed to the activity during a longer period of time. They are able to start relating the actions that they are programming with the behaviour of the creatures in the screen. Trying to answer to an emerging goal of the research, we would like to comment that although it is unclear if students learn differently when using computers, the mental process of being aware of their learning process is more explicit with this use of an interactive learning have explicit data that supports that this understanding is better than without computers, at least we can assure that the interactivity makes it more clear and remarkable for the students in this research study. This affirmation will be complemented by the quantitative data of the following paper.

  • 1222 Teresa Ferrer-Mico et al. / Procedia - Social and Behavioral Sciences 46 ( 2012 ) 1219 1223

    4.2. Level of consensus

    The data obtained from the focus groups interviews is displayed below as a matrix adapted from Onwuegbuzie et alt. (2010). We evaluated the agreement frequency, this is, the general consensus within the group. The matrix shows the five questions (paraphrased), proposed to each of the sub-groups, and the frequency findings, (Table 1).

    Table 1. Consensus Matrix

    Frequencies %

    Question 1

    Usefulness of feedback

    suggestions

    Question 2

    More time-better

    understanding

    Question 3

    Usefulness of presenting

    Question 4

    Enjoying the experience

    Question 5

    Be able to teach

    Agreement 46 82 32 45.5 32 Suggested agreement 36 9 50 18 18

    Disagreement Suggested disagreement

    No Response

    0 18 0

    4.5 4.5 0

    0 9 9

    23 9

    4.5

    36 14 0

    Where suggested agreement and suggested disagreement stands for the answers that suggest such an inclination of

    the interviewee: nodding, explaining a situation, sharing an example etc. Because we are working with middle school students and not adults we decided to count also what is called non-verbal communication (Fontana & Frey, 2005)

    5. Discussion

    The main goal of this paper was to study how Scratch Programming impacts the self-directed learning capability in young learners. The quantitative data was obtained by testing the participants with the Self Directed Learning with Scratch Test (findings will be displayed in a following paper), and qualitative observations were also performed using a matrix to assess the level of consensus within the group.

    Using the information from the focus groups displayed in the consensus matrix we would like to highlight three main points:

    Relationships that were known and we have been able to confirm Situations that were suspected and we have confirmed

    One of our main goals for the study has been to start developing the idea of self-reflection within this group of group, we conclude that the majority of the

    students are able to realize that they can increase their knowledge construction if they spend longer time using the particular tool. From previous studies (Ferrer- , 2011) it was known already that the more you use a computing

    Related with question 2 (Table 1), around 90% of the participants in the focus group think that as they keep

    working on the projects and spending more time programming with Scratch their understanding and confidence increases.

    As we can read in recent literature (Hsiao & Brusilovsky, 2011) feedback and peer-reviewed comments and activities have a great impact on students work when testing an online learning platform. We already suspected that the feedback sessions could help the students to progress with their projects, and 82% of them think that the sessions where useful, (see question 1 on Table 1).

    On the other hand, and although there are studies that confirm that feedback improves self-assessment skills and communicating knowledge abilities (Luxton-Reilly & Denny, 2010), when our students were asked about their abilities to teach, and to communicate orally, the results show a 50% of agreement, but also 50% of disagreement, (see question 5 in Table 1). We want to comment that we have been working with students of 1st year of secondary education and in this particular school setting they are not really used to interchange oral information with the purpose of teaching; therefore they are aware that their oral manners need to improve.

    Lastly, there has been an unexpected finding within the focus groups answers. Related with the question about their enjoyment of the experience the results show only 45.5% of real engagement and 18% of suggested

  • 1223 Teresa Ferrer-Mico et al. / Procedia - Social and Behavioral Sciences 46 ( 2012 ) 1219 1223

    commitment with Scratch, (see question 4 in Table 1). This programming environment has been designed to really engage the students at this age and cognitive level (Maloney , Resnick, Rusk, Silverman, & Eastmond, , 2010) therefore we expected higher level of enjoyment. This may have different answers: particular characteristics of the group, confirmation that the students are just starting to learn about flux diagrams and programming sequences by using new vocabulary and thinking structures, and a validation that this subject matter (programming and self-learning) is not a trivial and easy one.

    6. Conclusion

    This paper highlights the importance of introducing programing activities within the middle school curriculum self-directed learning capabilities. Qualitative data point to the idea that time

    and some personality traits may interact with the accomplishment of the programming activity. With a next paper displaying quantitative findings we will have a more complete idea of this interaction.

    References

    Brockett, R. G., & Hiemstra, R. (1991). Self-direction in adult learning: Perspectives on theory, research, and practice. New York: Routledge. Candy, P. C. (1991). Self-direction for lifelong learning: A comprehensive guide to theory and practice. San Francisco: Jossey-Bass. Choi, S., Clark, R. (2006). Cognitive and affective benefits of an animated pedagogical agent for learning English as a second language. Journal

    Research, 34(4), 441- 466. Cohen, L., Manion, L., & Morrison, K., (2000). Research Methods in Education. (5th ed.) New York, NY: RoutledgeFalmer Corno,L., & Mandinach, E.,B. (2004). What have we learned about student engagement in the past twenty years. In D. McInemey & S. Van Etten

    (Eds.), Big Theories Revisited (pp.299-328). Greenwich, CT: Information Publishing Age. L. Morgan (Ed.)

    Successful focus groups: Advancing the state of the art, (pp.137-149). Newbury Park, CA: Sage Ferrer- Proceedings of the International Technology,

    Educational and Development Conference, 7-9 March 2011, Valencia, Spain. Fontana, A., & Frey, J., H. (2005). The interview: from neutral stance to political involvement. In N., K. Denzin & Y., S. Lincoln (Eds.). Sage

    handbook of qualitative research, (2nd ed., pp. 695-727). Thousand Oaks, CA: Sage Garrison, D. R. (1997). Self-directed learning: Toward a comprehensive model. Adult Education Quarterly, 48(1), 18-33. Hadwin, A., F., Oshige, M., Gress, C., L.Z. & Winne, P., H. (2008). Innovative ways for using gStudy to orchestrate and research social aspects

    of self-regulated learning. Computers in Human Behaviour,(26)5, 798-805. doi: 10.1016/j.chb.2007.06.007 Hartley, K., & Bendixen, L. D. (2001). Educational research in the Internet age: Examining the role of individual characteristics. Educational

    Researcher, 30(9), 22-26. Hsiao, H., Brusilovsky, P., (2011). The role of community feedback in the student example authoring process: An evaluation of AnnotEx. British

    Journal of Educational Technology,(42)3, 482-499 Liu, R., Qiao, X., Y., Liu,. (2006). A paradigm shift of learner-centered teaching style: reality or illusion? Arizona Working Papers in

    SLAT,(13)1, 77-91. Luxon-Reilly, A., & Denny, P., (2010). Constructive evaluation: A pedagogy of student-contributed assessment. Computer Science Education,

    20(2), 145-167 Maloney, J., Resnick, M., Rusk, N., Silverman, B., & Eastmond, E., (2010). The Scratch programming language and environment. ACM

    Transactions on Computing Education, 10(4), 1-15 Marzano, R., J, Kendal, J., S., (2008). Designing and assessing educational objectives. Thousand Oaks, CA: Corwin Press Inc. Monroy- Interactions, 15(2), 50-53 Onwuegbuzie, A., J., Leech, N., L & Collins, K., M. (2010). Innovative data collection strategies in qualitative research. The Qualitative Report,

    15(3), 696-726 Peppler, K., A., & Kafai, Y., B. (2007). From SuperGoo to Scratch: Exploring creative digital media production in informal learning. Learning,

    Media and Technology, 32(2), 149-166 Rauner, F., & Maclean, R. (2008). Handbook of Technical and Vocational Educations and Training Research. Bonn, Germany: Springer Schunk, D., L. (2008). Metacognition, self-regulation and self-regulated learning: Research recommendations. Educational Psychology Review,

    20: 463-467 Song, L. & Hill, J., R. (2007). A conceptual model for understanding self-directed learning in online environments. Journal of Interactive Online

    Learning: 6(1), 27-42 Teo, T., Tan, S.,C., Lee., C., B., Chai, C., S., Koh, J., H., L., Chen, W., L., Cheah, H., M. (2010). The self-directed learning with technology scale

    (SDLTS) for young students: An initial development and validation. Computers and education, 55(2010), 764-1771. doi: 10.1016/j.compedu.2010.08.001

    Winne, P., H. (1997). Experimenting to bootstrap self-regulated learning. Journal of Educational Psychology, 89, 379-410 Zimmerman, B., J. (1989). A social cognitive view of self-regulated academic learning. Journal of Educational Psychology, 81, 329-339 Zimmerman, B., J. (1990). Self-regulated learning and academic achievement: An overview. Educational Psychologist, 25, 3-17 Zimmerman, B., J. (2008). Investigating self-regulation and motivation: Historical background, methodological developments, and future

    prospects. American Educational Research Journal, 45(1), 166-183

Recommended

View more >