Figure 3.6: The concept cognitive modelling is in focus, and shown at Term Expansion level 1, 2 and 5 (as indicated by the Term Expansion radio buttons on the top of the visualisation). As the expansion level increases, the number of visible related concepts is also shown.
Sheen, K. A., & Luximon, Y. (2017). Student perceptions on future components of electronic textbook design. Journal of Computers in Education, 4(4), 371-393.
Scaffolded, Scrutable Open Learner Model (SOLM) as a Foundation for Personalised e-Textbooks
Scaffolded, Scrutable Open Learner
Model (SOLM) as a Foundation for
Judy Kay and Bob Kummerfeld
Human Centred technology
edTrello Slack ...
Evidence from student
e-text as one source of evidence about learner
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
– Group work
– Self-regulated learning and meta-cognition
What might the learner model look like?
• 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)
• What is the trend in my performance this semester?
• What is the priority for me to do next?
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).
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.
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
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!
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)
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
What scaffolding do teachers need?
• Defining the learner model
• Linking the learner model to the available evidence
• Providing standards for the pl
Why Runestone – wishlist of e-textbook
• Bibliographic data management
• Good support for co-authorship, versioning
• Supports embedded code that can be run
• Self-test exercises
• 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
• Supports tagging on content with Knowledge Components and level
• Learning analytics data can be customised
• 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
• Standards for self-monitoring
Presented at the First Workshop on Intelligent Textbooks (Chicago, IL, US; June 25, 2019)