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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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

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The organizational’ s objectives of the CCC division of the Achmea Company
Customer satisfactionAverage call handling time
Sale targets

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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)

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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

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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

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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

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(c) Brain breaker (d) Duel-learning game(a) Brain snack (b) Poll question
Samples of PowerApp’s content

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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

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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

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Results

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The structure of the duel game network between participants

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The pattern of interactions between different teams resulted from playing duel-learning games

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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

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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.

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Ebrahim Rahimi
Twitter: @esk_rahimi
Linkedin:ebrahimrahimi
ResearchGate:Ebrahim_Rahimi2
Slideshare:ebrahim1354
Blog:ebrahimrahimi.wordpress.com