1. LASER
LEARNING ANALYTICS SOLUTIONS FOR STUDYING AND SUPPORTING
SRL IN BL
05/05/2021
KICK OF MEETING
MAR PÉREZ SANAGUSÍN
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LASER (ANR-20-CE38-0004 )

2. WELCOME!
Let’s know each other and see how to
collaborate through LASER
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3. AGENDA
1. General introduction
2. Overview of the project
3. Current state and plans
4. Open questions and potential collaborations
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4. 1. GENERAL INTRODUCTION
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5. Pontificia Universidad Católica de Chile
PhD in Computer Science and Education
Université Paul Sabatier Toulouse
HDR Computer Science
Isabel Hilliger
Julien Broisin
Université Paul Valéry Montpellier
HDR Psychology
Cornell University
PhD in Education
René Kizilcec
Universidad de Cuenca
PhD in Computer Science and Education
Jorge
Maldonado
André Tricot
https://www.irit.fr/laser/people/
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6. About the call
• 1 PhD student starting september 2021 (Esteban
Villalobos)
• 1 Post-Doc (1,5 years, November 2021)
• 1 undergraduate student for 1,5 years for development
(part-time)
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7. 2. OVERVIEW OF THE PROJECT
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8. About the call
• Funded by the Agence Nationale de Recherche
• ANR JCJC, is a call dedicated to young researchers
• Three projects were accepted in our area
• Around 18% acceptance rate
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9. About project
• Duration: 4 years
• Period: 01 April 2021 – 01 Abpril 2025
• Total funded budget : 253.875 €
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10. Project Objective
To investigate the Self-Regulated Learning
strategies used by learners in Blended Learning
Scenarios and to propose and evaluate a learning
analytics solution to support these strategies.
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11. How does
Students’ SRL
strategies
manifest in SRL?
How do we
measure SRL in
BL?
Are dashboard-
based solutions
useful?
Open Challenges
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12. Instruments and measures for understanding how
SRL manifests and their relationship with learners’
characteristics and performance
SRL ANALYTICAL FRAMEWORK
01
LA dashboard-based solutions for supporting SRL for
both, teachers and students
LEARNING ANALYTICS SOLUTION
02
Blended Learning exemplary scenarios to evaluate
the impact of the LA solution in students’ learning
strategies and teachers’ decision making
EXEMPLARY SCENARIOS
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15. 3. CURRENT STATE AND PLAN
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16. WP1.Analysis: Analytical Framework
• Instruments (First version)
• Data analysis scripts (Not yet defined)
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18. Link OSF (Open Science Framework)
https://osf.io/s86au/?view_only=455371582ac345809e91eb
844f80c5e7
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19. WP1.Analysis: Analytical Framework
Open questions
• How do we measure “sense making” of a dashboard?
• How do we measure the decision making process?
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20. WP2. Design, Development and
Implementation
• Tool NMP: A plugin for Moodle or supporting students’ SRL.
Adapted from a previous project Erasmus + LALA by Jorge
Maldonado-Mahauad
• Pintrich SRL model (underpinning theoretical
educational model behind the design
• Visualizations for students
• Visualizations for teachers
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21. WP2. Design, Development and
Implementation
• Github account for sharing tool (Pending)
• Link to NMP Tool: http://52.47.127.7/
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22. WP3. Evaluation
Research questions to evaluate with the scenarios
• RQ1. How can pre-existing LA methods and techniques be adapted and combined
with qualitative methods to create an analytical framework for characterizing
students’ strategies over time and across learning modes in BL scenarios?
• RQ2. How useful (interpretable, actionable, and comprehensive) are the existing
indicators provided in the NoteMyProgress dashboard for students’ and teacher, and
which new indicators should be designed?
• RQ3. How does the LA dashboard influence students’ SRL strategies and teachers’
decision making in BL scenarios?
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23. WP3. Evaluation – Scenario 1
• Objective: Evaluating students’ and teachers’ perception of
NMP and its usage
• Related research questions: RQ1 (methods); RQ2
(indicators)
• Context:
• “Basics in informatics”, Universidad de Cuenca (Ecuador)
• Around 300 students and 4 teachers
• 5th April – 31st July 2021
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24. WP3. Evaluation – Scenario 1
Hypothesis related with RQ1
• H1.1. Students find the dashboards provided by NMP 2.0 usable according to the SUS measure (SUS)
• H1.2. Students “make sense” some indicators in the NoteMyProgress dashboard useful (interpretable,
actionable and comprehensive)
• H1.3.Teachers find the dashboards provided by NMP 2.0 usable according to the SUS measure (SUS)
• H1.4.Teachers “make sense” of the indicators in the NoteMyProgress dashboard useful (interpretable,
actionable and comprehensive)
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25. WP3. Evaluation – Scenario 1
Hypothesis related with RQ2
• H2.1. Students with higher SRL profiles use more frequently the dashboards provided by NMP tool.
• H2.2. Students with higher SRL profiles make more sense of the information provided through the NMP
Dashboard.
• H2.3.Teachers with higher SRL profiles use more frequently the dashboards provided by NMP.
• H2.4.Teachers with higher SRL profiles make more sense of the information provided through the NMP
Dashboard.
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26. WP3. Evaluation – Scenario I
Expected results: Improvements of NMP and
indicators
Pre-registered Experimental plan:
https://osf.io/dswxb/
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27. WP3. Evaluation – Scenario 2
• Objective: Evaluating the relationship between SRL strategies
and dashboard use
• Related research questions: RQ1 (methods); RQ2
(indicators); RQ3. (impact)
• Context:
• “Data Bases”, Université Paul Sabatier Toulouse (France)
• Around 200 students and 2 teachers
• September– December 2021
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28. WP3. Evaluation – Scenario I
Expected results: Measures for SRL in BL; Impact
of using NMP in a hybrid scenario
Pre-registered Experimental plan: June 2021
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29. 3. OPEN QUESTIONS AND POTENTIAL
COLLABORATORS
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30. Open questions
• Measures for “Sense making”
• How do we measure sense making of a dashboard?
• Approaches for measuring beyond the platform
• How do we move beyond the “click” proxy to
measure SRL behaviors within the clasroom and
beyond?
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31. Potential collaborations
• Budget for travel expenses (if possible…)
• Common project collaborations?
• Periodical meetings?
• LASER list to share?
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32. THANKYOU ALL!
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33. EXTRAS
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