Developing Self-regulated Learning in High-school Students: The Role of Learning Analytics
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Slides from our workshop at 2018 Australian Learning Analytics Summer Institute (ALASI'18) at Monash University, Melbourne, VIC on Nov 24, 2018.
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Developing Self-regulated Learning in High-school Students: The Role of Learning Analytics
- 1. Developing self-regulated learning in high-school students: The role of learning analytics Vitomir Kovanovic, Srecko Joksimovic The Centre for Change and Complexity in Learning (C3L) University of South Australia Wayne Jaeschke Trinity College
- 2. Outline ▰ Trinity College Context & current SRL development ▰ Future of Learning at Trinity College ▰ The Role of Learning Analytics in SRL development ▰ LA and the Attainment of Graduate Qualities ▰ Workshop Activity- LA and SRL 2
- 3. Trinity College by School School # Students #Teachers ICSEA Blakeview 639 44 1030 Gawler River 758 55 1024 North 838 63 1052 South 835 62 1052 Senior 619 54 Total 3689 278 1041 https://www.youtube.com/watch?time_continue=1&v=U2BxrNV60xk 3
- 5. Trinity College ATAR Performance 5
- 6. Trinity College - University & VET Pathways 6 ▰ ~300 Year 12 graduates each year ▰ 70% University applicants
- 7. Trinity College - Graduate Performance at University (Challenge #1) 7 ▰ University of South Australia Report (September 2016) ▰ Old Scholar Survey Results (3 years post graduation)
- 8. Trinity College - Implementation of LMS 8 ▰ Implementation of LMS (Schoolbox) at Senior School in 2017 ▰ Implementation across middle schools in 2018 (Year 10 only year level with devices)
- 9. Trinity College - Digitisation of Current Practices & Drowning in Data (Challenge #2) 9 ▰ The Feedback imperative ▰ Staff workload associated with digitisation of existing practices- ‘Effort’ rubric ▻ 12 indicators * 27 students per class * 11 classes * 8 reporting periods per year = 28,512 rubric clicks
- 10. Trinity College - The ‘Effort’ Rubric 10 Challenges 1 Managing challenges 2 Sharing work Communication 3 Active Listening 4 Learning conversations 5 Questioning Feedback 6 Utilising feedback Learning from Mistakes 7 Managing mistakes 8 Self-reflection Organisation 9 Completion of assessment tasks and homework 10 Punctuality and preparedness Strategies for Learning 11 Collaboration 12 Perseverance
- 11. The Future of Education - Influences 11 ▰ Melbourne Declaration ▰ Through Growth to Achievement - Gonski ▰ OECD Education 2030
- 12. The Future of Education - Trinity College Learning Outcomes 12 ▰ Students who are self-regulated & lifelong learners ▰ Students who demonstrate attainment of the general capabilities
- 13. The Future of Education - Trinity College Common Intent & Transformation of Education 13 ▰ Trinity Institute (Launch January 2019) ▰ Trinity College Graduate Qualities ▰ General Capabilities embedded in learning activities ▰ Problem and Project Based Learning ▰ LMS & LA to provide appropriate, timely and actionable feedback to all stakeholders
- 14. LA and the Attainment of GQ at Trinity College 14 ▰ What aspects of the current reporting and feedback process are valuable and should be maintained? ▰ What indicators of student learning and behaviour could be passively generated from LMS data? ▰ What aspects of the current processes seem to be redundant or of little value and should be discarded or adjusted? ▰ How can the large volume of data be refined into feedback that is timely and actionable for students, teachers, managers and parents? ▰ What assessments and student activities can be adjusted to generate meaningful data?
- 15. What can analytics be used for? ▰ What students are at risk? ▻ What are the indicators of risk? ▻ What trends we see with at-risk students? ▰ What students engage with? ▰ Which interventions are most effective? 15
- 16. What we can measure with analytics? ▰ How active are the students? ▻ When they log to the system? ▻ How frequently? ▰ What resources are accessing? ▻ Frequency of access? ▻ Timing of access? ▻ Amount of access? ▰ Do students engage with feedback? ▻ Do they read it ▻ Do they act on it? 16
- 17. Self-regulated learning (SRL) ▰ Ed Psychology theory of how students learn and adjust they approach to learning ▻ Students are agents ▻ Students adjust they learning approach ▻ Often not so well ▻ Often stuck to the same approach 17
- 19. 19 COPES model 1. Conditions 2. Operations 3. Products 4. Evaluations 5. Standards
- 20. How is SRL assessed? 20 ▰ Think-aloud protocols ▰ Self-reports ▻ MSLQ: Motivated Strategies for Learning Questionnaire ▰ LMS trace data ▰ Multimodal data capture ▻ Cameras & Facial recognition tools ▻ Microphones & NLP techniques ▻ RFID tags (Social network analysis)
- 21. MSLQ (Motivated Strategies for Learning Questionnaire) components 21 ▰ Motivation ▻ Intrinsic goal orientation ▻ Extrinsic goal orientation ▻ Task value ▰ Expectancy ▻ Control beliefs ▻ Self-efficacy beliefs ▰ Affect & Anxiety ▰ Cognitive & Metacognitive Strategies ▻ Rehearsal ▻ Elaboration ▻ Organization ▻ Critical Thinking ▻ Metacognitive Self-Regulation ▰ Resource Management Strategies ▻ Time and Study Environment ▻ Effort Regulation ▻ Peer Learning ▻ Help Seeking
- 22. MSLQ challenges 22 ▰ Research instrument ▰ Too long: 81 items (some shorter alternatives available) ▰ Can’t be used continuously ▰ Reliability ▻ Only 27% correlation between self-reports & trace data
- 23. Learning Analytics for SRL 23 Pros ▰ Automated capturing ▰ Continuous monitoring Cons ▰ Cannot capture all SRL processes ▻ Goal of learning design ▰ Too much context dependent ▻ Need for robust measures
- 24. Learning Analytics for SRL 24 ▰ Need for standardized measures ▻ Different stakeholders ▻ Different course contexts
- 25. Learning Design and Learning Analytics ▰ Learning activities must be created with analytics in mind ▻ What processes activities should promote? ▻ What data will be collected? ▰ Data capturing should not drive learning design ▻ Should be unobtrusive ▻ Simple for end-users 25
- 26. Evidence-centered assessment design ▰ Assessment development method ▻ Student model: What to measure? ▻ Evidence model: How to measure? ▻ Task model: When to measure? 26
- 27. MSLQ (Motivated Strategies for Learning Questionnaire) components 27 ▰ Motivation ▻ Intrinsic goal orientation ▻ Extrinsic goal orientation ▻ Task value ▰ Expectancy ▻ Control beliefs ▻ Self-efficacy beliefs ▰ Affect & Anxiety ▰ Cognitive & Metacognitive Strategies ▻ Rehearsal ▻ Elaboration ▻ Organization ▻ Critical Thinking ▻ Metacognitive Self-Regulation ▰ Resource Management Strategies ▻ Time and Study Environment ▻ Effort Regulation ▻ Peer Learning ▻ Help Seeking
- 28. Approach #1 ▰ Student model: What to measure? ▻ Goal setting & goal orientation ▻ Rehearsal ▻ Elaboration ▻ Organisation ▻ Critical thinking ▻ Time management ▻ Peer learning ▻ Help seeking 28
- 29. Approach #1 ▰ Evidence model: How to measure? ▻ Goal setting: survey ▻ Rehearsal: LMS traces ▻ Elaboration: LMS traces ▻ Organisation: LMS traces ▻ Critical thinking: Text analysis ▻ Time management: Attendance & LMS traces ▻ Peer learning: LMS discussions ▻ Help seeking: LMS discussions 29
- 30. Approach #1 ▰ Task model: When to measure? ▻ Goal setting: survey ▻ Rehearsal: LMS traces ▻ Elaboration: LMS traces ▻ Organisation: LMS traces ▻ Critical thinking: Text analysis ▻ Time management: Attendance & LMS traces ▻ Peer learning: LMS discussions ▻ Help seeking: LMS discussions 30
- 31. LA approach for fostering SRL ▰ Adjusting the design of single/few core course(s) to promote SRL strategies e.g. ▻ Formative LMS quizzes (rehearsal) ▻ Essay outlining activity (organisation) ▻ Creating annotated bibliography (elaboration) ▰ Develop metrics & models to capture SRL strategies ▻ Multiple threshold metrics ▻ IRT-based analytics models ▰ Provide students with feedback based on model output ▻ Capture reflections on provided feedback & suggestions 31
- 32. Issues with the proposed approach ▰ SRL is not course-specific ▰ SRL processes not full captured by LMS data ▰ SRL more fine-grained than what is provided by trace logs ▰ Use of technology primarily to enable data collection ▰ How to affect student motivation & beliefs? ▰ Primary and middle school students do not use LMS extensively 32
- 33. New opportunities ▰ Classroom data-capturing ▻ Multimodal data capturing tools ▻ Video recording ▻ Conversation recording ▻ Digital learning tools (e.g., tablets) 33
- 36. “Group work 36
- 37. What's next? - 3 questions - 3x10 minutes - 7 minutes preparation within the group - 3 minutes public discussion - Each group - Open a Google doc - Have fun... 37
- 38. Workshop Activity - Designing for Feedback 38 ▰ Identify stakeholders and their role in contributing to students’ development of SRL
- 39. Workshop Activity - Designing for Feedback 39 ▰ What insights do the stakeholders need?
- 40. Workshop Activity - Designing for Feedback 40 ▰ How can pertinent data be captured to gain the requisite insights?
- 41. Workshop Activity - Designing for Feedback 41 ▰ How should insights be communicated to each stakeholder?