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Scaffolded, Scrutable Open Learner Model (SOLM) as a Foundation for Personalised e-Textbooks

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Presented at the First Workshop on Intelligent Textbooks (Chicago, IL, US; June 25, 2019)

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Scaffolded, Scrutable Open Learner Model (SOLM) as a Foundation for Personalised e-Textbooks

  1. 1. Scaffolded, Scrutable Open Learner Model (SOLM) as a Foundation for Personalised e-Textbooks Judy Kay and Bob Kummerfeld Human Centred technology Sydney University hct:.human-centred technology
  2. 2. E-textbook centric view
  3. 3. The actual situation Canvas Peerwise Colab edTrello Slack ... Student Evidence from student e-text as one source of evidence about learner
  4. 4. Case Study: Top level of HILDA model – Knowledge components for Human-in-the-loop Data Analytics (HILDA) – Big picture and HILDA links – Ethics, privacy, anonymisation, provenance, security and access control – Problem formulation and stakeholder analysis – Data: Raw and Inferred, cleaned and transformed data – Model building – Interfaces and tools for exploration and interpretation – Interfaces for reporting and decision making – Managing data and models, literate programming, collaborative HILDA – Engagement – Group work – Self-regulated learning and meta-cognition
  5. 5. What might the learner model look like? Self-monitoring: • Am I meeting my personal goals? • Am I meeting the teacher’s goals for a bare pass? • And for a high grade? • How do I compare with other students in my class? (needs other students’ data) Reflection • What is the trend in my performance this semester? Planning • What is the priority for me to do next?
  6. 6. Overview example from C course MOOC Black = “Known” White = “Unknown” Cook, R., Kay, J., & Kummerfeld,B. (2015). MOOClm: user modelling for MOOCs. In International Conferenceon User Modeling, Adaptation, and Personalization (pp. 80-91). Springer..
  7. 7. Student progress against teacher’s ideal model for Week 4 Compared with things the teacher expects students to know by Week 4: Black = Alice meets targets Green = Alice is ahead Yellow = Alice is behind White = Alice has not mastered this. Teacher did not expect students to know it at Week 4 either.
  8. 8. Adding scrutability
  9. 9. Forms of evidence Map learning objectives to: Learning Objects used: Components of the course designed to teach eg lectures, Assessments: Testing achievement in learning objectives eg. self-test MCQ, summative quiz, auto-graded assignment … Data from these provide evidence of learning
  10. 10. Viewing Evidence Description of model component Student can see exactly what activity was recorded for them - playing video indicates “familiarity” level of knowledge Student can make manual corrections. eg. Tell Model this item is KNOWN Also links to the relevant videos & exercises … to support learning!
  11. 11. Image included with the permission of the author from the following paper: Guerra-Hollstein, J., Barria-Pineda, J., Schunn, C.D., Bull, S., Brusilovsky, P.: Fine-grained open learner models: complexity versus support. In: Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization. pp. 41–49. ACM (2017)
  12. 12. Scaffolding for the student Overview and details on demand for learning progress monitoring Selection of standards for comparison Allowing the student to add their own evidence
  13. 13. What scaffolding do teachers need? • Defining the learner model • Linking the learner model to the available evidence • Providing standards for the pl
  14. 14. Reflection scaffolding
  15. 15. Why Runestone – wishlist of e-textbook Authoring • Bibliographic data management • Good support for co-authorship, versioning • Supports embedded code that can be run • Self-test exercises Students • All the affordances of paper textbooks • Single place with all materials and searchable for content with links to external content • See progress: mark as mastered for text only, completed with tests • Mark up for self: highlight, bookmarks, add notes • Communication: annotate problematic parts, connect with other students who are reading current material Modelling learning • Supports tagging on content with Knowledge Components and level • Learning analytics data can be customised
  16. 16. Key take-aways • Independent OLM that gives learner ownership of their own data • Integrates data from e-book and other learning data • Scaffolding the student • Scaffolding the teacher • Scrutability • Standards for self-monitoring

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