Developing Self-regulated Learning in High-school Students: The Role of Learning Analytics
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The document discusses the role of learning analytics in fostering self-regulated learning (SRL) among high school students at Trinity College. It outlines the college's current challenges in implementing Learning Management Systems (LMS) and ways to enhance student engagement and feedback through analytics. The future of education at Trinity College is focused on developing students into self-regulated and lifelong learners while effectively utilizing data for actionable insights.
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?