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While learner-centric theories such as self-regulated learning (SRL) seem appropriate to inform the design of e-learning systems aiming at enhancing learner’s control, there have been ...

While learner-centric theories such as self-regulated learning (SRL) seem appropriate to inform the design of e-learning systems aiming at enhancing learner’s control, there have been deficiencies within SRL research when applies within workplace settings. Historically, SRL has been conceptualised and researched from an individual perspective within formal settings with disconnected individuals, resulting in reducing regulating process to the individuals and providing a vague picture of the interaction between self- and co-regulatory learning processes. Recently, there has been increasing attention given to the context in which the regulatory process takes place and the social and emotional processes which are components of it. However, it is still unclear how the individual and social aspects of regulation processes interact and contribute to explain individual and group engagement in real-life learning situations. The purpose of this paper is to propose a theory-informed framework to design e-learning systems aiming at supporting learning regulatory process in work environments and then to analyze the relationship between self- and co-regulatory processes. Accordingly, by following a design-based research methodology, we developed a theory-based framework to inform the design of an e-learning system for a workplace setting. Then we explained the implementation of a prototype built upon this framework. Next, we evaluated and tested the prototype in a pilot group consists of 177 users. Finally, we used the created data logs in this prototype to scrutinize the possible relationship between self- and co-regulatory learning processes performed by these users.

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  • Time index: Refers to the number of days a user accessed PowerApp to do individual-based learning activities and <br /> aims to measure time management aspect of the self-regulatory process followed by the user in using PowerApp. <br /> Diversity of chosen content categories Refers to the number of different content categories a user read or answered during performing individual-based learning activities aims to measure goal setting aspect of the self-regulatory process followed by the user in using PowerApp. <br /> Individual activeness: Refers to the number of individual learning activities accomplished by a user in PowerApp consist of different learning functions (i.e. brain breaker, poll question, and brain snack) and assessing her knowledge by answering brain choices and brain selects. <br /> <br /> Co-regulation metric- PowerApp mainly has capitalized on duel-learning games to support and foster co-regulatory learning process among the users. In order to measure the level of co-regulation performed by a user in PowerApp, first we identified the number of duel-learning games initiated, accepted and continued by a user as an initial index. Then, as during each duel-learning game the user answers to five questions, we multiplied this index by five to calculate the co-regulation metric for the user. <br />
  • Next, we used regression analysis to investigate the impact of self-regulatory factors on co-regulatory factor as the dependent variable. Linear regression estimates the coefficients of the linear equation by involving one or more independent variables that best predict the value of the dependent variable. We used stepwise regression model to determine a significant model. Table 3 shows the results of ordinary least square regression provided by stepwise regression model with co-regulation index as the dependent variable and time management index, individual activeness, diversity of chosen content and working experience as the independent variables. <br />

Eden presentation ver 2 Presentation Transcript

  • 1. 1Challenge the future INVESTIGATING RELATIONSHIP BETWEEN SELF- AND CO- REGULATORY LEARNING PROCESSES IN A WORKPLACE E- LEARNING SYSTEM Ebrahim Rahimi, Sebastiaan Tampinongkol, Mohammad Sedighi, Ser van Nuland, Jan Van den Berg, Wim Veen Presented in EDEN 2014 Conference, Zagreb
  • 2. 2Challenge the future The organizational’ s objectives of the CCC division of the Achmea Company Customer satisfactionAverage call handling time Sale targets
  • 3. 3Challenge the future A Design-Based Research Analysis of Practical Problems by Researchers and Practitioners in Collaboration Development of Solutions Informed by Existing Design Principles and Technological Innovations Evaluation and Testing of Solutions in Practice Documentation and Reflection to Produce " Design principles" Refinement of Problems, Solutions, Methods and Design Principles Four phases of design-based research methodology (Reeves, 2006)
  • 4. 4Challenge the future The slowness of insurance information updating process Information factors Technological factors Human factors Organizational factors Analysis of Practical Problems by Researchers and Practitioners in Collaboration
  • 5. 5Challenge the future Development of Solutions Informed by Existing Design Principles and Technological Innovations Organizaton's objectives Design of the eLearning system -Flexible delivery -Providing choices -Game-based social learning -Bite-size content -Process-based Assessment & Reflection mechanism Principles of adult learning Contextual requirements Theories in use Independence Support Capability
  • 6. 6Challenge the future Learning score visulizer: Total scores for : -Insurance industry -Financial/procedural information -Skills -Organizational culture Categorized content items Very current content item (most score) Medium current content item (Medium score) Almost outdated content item (Minimum score) Start duel-learning gameBrain snack Poll question Brain breaker Duel-learning game Interface of PowerApp
  • 7. 7Challenge the future (c) Brain breaker (d) Duel-learning game(a) Brain snack (b) Poll question Samples of PowerApp’s content
  • 8. 8Challenge the future Evaluation and Testing of Solutions in Practice Research Question: Is there a correlation between self- and co-regulatory learning behaviours of learners in PowerApp? Research Setup/participants: 177 users accessed and used PowerApp within 45 days Research Instrument: Analyzing PowerApp data logs
  • 9. 9Challenge the future Time management Diversity of chosen content categories Individual activeness Metrics to measure self- regulatory learning behaviour (adopted from Barnard, Paton, & Lan, 2008) Initiating a duel-learning game Continuing/canceling a duel-learning game Accepting a duel-learning game invitation Metrics to measure co- regulatory learning behaviour Analyzing PowerApp’s data logs
  • 10. 10Challenge the future Results
  • 11. 11Challenge the future The structure of the duel game network between participants
  • 12. 12Challenge the future The pattern of interactions between different teams resulted from playing duel-learning games
  • 13. 13Challenge the future Variables Statistics Timemanagementindex 10.542 (1.245)∗∗∗ 7.226 (1.517)∗∗∗ 6.857 (1.515)∗∗∗ IndividualActiveness 0.176 (0.049)∗∗∗ 0.129 (0.054)∗∗ Diversityofchosencontent 2.856 (1.413)∗∗ Adjusted 𝑹𝟐 0.285 0.331 0.343 Constant −4.575∗ −4.330∗ −9.467∗∗ F 36.067∗∗∗ 29.996∗∗∗ 22.920∗∗∗ Noofobservations 177 The dependent variable is Co-regulatory factor. Standard errors are reported in parentheses. *, **, *** indicates significance at the 90%, 95%, and 99% level, respectively. The results of Linear regression analysis
  • 14. 14Challenge the future Documentation and Reflection to Produce " Design principles" Design criteria/principles: • Defining more social learning activities and scenarios to improve both individual- and co-regulatory learning process. • Feeding both individual- and social-based learning activities with similar types of content in order to make a close link between these processes. • Allowing the learners to observe other learners learning choices, objectives, and activities. • Supporting motivational aspects of regulation process by introducing more extrinsic( gaming elements ) and intrinsic elements (i.e. curiosity-based learning). • Increasing the usability of e-learning system through generating context-based and relevant content. • Designing and implementing learning analytic module to assist learners to get a clear picture of their learning process and pattern. • Allowing more knowledgeable learners to participate in developing and evaluating content items.
  • 15. 15Challenge the future Ebrahim Rahimi Twitter: @esk_rahimi Linkedin:ebrahimrahimi ResearchGate:Ebrahim_Rahimi2 Slideshare:ebrahim1354 Blog:ebrahimrahimi.wordpress.com