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DEFENCE ACADEMY OF THE UNITED KINGDOM, CRANFIELD UNIVERSITY
What do learners within an m‐learning environment need?
Annual Report 1 Aug 2011 – 31 Jul 2012
ONRG Grant N62909‐10‐1‐7121
Dr VVSS Sastry & Mr P MacLean
9/18/2012
The annual report includes the research efforts undertaken under ONRG Grant N62909‐10‐1‐7121. Included in the document are an extended literature survey and a research design approved by the MoD Research Ethics Committee. The activities described complement those of the MoLE Project.
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Contents
Introduction ............................................................................................................................................ 1
Purpose of the study ............................................................................................................................... 1
Literature Review (extended) ................................................................................................................. 3
Phases of self‐regulation ..................................................................................................................... 4
Measuring self‐regulated learning ...................................................................................................... 6
The Self‐Regulated Learning Self‐Report Scale ................................................................................... 8
Study design, methodology and data analysis ........................................................................................ 9
Aims and objectives ............................................................................................................................ 9
Experimental design ............................................................................................................................ 9
Independent Variables .................................................................................................................... 9
Dependent Variables ...................................................................................................................... 9
Hypotheses ................................................................................................................................... 10
Analysis methods .............................................................................................................................. 10
Primary analysis ............................................................................................................................ 10
Secondary analysis ........................................................................................................................ 10
Materials ............................................................................................................................................... 11
Procedure .............................................................................................................................................. 11
Ethical Considerations ........................................................................................................................... 14
Informed consent .............................................................................................................................. 14
Debriefing .......................................................................................................................................... 14
Deception .......................................................................................................................................... 14
Freedom of participation .................................................................................................................. 14
Confidentiality ................................................................................................................................... 14
Protection from harm ....................................................................................................................... 15
Professional conduct ......................................................................................................................... 15
Participants to be studied ..................................................................................................................... 15
Justification for the sample size: ....................................................................................................... 15
Chi‐square test on First Time Pass Rate (FTPR) ................................................................................ 15
Selection Criteria ............................................................................................................................... 16
Recruitment ...................................................................................................................................... 16
Participant involvement: Risks, requirements and benefits ................................................................. 17
Potential hazards .............................................................................................................................. 17
Risks .................................................................................................................................................. 17
Location ............................................................................................................................................. 17
Expected benefits to the research participant: ................................................................................ 17
Participant withdrawal ...................................................................................................................... 17
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Financial incentives, expenses and compensation ........................................................................... 18
Confidentiality, anonymity and data storage ................................................................................... 18
Consent forms and other records? ................................................................................................... 18
Lessons Identified ................................................................................................................................. 19
Institutional Review Boards .............................................................................................................. 19
Visual Analog Scale ........................................................................................................................... 19
Courses .................................................................................................................................................. 19
Conferences .......................................................................................................................................... 20
Meetings ............................................................................................................................................... 20
References ............................................................................................................................................ 20
Appendix A: MoDREC Approval ........................................................................................................... 22
Appendix B: Year 2 and 3 ...................................................................................................................... 23
Appendix C: Year 3 ................................................................................................................................ 24
Appendix D: Conference Report ........................................................................................................... 25
Appendix E: The SRL‐SRS ....................................................................................................................... 27
Appendix F: Workshop format and Product Reaction Cards ................................................................ 30
Product Reaction Cards ................................................................................................................... 31
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Introduction
In this report we recap the purpose of the study and present the text of the ongoing literature review for self‐regulated learning and associated instruments for its measurement. The major lessons identified are discussed and a summary of conferences, visits and meetings provided. The majority of the report focuses on the research protocol submitted to and approved by the Ministry of Defence Research Ethics Committee (MoDREC) on 20 July 2012 (see Appendix A).
Purpose of the study
The main aim of the project sponsored by the US Navy Office of Naval Research (Global) (Navy Grant #N62909‐10‐1‐7121) is to investigate what learners within a mobile learning (m‐Learning) environment need in order to achieve the intended learning outcomes of a particular course and become self‐organised learners. The research takes into account ongoing research efforts in this field by both the United States Department of Defence (US DoD) and the United Kingdom Ministry of Defence (UK MoD). More specifically the current study is aligned with the U.S. Military Sponsored multinational Mobile Learning Environment Project (MoLE) and UK MoD research efforts on using mobile applications for Military Annual Training Test (MATTs) materials. (For further information about the MoLE project see http://www.mole‐project.net/about‐us.)
The MoLE Project is a Coalition Warfare Program (CWP) that involves the US and twenty‐four international partners. The goal of the project is to develop and evaluate a mobile learning capability that will provide training using the global cellular network, mobile technologies, and the DD J7 JCW Public Internet.
The mobile application developed for the MoLE Proof of Concept comprise a wide range of resources including courses on trafficking in persons, MoD fitness, NGO Activities and Medical Procedures. The topics were chosen for their wider appeal and potential use of available features on mobile devices. UK MoD has several m‐Learning products that are being tested and evaluated as part of US/UK research efforts. These and other collaborative initiatives aim to capture the benefits of using mobile technologies in providing education and training to the warfighter.
At the request of ONRG the current Naval International Cooperative Programme (NICOP) project was adjusted to maximise the synergies between NICOP and MoLE thereby reflecting wider perceived requirements for understanding aspects of mobile learning. The emphasis of the research subsequently moved from the broader context of conventional online ADL training and learners to the more specific one of mobile learning and learners. Activities within this project (ONRG Grant N62909‐10‐1‐7121) became more closely aligned with the MoLE project. Contacts already established with UK military personnel managing mobile learning projects at DTrg(A) were reinforced at the MoLE workshop in February 2011. Since that time working relationships have been established with British Army training managers working at HQ Land (Andover) (Major Graham Yare AGC (ETS), SO2 Learning Technologies Design & Development| Directorate Training (Army) Major Rich Gill, SO2 Future Learning, Army Headquarters, DETS(Army)) who have facilitated and confirmed access to both learning materials, equipment, and sample populations.
Advanced Distributed Learning (ADL) features the use of networks and network technologies to provide education and training. The term also refers to the founding initiative and organisation of the same name, ADL, of the US Office of the Under Secretary of Defense for Personnel and Readiness. For the purpose of this research learning with mobile handheld technologies is understood as a subset of ADL.
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The concept of learning using handheld devices such as smartphones has drawn increasing global attention across education, commercial and defence sectors. The US Armed Forces have been seeking to understand how innovations in mobile phone technology can be used to provide performance support and training to military personnel. Although the body of research on mobile learning is only now beginning to encompass a wider range of training and education contexts reports indicate that implementing mobile learning and other technological innovations will impact on the way in which training is understood, delivered and developed in the near future.
British Army m‐learning research has investigated the utility of these devices and whether soldiers can achieve the same training objectives using mobile content as they can in conventional classroom settings (for further information see the separate project ‐ ‘Military Annual Training Test (MATT): Training Evaluation Study’). Our intention is to conduct supplementary trials to address the research goals of the present study using software applications (‘apps’) for use on mobile devices e.g., smartphones and the iPod Touch. The Army has developed a number of these apps to support learning of selected MATTs subjects.
MATT3 (Battlefield Casualty Drills) and MATT6 (Security) have been selected for use in the research because they represent two different kinds of content. MATT3 is based on developing practical skills required for administering first aid and the MATT6 content concentrates on building the soldier’s knowledge and understanding of a variety of threats to security.
Within a military context, the science and technology research goals of the present study are to:
inform development of a user‐friendly conceptual framework summarizing principles and rubrics for effective m‐learning course design practice
investigate the extent to which advanced distributed learning (ADL) facilitates attainment of learning objectives among ADL populations using knowledge‐based and skills‐based mobile learning courses
identify relationships between learner attributes and the use of mobile learning content
gather user reaction data about using mobile learning applications for military training
In terms of our research goals we propose to conduct an empirical study. The study examines the impact of introducing scaffolding on strategic approaches to learning using mobile devices. Changes in performance test scores will be used to explore goal b). The data collected on learner attributes, attitudes and approaches to mobile learning will support goals c) and d). The extent to which m‐Learning facilitates the attainment of learning objectives are analysed through performance on MATT 3 (skills‐based) and MATT 6 (knowledge‐based) test scores.
The theoretical approach underpinning this study draws principally upon social cognitive theory and Self‐Regulated Learning (SRL) (see Bandura 1986 ; Zimmermann 1989). Toering et al.’s (2012) synthesis of the significant body of self‐regulated learning research led to the development of the Self‐Regulation of Learning Self‐Report Scale. A copy of the scale used in this study is at Appendix
The perceived benefits for the UK Army and project sponsors include identification of i) the nature of the content that can exploit mobile delivery and, ii) the attributes of the learner which can benefit from this mode of delivery. In the current research we only focus on learning revision material. Having identified the relationship between content and the learner we will be able to extend the scope of what can be achieved in terms of meeting learner requirements. The research will also inform development of learning content that will exploit multi‐modal capabilities of mobile devices that have not as yet been fully leveraged. The research will also suggest ways in which military personnel can increase their own motivation to learn using mobile devices and thus better exploit
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any kind of mobile‐learning opportunity in order to reinforce and develop their professional knowledge and skills.
The most significant benefit of the study derives from the revisions to the conceptual framework for the design of conventional military computer based training or elearning materials. These revisions will be made on the basis of the results of the study and will inform the development of new forms of training and education where the student is expected to take responsibility for their own learning and engage independently with training and revision resources, at different times and in a diverse range of environments other than the classroom.
Literature Review (extended)
There has been extensive research into self‐regulated learning since 1989. The literature reviewed in this section seeks to identify mainstream concepts of and research into self‐regulated learning and the development of valid instruments for its measurement. The section begins by revisiting these concepts associated personal factors. A description of the main phases of self‐regulated learning precedes further discussion of various instruments for its measurement before describing a recently developed and validated scale.
Human functioning in social cognitive theory (Bandura 1986) is influenced by the interplay of behavioural, environmental and personal factors. Zimmerman (1989) proposed a view of learning as being a self‐regulated process based in a triadic framework of reciprocal relationship between the learner’s self, their environment and their behaviour. The framework reflects that personal factors alone do not determine what is learned. It is the dynamic reciprocity of the relationships between personal processes and environmental and behavioural events that shapes how the individual learns.
Zimmerman draws upon the literature to provide a detailed account of the processes and sub‐processes involved and identifies three kinds of influence which can affect these processes i) self‐efficacy or key personal influence ii) performance‐related influences (including self‐observation, self‐judgement and self‐reaction) and iii) environmental influences include the physical context and social experience. Within the context of self‐efficacy, self‐regulation is the exercise of influence over one’s own motivation, thought processes, emotional states and patterns of behaviour (Bandura, 1994). Over time it can assist in developing more effective acquisition and application of skills and knowledge (Zimmerman, 2006). Zimmerman (1989) concluded that student self‐regulation is both observable and trainable. In their extensive review of the literature on academic self‐regulation Zumbrunn et al. (2011) provide a useful collection of strategies for students to employ and approaches which teachers might use for encouraging self‐regulated learning; something which few students can do well without support. The authors provide their guidance from the perspective that student motivation is the key factor in the adoption of self‐regulated learning. The clearest summary of self‐regulated learning is provided by Zimmerman and Schunk (2011):
‘Self‐regulated learning and performance refers to the processes whereby learners personally activate and sustain cognition, affects, and behaviours that are systematically oriented toward the attainment of personal goals. By setting personal goals, learners create self‐oriented feedback loops although which they can monitor their effectiveness and adopt their functioning. Because self‐regulated persons must be proactive in order to set goals and engage in a self‐regulatory cycle, supportive motivational beliefs are also essential. Contrary to conventional wisdom, self‐regulation is not defined as an individualized form of learning because it also includes self‐initiated forms of social learning, such as seeking help from peers, coaches, and teachers.’ (Barry J. Zimmerman & Schunk, 2011, p. 1)
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Phases of self‐regulation In analysing motivational beliefs of learners acquirement of new skills as a form of complex problem‐solving Zimmerman & Campillo (2003) present a cyclical model which integrates motivational and self‐regulatory beliefs. The phases and subprocesses of self‐regulation described by the authors are depicted in their integrated model in Figure 1. Note that the model depicted is the updated version provided by Zimmerman (2008), the original terms replaced by Zimmerman are shown in square brackets.
Figure 1. Phases and subprocesses of self‐regulation. Terms in square brackets are replaced in the later version (after Zimmerman, 2008; Zimmerman & Campillo, 2003)
The forethought phase occurs prior to solving a problem; subprocesses are activated and motivational beliefs addressed to ‘set the stage’ for solving the learning problem. Planning and selection of strategies should be flexible and based on earlier self‐feedback from previous cycles because constant application of a single, rigid approach to all learning problems is a sub‐optimal strategy for effective learning. The term ‘intrinsic interest’ used in the original version (B. J. Zimmerman & Campillo, 2003) was later replaced by Zimmerman, probably to reflect that it refers to ‘valuing a task for its own properties’ (B. J. Zimmerman & Campillo, 2003, p. 240). The authors also acknowledge the importance of extrinsic or external sources of motivation such as rewards. Self‐efficacy, the learner’s belief that they are able to learn and carry out tasks is also a source of motivation as is goal orientation wherein learners seek to achieve mastery levels in setting, working towards and achieving learning goals.
Performance Phase
Self‐Control Self‐instruction
Imagery Attention focusing Task strategies
Self‐Observation Metacognitive monitoring
Self‐recording [Self‐recording]
Self‐reflection Phase
Self‐Judgement Self‐evaluation
Causal attribution
Self‐Reaction Self‐satisfaction/affect
Forethought Phase
Task Analysis Goal setting
Strategic planning
Self‐Motivation Beliefs Self‐efficacy
Outcome expectations Task [Intrinsic] interest/value
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During the performance phase processes are oriented towards solving the problem; their role is to influence the learner’s focus on the task and monitoring and adjustment of thought and action. Self‐ instruction refers to the learner talking themselves through a task while imagery is in reference to their being able to see themselves performing a task which assists in understanding of how it can be approached and carried out.
In a reflective phase similar to Gibb’s (1988) reflective model of learning reflection upon and evaluation of personal performance is intended to influence subsequent forethought in further problem solving and learning. Self‐evaluation is usually carried out against standards which learners set for themselves and against which monitor progress and outcomes. Being able to correctly attribute good or poor performance to the causes is a quality found in learners with stronger self‐efficacy beliefs. When a learner adapts their approach on the basis of reflection upon performance they are likely to develop as opposed to learners who become defensive and unrealistic and less likely to develop. This is where a thorough analysis of performance and attempt to draw sound conclusions about the reasons is a vital component of reflection (e.g., Gibbs, 1988; Tripp, 1993; Argyris & Schön, 1974).
Zumbrunn et al., (2011) provide what they call a popular version of the original model (see Figure 2). It appears to be simplified and places greater emphasis on motivation. What is again interesting is the way in which it stresses the need to address emotional responses to the outcomes of the experience which is again similar to the second stage of Gibb’s model and the advice to address feelings and thoughts both at the time of performance and afterwards. The authors, however, provide no explanation for why this should be an important part of the process.
Figure 2: A popular model of self‐regulated learning (souce: Zumbrunn et al., 2011)
Performance
Monitoring Phase
Employ strategies to make progress on the learning task.
Monitor the effectiveness of the strategies employed.
Monitor motivation for
completing the learning task.
Reflection on Performance Phase
Evaluate performance on the
learning task.
Manage emotional responses related to the outcomes of the learning experience.
Forethought and Planning Phase
Analyze the learning task.
Set goals toward completing the task.
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Schön (1983) puts to us that the learner or in the case of professionals learning and developing through reflective practice, the ‘practitioner’, should attend to what they are feeling and learning because thoughts and feelings are an integral part of what has been experienced. Therefore, they must be included in sense‐making and analysis of the experience in order to develop new personal theories for self‐experimentation:
‘… the practitioner allows himself to experience surprise, puzzlement, or confusion in a situation which he finds uncertain or unique. He reflects on the phenomenon before him, and on the prior understandings which have been implicit in his behaviour. He carries out an experiment which serves to generate both a new understanding of the phenomenon and a change in the situation.’ (Schön, 1983, p. 68)
Measuring self‐regulated learning Following a brief analysis of several earlier instruments designed for the measurement of self‐regulation of learning, Zimmerman (2008) summarises more recent developments in theory and methodological innovations which take advantage of advanced in technology and the ability to carry out online research.
He discusses earlier scales which measure the self‐regulation of learning as a metacognitive, motivational and behavioural construct. These include two questionnaires; the Learning and Study Strategies Inventory (LASSI) (C.E. Weinstein, Palmer, & Schulte, 1987) and the Motivated Strategies for Learning Questionnaire (MSLQ) (Pintrich, Smith, Garcia, & Mckeachie, 1993). The original 1987 version of LASSI was a 77‐item self‐report instrument in questionnaire form designed to assess learning strategies. In a second, revised edition (Claire E Weinstein, Palmer, & Shulte, 2002) 80 items are arranged within 10 subscales organised by what the authors call the three components of strategic learning; skill, will, and self‐regulation. A summary of the subscales organised by component is shown in Table 1.
Component of Strategic Learning
Aim of subscales Subscales
Skill
Examination of strategies, skills and processes for identifying, acquiring and constructing meaning for new information, ideas and procedures and planning for demonstration of new knowledge.
Information processing Selecting Main Ideas Test Strategies
Will Measurement of receptiveness to new learning, attitude and interest in learning environment, motivation, self‐discipline and concern about performance.
Attitude Motivation Anxiety
Self‐regulation Measurement of self‐regulatory processes, focus and concentration over time, monitoring and use of different kinds of study support.
Concentration Time Management Self‐Testing Study aides
Table 1: Summary of revised LASSI components and scales (source: Weinstein et al., 2002)
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The questionnaire is organised by subscale and gathers responses using a 5‐point Likert scale with ratings between ‘not at all typical of me’ to ‘very much typical of me’. The authors claim that the revised LASSI with its three components of skill, will, and self‐regulation is useful instrument for measurement of learning and study strategies and, as a diagnostic measure, a basis for improving student learning. However, it has been suggested that there are other models which provide a better fit to the underlying three factors contained in the original version; effort‐related activities, goal orientation, and cognitive activities (see Prevatt et al., 2006).
THE MSLQ (Pintrich et al., 1993) is also a self‐report instrument. It is an 81‐item questionnaire with 15 subscales addressing cognitive, metacognitive, and resource management strategies. The questionnaire was designed for use at the level of the college course and assesses student motivation and use of learning strategies. It is organised in two sections, motivation and learning strategies, and the responses to items are gathered using a 7‐point Likert scale ranging from ‘not at all true of me’ to ‘very true of me’. A summary of the MSLQ components is provided in Table 2.
Section Aim of the subscales Subscales
Motivation Assessment of learners’ goals and beliefs about their values, their skills to succeed and their anxiety about tests.
Intrinsic goal orientation Extrinsic goal orientation Task value Control of learning beliefs Self‐efficacy for learning and performance Test anxiety
Learning strategies Assesment of learners’use of different cognitive and metacognitive strategies and their use of different resources.
Rehearsal Elaboration Organisation Critical thinking Metacognitive self‐regulation Time and study environment management Effort regulation Peer learning Help seeking
Table 2: Summary of the MSLQ components (sources: Pintrich et al., 1993; Duncan & McKeachie, 2005)
In the conclusion to their account of the making of the MSLQ, Duncan and McKeachie (2005) make the point that the validity of self‐report scales have always been open to question with one the main concerns being that of social desirability bias, or the tendency of questionnaire respondents to provide responses which they think will be viewed favourably. Although they have found no significant response bias in their work with MSLQ, they recommend that this be kept in mind when interpreting self‐report data.
LASSI, MSLQ and other self‐regulation measurement instruments are perceived to overlap conceptually (Entwistle & McCune, 2004) and share Zimmerman’s (1989, 2006, 2008) defining criteria for self‐regulated learning i.e., the ‘degree to which students are metacognitively, motivationally, and behaviourally active participants in heir own learning process’ . What Zimmerman suggests is that the two instruments discussed here measure similar processes but the names of the processes vary. However, it is also clear that some have a greater emphasis on one or other of the defining criteria for example, motivation appears to draw more attention in the MSLQ than LASSI.
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The Self‐Regulated Learning Self‐Report Scale Toering et al. (2012) draw upon the significant body of self‐regulated learning research to develop the Self‐Regulation of Learning Self‐Report Scale (SRL‐SRS). The scale is a synthesis of several previous instruments. It has been designed with the intention of measuring self‐regulation as an attribute in different learning domains. The original 50 items were arranged using subscales for each of six factors in the self‐regulation of learning; planning, self‐monitoring, evaluation, reflection, effort, and self‐efficacy. These were eventually reduced to 46 items. Although the authors found that the SRL‐SRS has some limitations they confirm that it can reliably measure self‐regulation as a reasonably stable attribute. Its reliability and domain independence render it suitable for the current project.
In developing the SRL‐SRS the authors aimed to create and validate and instrument suitable for measuring the self‐regulation of learning as a ‘relatively stable attribute in multiple learning domains’ (Toering et al., 2012, p.25) and not just specific academic fields. The final version of the SRL‐SRS was drawn from the extensive research literature on self‐regulated learning. Six subscales were identified and incorporated: planning, self‐monitoring, evaluation, refection, effort, and self‐efficacy. The final 46 items can be seen in the questionnaire at Appendix E.
The planning and effort subscales were derived from Hong and Neil (2001) who, drawing on Spielberger’s work on state‐trait anxiety, hypothesised that self‐regulation consisted of transitory cognitive states states and relatively stable traits. Whereas the former were considered to be variable dependent upon context the latter, trait self‐regulation, is a relatively stable intellectual characteristic in many contexts. Herl et al.’s (1999) research into problem‐solving measures used the distinction between state and trait for both cognitive and affective domain measurement and subsequently developed and validated a number of instruments. The SRL‐SRS uses the trait the metacognition subscale for self‐monitoring. Howard et al.’s (2000) validated self‐report measure for problem‐solving provided the evaluation subscale. The subscale for reflection comes from the work of Peltier et al. (2006) who perceive reflective learning as a series of stages from shallow habitual action/learning to understanding, reflection and finally, critical/intensive reflection. The scale developed by the authors was validated and refined in a number of studies. Finally, the self‐efficacy subscale is taken from Schwarzer and Jerusalem’s General Self‐Efficacy Scale, as cited in Schwarzer et al. (1997) which is designed to assess ‘optimistic self‐beliefs to cope with a variety of difficult demands in life’. The subscales and related items used in the version of the SRL‐SRS used for this study are provided at Table 3:
Item Number Subscale
1 – 8 Planning
9 – 17 Self‐monitoring
18 – 22 Evaluation
23 – 27 Reflection
28 – 37 Effort
38 – 46 Self‐efficacy
Table 3: Subscales of the final SRL‐SRS questionnaire.
The decision to use the SRL‐SRS is based upon Toering et al.’s claims to its reliability and validity as a measurement of self‐regulated learning. Its particular merit lies in its perceived usefulness in multiple domains of learning.
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Study design, methodology and data analysis
Aims and objectives In order to address our research goals stated in Section 8, the research involves inviting Soldiers (total sample of n=128) from the British Army to be introduced to the processes of self‐regulated learning. Participants will be coached on how to approach their learning when using content on an m‐learning device. More specifically, they will be coached on learning strategies that map on to 6 attributes of self‐regulated learning, as evidenced in the literature (see for example, Zumbrun et al. 2011; Toering et al., 2012). Participants will be asked for their consent to use performance data from their Battlefield Casualty Drill (BCD) and their Security knowledge assessment tests for a study being run and analysed by researchers from Cranfield University. The tests will be designed by Cranfield University and validated by Army MATT 3 and MATT 6 Subject Matter Experts (SMEs); the results will not contribute towards the Soldiers’ annual training records.
Experimental design An empirical mixed experimental design will be adopted to examine whether structuring individual’s learning (scaffolding) when using content on a mobile device leads to a change in self‐regulated learning attribute ratings. The study also examines whether structuring individual’s learning improves performance on MATTs assessments. Therefore a two group comparative study will be conducted.
Independent Variables There is one independent variable (IV) manipulated in the study, which is whether or not an individual’s learning is structured by scaffolding. Therefore for this IV there are two conditions: scaffolding and the control condition (no scaffolding).
Dependent Variables To investigate the aims of this study scores from bespoke MATT 3 and MATT 6 tests and the SRL‐SRS scores will be collected and used as Dependent variables (DVs) in separate analyses.
An opportunistic sample of 128 soldiers in total with 64 soldiers in each group will undertake the research (see Figure 3).
Different major units will be contacted and potential volunteers will be drawn from at least four of these. Participants within one unit can not be randomly assigned to each of the two conditions because of the risk of corrupting the experiment where participants are likely to discuss the treatment being applied to their group with members of the other group. Therefore each unit with volunteers will be randomly assigned to one of the two conditions. This will avoid sharing of SRL scaffolding information (see Independent Variable) between the two groups and subsequent contamination of data. If volunteers are available from more than the minimum of four units then this will further reduce the potential for bias.
Currently the major units which will be approached are Royal Logistic Corps Regiments but other units may need to be included depending on operational requirements and availability.
The potential volunteers for each group will have more than 2 years but less than 10 years service in the Army. These volunteers will be representative of the target population of personnel i.e., those required to undertake MATTs training.
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Hypotheses
H1. There will be a difference between pre and post SRL‐SRS scores between and within groups.
H2. There will be a significant difference in MATTs assessment performance scores between the control and experimental groups.
H3. There is significant change in Self‐Regulatory Learning Self‐Report scales dependent upon the type of learning content i.e., knowledge‐based MATT 6 and skills‐based MATT 3.
Analysis methods
Primary analysis A demographic questionnaire capturing participant experience will be analysed both quantitatively (frequencies and descriptive) and self‐reported confidence ratings of MATT3 and MATT6 content knowledge will be analysed.
The six SRL‐SRS subscale ratings will be derived from summing the item scores within each subscale. The pre and post SRL‐SRS subscale ratings will be analysed for both groups by a paired samples t‐ test as interval level data is obtained and we are investigating whether there is a difference between the pre and post subscale SRL‐SRS scores of individuals.
The results of the MATTS assessments will be in the form of the total number of correct answers, which will be analysed by an independent samples t test as the data will be interval raw scores. The t‐tests will be used to determine if there is a significant difference between pre SRL‐SRS subscale ratings and post SRL‐SRS subscale ratings and whether there is a significant difference between the groups in MATTS assessment performance scores.
In addition to looking at the number of correct answers for the MATTS assessments, results in terms of first‐time pass or fail will be analysed using a Chi‐square test as the data collected will be categorical (nominal) where participants either pass or fail first time. The Chi‐square test will determine if there is a significant association between FTPRs whether participant’s learning was scaffolded or not (i.e. the group).
Secondary analysis Perform a principal component analysis using Self‐Regulation – Self‐Report data augmented by demographic data and type of learning content to discern the clusters in the data set.
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Materials
The participants will be using MATT3 (Battlefield Casualty Drills) and MATT6 (Security) mobile learning materials designed by an independent organisation for and validated by the Army. The materials are installed on Apple iTouch™ handheld devices. DTrg(A) will configure and provide up to 40 of these devices at a time in support of the research project.
A briefing introducing self‐regulated learning and an online support resource accessible via the Internet will be used by the research team to provide scaffolding of learning processes to the experimental group (see ‘Group 2’ in Figure 3).
Data will be gathered using test scores and a Self‐Regulation of Learning Self‐Report Scale (SRL‐SRS) adapted from Toering et al. 2012. A Likert scale is used to collect responses. The full list of question items is shown at Appendix E.
Bespoke MATT3 and MATT6 assessments for use on Day 8 (see Figure 1, Day 8, serial a)) are being developed by Cranfield University from question bank items provided by the Army’s SMEs. The SMEs will validate the tests prior to use.
Procedure
The ‘Informed Consent’ form comprises a single document with information for participants and the form to be signed. This single document will be given to all prospective participants at least 24 hours prior to the trials taking place. Those who choose to take part will attend at the given time. (See Figure 3 for a schematic of the design including timings.)
Upon arrival at the trial event on Day 1, participants will be registered by a member of the military personnel who will record their name and last three digits of their service number and issue them with a Participant Number. This will ensure that confidentiality of data is maintained. See Section 18a for further details on the reasons for collecting names and the last three digits of service numbers. They will be asked to enter their Participant Number on all of the subsequent paperwork given to them by the research team. The assisting military personnel will be independent and not have authority over participants. The member of the military personnel issuing participant numbers will be responsible for ensuring that the researchers do not have access to the key mapping name and last three digits of the service number to Participant Number.
Once all potential participants have arrived, instructors will leave the room and the research team will go through the details provided in the ‘Informed Consent’ (see note above and Appendix A) with the participants and answer any questions they may have. Participants will be given the opportunity to ask any questions, and will then be asked to sign the consent form if they wish to take part. Participants will be given a signed copy of the consent form to keep. Choosing not take part will not have any career impact. Further opportunity to ask questions on a one‐to‐one basis will be available as the forms will be collected from individuals by the research team who will ask each participant if they have any further questions and confirm they are happy to consent. At this point, non‐participating military personnel will re‐enter the room to assist with administration.
The researchers will not be able to identify participants by their name or service number. Only Participant Numbers will be recorded on trial documentation. Within 7 days of data collection, the key mapping the last three digits of service numbers and names to Participant Numbers will be destroyed to ensure anonymity of data. All subsequent analyses are conducted using only the Participant Number.
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Since the study spans over 8 days there is a likelihood that participants will lose their Participant Number. We require a mechanism to help them retrieve
Figure 3: Schematic representation of the research design showing timings and activities for the control and experimental groups.
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this. To this end, a key mapping the Participant Number with the participant is maintained by an independent member of the military staff at the participant’s unit. This person will be given a bank of numbers to issue for the study.
All participants will complete a Demographic Questionnaire which will gather data on the following:
Age
Gender
Educational background
Experience of mobile learning
Military career
Approximate interval since last MATT3 and MATT6 training An additional item will ask all participants to rate how confident they are in their knowledge of MATT3 and MATT6. All participants will then be asked to complete the SRL‐SRS questionnaire. Participants from the control group (Group 1) will be issued with an iPod TouchTM and ancillaries using an AFG1033. The consequent actions following loss or theft of the device will be explained and it will be made clear that a charge to cover replacement may be incurred. Following instruction on using the equipment e.g., switching on, interacting with and recharging, the participants will be dispersed until Day 8. N.B. The MoDREC Chairman will also be informed of any loss or damage to the devices. This information will be included in the final report.
After a short break participants from the experimental group (Group 2) will attend a briefing during which they will review the SRL‐SRS and be introduced to a framework of processes which support the development of self‐regulated learning. The briefing will conclude with a discussion of ways in which individuals may apply self‐regulated learning processes to using mobile learning apps. They will then be issued with iPod TouchTM devices and following instruction on using the equipment e.g., switching on, interacting with and recharging, they will be dispersed until Day 8.
On Day 8 participants will re‐assemble for the final research activities. Non‐participating military personnel will not be present.
The researchers will administer assessments of MATT3 and MATT6 to be taken by all participants. The participants will be reminded that the results will not contribute towards annual training records. Participants will be given green pens to complete the assessment papers. The green pens will be collected and a different colour pen handed out for self‐marking to reduce the likelihood of participants altering their answers. To encourage accurate self‐marking it will be emphasised that their answers and scores will be seen only by themselves and the researchers. Their initial marking is a part of the feedback to themselves on their performance. Having seen their results, the participants will again complete the SRL‐SRS. All assessment papers and SRL‐SRS forms will be collected. The assessments are second‐marked by the researchers and it is these scores that will be used in the analysis.
All participants will be debriefed about the research and how they may make use of the concepts being investigated and apply what they know about themselves from their SRL‐SRS self ratings in their training. Before concluding they will be asked if they have any questions.
Volunteers will be sought from among the groups to contribute to a final workshop which will be conducted after a short break. Instructions for the workshop (see Appendix F) will be given prior to the participants being given sets of reaction cards. They will select cards which reflect their views on the experience of learning with mobile apps (see also Appendix F). Their selections will be captured
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on a flipchart and will be used to form the basis of a discussion. A digital recorder will be used to capture what is said.
Ethical Considerations
Informed consent All participants will be briefed on the nature of the trial and what they will be asked to do. All participants will be given a copy of the participant information sheet (attached to this form) and will be given a period of not less than 24 hours to consider the trial. A member of the research team will be available to answer any questions the participants may have. Participants will be given a copy of the consent form to sign if they wish to take part and they will be given a copy to keep. No non‐participating military personnel will be present when participants are briefed. Signing the consent form will signify providing informed consent. Only those who sign the consent form will be accepted as participants in the study.
Debriefing Participants will be provided with contact details of the researchers in case they have any queries about the research. A summary of the results will be available on request. At the end of the study, participants will be fully debriefed, where instructors will explain the trial in more detail. Participants will have the opportunity to ask any questions.
Deception The research methodology used in this project does not require disguising the purpose of the study. The participants will be fully briefed on the project as mentioned above.
Freedom of participation The researchers will brief participants on the nature of the trial and no instructors or other non‐participating personnel will be present when participants are asked to give their consent. No pressure will be put on them in order to persuade them to give their consent. Participants will have an opportunity to ask any questions.
Participants will be clearly informed that they have the right to withdraw their data up to the point at which it becomes unidentifiable among other pooled data.
Confidentiality The researchers will not be able to identify participants from the Participant Number. The key associating the Participant Numbers with participants’ names and last three digits of service numbers (held independently of the researchers) will be destroyed within 7 days of completion of data collection (see Sections 18a).
These anonymised data will only be used for reporting to MoD on the findings of the study, and academic journal publications/conference presentations subject to MoD approval being sought.
The research team will have access to the records and the anonymous data. Data from the study will be combined, entered, and analysed using an appropriate statistical software package (e.g. SPSS for Windows).
In addition to the MoD, the anonymised data will be made available to the project sponsors i.e., US Department of the Navy Office of Naval Research, ADL Co‐Lab, EOARD.
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Protection from harm Participants will not incur any physical or psychological harm and their career will not be harmed as all data will be collected confidentially and kept in a locked filing cabinet by the researcher.
Professional conduct The researchers will carry out the study in accordance with standard professional conduct principles. It will be conducted according to the provisions of:
The Codes of Conduct, Ethical Principals and Guidelines of the British Psychological Society (2006).
The Guidelines of the Ethical Conduct and Scrutiny in MoD Research, JSP 536 (2006).
US Directives related to protection of human participants:
o 32 CFR 219.101 OSD Version 2.0 o DoD Directive 5400.11 (DoD Privacy Program) o DoD Directive 3216.2 (Protection of Human Subjects in DoD‐Supported Research)
Participants to be studied
Number of participants: n= 128
Lower age limit: 18
Upper age limit: 45
Gender: Male and Female
Justification for the sample size: The analysis of this study involves several types of analysis, which each require a different sample size in order to obtain 80% power. The statistical tests to be adopted and the sample size justifications are as follows:
Whether there is a difference in MATTs assessment performance scores (total number of correct answers) between the groups will be analysed using a two sample independent t test. The sample size per group needed for a two sample independent t test with equal sample sizes and a .05
nondirectional alpha (ɑ) was estimated using power tables (Cohen, 1988, Power and the factors affecting it, n.d) and G*Power a statistical power analysis software program (Faul, Erdfelder, Lang, & Buchner, 2007).
A sample size per group of 64 is required to achieve a statistical power of 0.80 (accepting a 1 in 5 chance that a significant effect may be missed a type II error) given an effect size of d = .50 and a significance level of p = 0.05 (Cohen, 1988).
For a Two sample dependent (paired) t‐test with equal sample sizes and a nondirectional (ɑ) hypothesis (two‐tailed), a sample size per group of 34 participants is required to achieve a statistical power of 0.80 (accepting a 1 in 5 chance that a significant effect may be missed a type II error) given an effect size of d = .50 and a significance level of p = 0.05 (G Power, version 3.1.3).
Chi‐square test on First Time Pass Rate (FTPR) For both trials, a chi‐square test will be carried out to examine the FTPR of participants in each group (scaffolding and the control). When using the Chi‐square test the DV measures how many participants in each group will fall into certain categories. As a consequence, data needs to be gathered from a suitable number of participants to make sure that a sufficient number of participants turn out to be placed in to each classification. Smaller expected frequencies in one or
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more cells can reduce power greatly. Howell (1997) points out that having smaller expected frequencies can also act to inflate the type I error rate but with at least a total of 20 participants the alpha rarely rises above .06. The minimum is considered to be at least 20 participants, with no cell (expected frequency) smaller than 5 (Greene & D’Oliveira, 1999; Wilson VanVoorhis & Morgan, 2007). Therefore a sample size of 51 per cell (group) will be more than adequate. This study will use an opportunistic sample of participants.
Selection Criteria Participants will be military personnel from the British Army who have completed their Phase 1 and Phase 2 training.
Recruitment Potential volunteers will be approached by the researchers at a pre‐trial briefing where they will be briefed on the nature of the study, that is, why the researchers wish to conduct the trial and have their data. No training instructors will be present when potential volunteers are briefed. Potential participants will have an opportunity to ask any questions. Participants will be given 24 hours to consider whether or not they would like to take part and give consent for their data to be used at the end of the trial.
Potential volunteers will be approached by the researchers at a pre‐trial briefing where they will be briefed on the nature of the study, that is, why the researchers wish to conduct the trial and have their data. No training instructors will be present when potential volunteers are briefed. Potential participants will have an opportunity to ask any questions. Participants will be given 24 hours to consider whether or not they would like to take part and give consent for their data to be used at the end of the trial.
The chain of command will identify participants for each group with more than 2 years but less than 10 years service in the Army. Participants for this study will be asked by the researchers to give their consent to take part in the trial and for the researchers to use their performance data. No instructors will be present when consent is given. Therefore use of data for this study is subject to a signature on a participant consent form which will signify informed consent. Participants will be provided with an information sheet covering the aforementioned items, before the beginning of the trial. Data from potential volunteers will not be used in the study unless participants have provided informed consent.
Invitations to take part in the trial and information sheets will only be sent to potential participants who are 18 and over. It should be noted that the study imposes no physical or cognitive challenge beyond that which would be experienced by the participants in their normal role.
We cannot see any reason why people might feel pressured to give informed consent to take part in the trial and for their performance and data to be used. Again, no instructors will be present when consent is obtained during the trial briefing session. Participants will be clearly informed that they have the right to withdraw their data up to the point at which it becomes unidentifiable among other pooled data.
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Participant involvement: Risks, requirements and benefits
This section discusses potential hazards, risks or adverse effects associated with the study
Potential hazards Use of the device while driving, operating machinery or doing other activities where concentration and manual manipulation are required.
Risks The risks of injury to participants or others are no greater than those normally encountered in daily life. Participants will be reminded that they are to abide by the rules that apply to the use of mobile devices in their working environment.
There is a risk that participants may misinterpret the purpose of the research materials and assume that the test results contribute towards their annual training record. (See procedure notes for mitigation.) The assessment sessions will not be more than 2 hours in duration.
Risk is also mitigated because the researchers are experienced in the administration and conduct of research using questionnaires and assessments in experimental research and workshops. One researcher is an applied experimental/cognitive psychologist with several years experience of research in the human factors domain.
Location We are currently in discussion with Training Wing staff to use the facilities at various Royal Logistic Corps Units. To be confirmed.
Individual interviews / questionnaires will not discuss any topics or issues that might be sensitive, embarrassing or upsetting. The research uses questionnaires to measure individual’s self reported ratings of their self‐regulated learning processes. It will be made clear that there is no correct response and no set of responses is any better or worse than another. As with the MATTS assessments, at the analysis stage the questionnaire data will be anonymised.
Expected benefits to the research participant: All participants may benefit by learning and experiencing new ways of approaching training using a mobile device. Those in Group 2 (receive scaffolding) may learn how to develop effective learning strategies. These strategies may in turn contribute to enhanced performance in other learning tasks.
Taking part in the research will also provide participants with an additional opportunity for them to revise their MATT3 and MATT6 knowledge and skills in preparation for the next annual test.
Participant withdrawal Operational requirements, work commitments, or sickness may require individuals to withdraw from the study. Participants might not continue with the study due to medical discharge or if they were found unfit for service. In addition, participants will be withdrawn from the study if they show any sign of undue stress or if they do not adhere to the requirements of the protocol. Participants have to give consent to take part in the trial and for the research team to use their data. They will be informed of their right to withdraw all their data from any analysis conducted should they wish without any consequence. Therefore, if a participant withdraws, their data will be omitted from any analysis conducted.
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If large groups of participants at units have to be withdrawn because of the units’ operational requirements the impact on data collection and analysis will be reviewed. When there are insufficient numbers of participants available, the study will be postponed or terminated altogether.
Financial incentives, expenses and compensation There are no financial incentives for participants and because they are not expected to travel in order to take part, no travelling expenses will be given.
Confidentiality, anonymity and data storage Since the study spans over 8 days there is a likelihood that participants will lose their Participant Number. We require a mechanism to help them retrieve this. To this end, a key mapping the Participant Number with the participant is maintained by an independent member of the military staff at the participant’s unit. This person will be given a bank of numbers to issue for the study.
Volunteers will be allocated a participant number on arrival at the trial event and it is this number which will be used as an identifier on any assessment paperwork, results, questionnaires and workshop notes. A key of which number has been allocated to whom will be created, maintained and retained by a representative from the local military personnel. It will not be accessible to Cranfield University researchers. All raw data will, therefore, remain anonymous.
Raw data will remain anonymous and confidential; only accessible to Cranfield University Research staff. Cranfield University researchers will provide local military personnel responsible for registration with a series of unique participant numbers.
If a participant withdraws from the study it will enable us to destroy associated data from the analysis. The key is destroyed within 7 days of data collation. These anonymised data will only be used for reporting to MoD on the findings of the study, and academic journal publications and conference presentations subject to MoD approval being sought.
The research team will have access to the records and the anonymous data. Data from the study will be combined, entered, and analysed using an appropriate statistical software package (e.g. SPSS for Windows). In addition to the MoD, the anonymised data will be made available to the project sponsors i.e., US Department of the Navy Office of Naval Research, ADL Co‐Lab, EOARD.
Consent forms and other records? The consent forms and other data arising from this study will be handed over to the MoD for secure storage for a period of 100 years in accordance with MoD guidelines. Paper data and any CDs will be kept in locked cabinets and in locked offices or storage rooms, if unattended. Access to cabinets and / or storage rooms holding the data will be restricted to authorised personnel only.
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Lessons Identified
Institutional Review Boards It was initially assumed that the study, even though it would involve human participants would not require approval from the Ministry of Defence Research Ethics Committee (MoDREC). This assumption was based on two factors. The first was the perception that, following completion of the MoDREC ethics checklist, we would not require MoDREC approval. The second was that we were informally advised that the nature of the research described did not involve psychological probing and the fact that participants would be aged 18 years old and over, but that we should send the protocol to the MoDREC chairman anyway. The chairman’s response was that the protocol would need approval after all; a process which was to delay the project considerably while the protocol went through the stages of submission to the Army Scientific Advisory Committee, review, revision and then submission to MoDREC and presentation before the MoDREC members before making final revisions.
In any future research involving human participants the investigators will identify the relevant Internal Review Board.
Visual Analog Scale The visual analog scale (VAS) is a line along which research respondents may place a mark indicating a finer degree of rating than available in the conventional discrete measurements of characteristic or attitude found in Likert scales. On paper a line of 100mm is used. Equivalents can readily be implemented on web pages and possibly smartphone‐like mobile devices for the collection of user response data.
In future projects of this nature, the researchers will give serious consideration to whether an electronic version of the VAS might serve as a more suitable instrument in research into learning with technology. For more on the VAS including critical reviews see Wewers & Lowe. (1990), Reips & Funke (2008) and Marsh‐Richard et al. (2009).
Courses
In compliance with DoD requirements for conducting research with human subjects, both investigators have completed the CITI (Collaborative Institutional Training Initiative) research ethics training. Specific modules and completion certificate numbers are provided in Table 4
Dr Sastry
Module Ref Date Complete
Intstitutional Review Board Reference Resource #7932190 05/25/12
Investigators and Key Research Personnel – SBR #7932191 05/21/12
Social and Behavioural Responsible Conduct of Research #7932192 06/04/12
Mr MacLean
Module Ref Date Complete
Intstitutional Review Board Reference Resource #7455739 05/15/12
Investigators and Key Research Personnel – SBR #7455740 03/08/12
Social and Behavioural Responsible Conduct of Research #7455741 05/16/12
Table 4: Details of CITI Research Ethics modules
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Conferences
During the period 2‐4 May 2012, Mr Maclean attend the Educational Innovation in Economics and Business conference for 2012 held at the InHolland University, Haarlem, The Netherlands. While at the conference he presented a paper authored by both himself and Dr Sastry. See Appendix # for the conference report.
Meetings
MOLE workshop, Windsor, March 2012
Dr Sastry, Cambridge
Telecon support for MoLE
HQ Land, Andover, for discussions with the Army
Teleconferencing with JH
JH visits in
Fort Blockhouse, Portsmouth to meet the BCD Training Team manager
17 Regt RLC, Marchwood, to discuss research participation
References
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Duncan, T. G., & McKeachie, W. J. (2005). The Making of the Motivated Strategies for Learning Questionnaire. Educational Psychologist, 40 (2), 117–128.
Entwistle, N., & McCune, V. (2004). The Conceptual Bases of Study Strategy Inventories. Educational Psychology Review, 16(4), 325–345.
Faul, F., Erdfelder, E., Lang, A.‐G. & Buchner, A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39, 175‐191.
Gibbs, G. (1988). Learning by doing : a guide to teaching and learning methods. [London]: FEU. Herl, H. E., O’Neil, H. F., Chung, G. K. W. K., Bianchi, C., Wang, S., & Mayer, Richard E. (1999). Final
report for validation of problem‐solving measures ( No. CSE Technical Report 501). National Centre for Research on Evaluation, Standards, and Student Testing, UCLA. Retrieved from http://www.cse.ucla.edu/products/reports/TECH501.pdf
Hong E., & O’Neil H. F. (2001). Construct validation of a trait self‐regulation model. International Journal of Psychology, 36(3), 186–194.
Howard, B. C., McGee, S., Shia, R., & Hong, N. S. (2000). Metacognitive Self‐Regulation and Problem‐Solving: Expanding the Theory Base through Factor Analysis. Retrieved from http://www.eric.ed.gov/ERICWebPortal/contentdelivery/servlet/ERICServlet?accno=ED470973.
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Marsh‐Richard, D. M., Hatzis, E. S., Mathias, C. W., Venditti, N., & Dougherty, D. M. (2009). Adaptive Visual Analog Scales (AVAS): A Modifiable Software Program for the Creation, Administration, and Scoring of Visual Analog Scales. Behavior research methods, 41(1), 99–106.
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Pintrich, P. R., Smith, D. A. F., Garcia, T., & Mckeachie, W. J. (1993). Reliability and Predictive Validity of the Motivated Strategies for Learning Questionnaire (MSLQ). Educational and Psychological Measurement, 53(3), 801–813.
Prevatt, F., Petscher, Y., Proctor, B. E., Hurst, H., & Adams, K. (2006). The Revised Learning and Study Strategies Inventory: An Evaluation of Competing Models. Educational and Psychological Measurement, 66(3), 448–458.
Reips, U.‐D. & Funke, F., 2008. Interval‐level measurement with visual analogue scales in Internet‐based research: VAS Generator. Behavior Research Methods, 40(3), pp.699–704.
Schön, D. (1983). The reflective practitioner : how professionals think in action. [New York]: Basic Books.
Schwarzer, R., Bäßler, J., Kwiatek, P., Schröder, K., & Zhang, J. X. (1997). The Assessment of Optimistic Self‐beliefs: Comparison of the German, Spanish, and Chinese Versions of the General Self‐efficacy Scale. Applied Psychology, 46(1), 69‐88.
Tripp, D. (1993). Critical incidents in teaching: developing professional judgement. London ;;New York: Routledge.
Weinstein, C.E., Palmer, D. R., & Schulte, A. C. (1987). The Learning and Study Strategies Inventory. Clearwater, FL: Prentice Hall.
Weinstein, Claire E, Palmer, D. R., & Shulte, A. C. (2002). LASSI: learning and study strategies inventory. Clearwater, FL: H & H Publishing Co.
Wewers, M.E. & Lowe, N.K., 1990. A critical review of visual analogue scales in the measurement of clinical phenomena. Research in nursing & health, 13(4), pp.227–236.
Zimmerman, B. J., & Campillo, M. (2003). Motivating Self‐Regulated Problem Solvers. In J. E. Davidson & R. J. Sternberg (Eds.), The Psychology of Problem Solving. Cambridge University Press.
Zimmerman, Barry J. (1989). A Social Cognitive View of Self‐Regulated Academic Learning. Journal of Educational Psychology, 81(3), 329–339.
Zimmerman, Barry J. (2006). Development and adaptation of expertise: The role of self‐regulatory processes and beliefs. In K. A. Ericsson, N. Charness, P. J. Feltovich, & R. R. Hoffman (Eds.), The Cambridge handbook of expertise and expert performance (Vol. 45, pp. 705–722). New York: Cambridge University Press.
Zimmerman, Barry J. (2008). Investigating Self‐Regulation and Motivation: Historical Background, Methodological Developments, and Future Prospects. American Educational Research Journal, 45(1), 166–183.
Zimmerman, Barry J., & Schunk, D. H. (2011). Handbook of Self‐Regulation of Learning and Performance. New York: Routledge.
Zumbrunn, S., Tadlock, J., & Roberts, E. D. (2011). Encouraging Self‐REgulated Learning in the Classroom: A Review of the Literature. MERC.
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Appendix A: MoDREC Approval
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Appendix B: Year 2 and 3
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Appendix C: Year 3
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Appendix D: Conference Report
Conference Report: Grant NICOP #N61909‐10‐1‐7121 Educational Innovation in Economics and Business 2012 2‐4 May 2012, Haarlem, The Netherlands Visiting personnel: Mr Piers MacLean, Cranfield University
1. Introduction
EDINEB (Educational Innovation in Economics and Business) has evolved from the need to improve Economics and Business higher education. It is concerned with connecting people, institutions and the development of innovative instructional methodologies, approaches and tools. It held its 19th annual conference at the Inholland University of Applied Sciences, Haarlem, The Netherlands during the period 2‐4 May, 2012. The theme was ‘The Role of Business Education in a Chaotic World’. Conference tracks included the characteristics of the networked student and the ways in which better use could be made of technologies and the development of e‐learning programmes in order to support them. Other tracks were oriented to sociological aspects of educational innovation within local, national and global contexts.
2. Relevance
There is greater demand around the world for alternatives to conventional taught training and education programmes. The demand comes not just from potential learners but also their employers and sponsors who want to see training and education programmes which allow greater flexibility in time, place, and cost. These aims resonate with those of many mobile learning programmes where the learner is expected to undertake a programme of learning or upgrade their knowledge and skills in order to improve personal and organisational performance. The conference provided a good opportunity to engage with other academics, educators and training professionals facing the challenge of providing innovative learning opportunities to wider and more diverse audiences. Mr MacLean also presented a paper authored by himself and Dr. Sastry1
3. Key points
A recurring point was that, globally, institutions are having to change their practices to cope with the challenges posed by trying to provide young adults with the individualised and flexible programmes of learning they demand. It is not enough for institutions and organisations to solely focus on the provision of flexible programmes ‐ a new paradigm for learning may be needed. This was partially reflected in the many discussions about and arguments for supporting interdisciplinary learning, multi‐skilling, and the development of critical thinking and problem solving skills for coping with rapidly changing situations and uncertain futures. Technology could prove part of the solution especially in providing facilities for synchronous and asynchronous collaborative working/learning activities spanning different regions and time zones. The implications of such solutions are that more research is needed on learning in multicultural environments and for staff development in this area and using technology in teaching.
4. Conclusion
1 MacLean, P., & Sastry, V. V. S. S. (2012). Assuring Quality in Flexible Delivery. In B. Rientes, P. Daly, S. Reeb‐Gruber, K. Reid, & P. Van den Bossche (Eds.), Proceedings of the 19th EDINEB Conference The Role of Business Education in a Chaotic Worl,. 2‐4 May, 2012, Haarlem, The Netherlands, Haarlem: FEBA ERD Press.
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The conference provided an excellent opportunity to gain insights into current educational thinking and practice in a rapidly changing world. We were also able to receive feedback on the paper presented which deals with the issues of providing high quality post‐graduate defence education to sector professionals studying in India through the use of technology. What was most apparent was that the authors’ institution is not alone in realising that new and sustainable ways of working have to be embraced in order to continue to meet the increasing global demand for flexible education; skilful exploitation of technology and principled approaches to teaching and learning will be key in doing this.
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Appendix E: The SRL‐SRS
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Appendix F: Workshop format and Product Reaction Cards
1. Welcome. Purpose of workshop.
2. Ethics: Recording, anonymity, confidentiality, data access & storage, data use in reports,
respect confidentiality of others in the room.
3. Format of session: Card sorting exercise followed by a discussion.
4. Introduce cards. In a moment, I am going to give each of you a deck of cards. On each
card is a word, if you are not sure what the word means, you will find alternatives on
the back of the card). I would like you to look through all of the cards and sort them into
two piles – those words you feel relevant to the training you have just completed and
the other pile for those you feel are not relevant.
5. Take the ‘Relevant’ cards and have another sort through. This time you need to select
your Top Five. Each person to write their Top Five on flip chart for discussion with the
group.
6. Discussion.
7. Thanks and End of session.
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Product Reaction Cards The following words (printed on separate cards) will be given to workshop participants for them to select those they felt relevant to their training. A discussion will follow this exercise, using their chosen words as a framework.
Each card will also show the synonyms for the relevant word in order to aid understanding.
The original set of 118 words has been reduced to 80. Unused words have been struck through and
are shown on a grey background. The balance of approximately 60% positive and 40% negative
words has been maintained. Positive words are shown on a green background and negative on light
red.
Accessible Disconnected Impressive Reliable
Advanced Disruptive Incomprehensible Responsive
Annoying Distracting Inconsistent Rigid
Appealing Dull Ineffective Satisfying
Approachable Easy to use Innovative Secure
Attractive Effective Inspiring Simplistic
Boring Efficient Integrated Slow
Business-like Effortless Intimidating Sophisticated
Busy Empowering Intuitive Stable
Calm Energetic Inviting Sterile
Clean Engaging Irrelevant Stimulating
Clear Entertaining Low Maintenance Straight Forward
Collaborative Enthusiastic Meaningful Stressful
Comfortable Essential Motivating Time-consuming
Compatible Exceptional Not Secure Time-Saving
Compelling Exciting Not Valuable Too Technical
Complex Expected Novel Trustworthy
Comprehensive Familiar Old Unapproachable
Confident Fast Optimistic Unattractive
Confusing Flexible Ordinary Uncontrollable
Connected Fragile Organized Unconventional
Consistent Fresh Overbearing Understandable
Controllable Friendly Overwhelming Undesirable
Convenient Frustrating Patronizing Unpredictable
Creative Fun Personal Unrefined
Customizable Gets in the way Poor quality Usable
Cutting edge Hard to Use Powerful Useful
Dated Helpful Predictable Valuable
Desirable High quality Professional
Difficult Impersonal Relevant