1. EdScene Brainstorming Barry, Shakeel, Andy, Hugh

2. Acquisition of educational artifacts and the domain Interviewing domain experts Analyzing domain documents Identifying key concepts and relationships Identifying policies and rules Documenting scenarios Documenting best practice

3. Scenario - Navigation of the ECS pedagogy artifacts Using Bloom’s taxonomy

4. Scenario - Teaching load allocation management A teacher leaves, Allocate unassigned module to existing teachers, Match-making of module specification and teacher’s profile, Keep teaching load balanced (target teaching hours set by HoS) New teachers’ fitting into the system People like to keep the same modules as last year Requirement in general –Provide high-level view of existing teaching load allocation status –Suggest allocation on new modules

5. Scenario – Reusing student learning outcome Linking learning outcomes at different granularities. –Module level – subject related skills –Programme level – more generic objectives Rating students learning outcomes –F, 3, 2.2, 2.1, 1 Rating table at student-record –At different granularities –Can be exported into different format –To fit in CV and Homepage –Linked back to student-record (public or restraint access)

6. Scenario - Programme/Module Specification Validation Minor changesMajor changes Module specification programme leadercourse sub committee Programme specification course sub committee University committee What is Major change? change of 25% of the syllabus or over Module level - change of learning outcome mappings at programme level Programme level - change of learning outcomes Auto assigning various roles? (quality control?)

7. Scenario - Training course selection Two-fold (for student and teachers) Appraisal – training courses Student career inspiration –Programme and optional modules –Non assessed such as career service related

8. Scenario - Learning progress monitoring Statistical analysis of the learning outcome –diagrams of the student module outcome –Suggestion of low-profile learning outcomes Helping student selecting right optional courses Star-rating module outcomes for a student and guiding the student for improving performance –Diagnose –Advise remedy and things to avoid Tracking marks! –Predicting final results

9. Ontology Modeling

10. Priority Management Purpose –Inspecting large amount of data/semantic statements –Providing interesting examples Ranking criteria –Time Timestamp of the statements Recent (important) v.s. old (irrelevant) –Popularity Most visited User ratings Deployment –Through services

11. Technologies Free text tagging v.s. ontology based annotation –Tagging: flexible, informal, any text –SA: tagging using controlled vocabulary (ontology), therefore fit in the Semantic Web framework for reuse and reasoning –Both optional but value added –Transmittable (controlled by Knowledge Engineers) Web 2.0 –Browser based with enhanced accessibility –Component Widgets –Distributed and always on –Unlocking data for mash-up SOA –Service v.s. Application Improved interoperability Dedicated and reliable functionality Better reusability