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UvAinform project presentation
- 1. UvAinform Stefan Mol Alan Berg Jan 29th 2014
- 2. UvAInform: Past, Present, and Future •From “Bottom-Up” tender procedure (more = less) •Dilution of funds, disconnected pilot projects •Lack of strategic vision (trial and error) •To “Top-Down” project (less = more) •1/3 of budget devoted to ‘lasting’ central infrastructure •Limited number of goal directed pilot projects •Need for a vision •Parallels?
- 3. Blackboard / ELO Blackboard Moocs Grassroots UvAInform Pilots Digital testing Open Online Education SIS
- 4. FOCUS GROUP Learning Analytics framework SECURITY ETHICS BOARD UvAInform Pilot A UvAInform Pilot z COACH FACTS Learning Record Store Service A Activity Service X Video UvAInform Year 1 Prediction framework + Fact generations LMS next gen BasicLTI tools OAAI Blackboard Analytics Course Signals Caliper Warehouse Research Services SIS
- 5. Learning Record Store as part of an analytics framework FOCUS GROUP SECURITY GUIDELINES Mobile MOOC? ETHICS BOARD MijnUvA Video OpenAPI Thin adaption service BasicLTI tools Inter organizational Research community Cloud service LRS Rosters Non TinCAN API Services UvAInform Pilots VU Service UvACommunities BlackBoard http://tincanapi.com/adopters/ Including BlackBoard, Sakai CLE, Apereo OAE QuestionMark. Lots more to come Standards = Market penetration Question Mark /Exams Next Generation LMS showcases HvA Service University Z service
- 6. Stage 1: Learning Record Store with Dashboards Learning Record Store •Standards based •Talking with the same machine readable data format •Market share Regional / International We can attach services from departments, VU the HvA through the LRS. Avoiding duplication, leveraging investment, sharing experience, increasing quality by cross validation. •Compatible with other a number of validated frameworks •Eliminates much of the data cleaning •Secure Repository Validation across services DashBoards If we speak the same language, we can consistently validate services •Experiment with interventions •Experiment with benchmarking validation •Start of process of growing regional services •Breaking down silos •Forces ethics committee other processes •Fuller overview Services for researchers We can now provided a wide range of consistent data practices for researchers
- 7. Responsibilities of the Focus group • • • • • • • • Vision Avoid duplication of effort Guidelines Communication channel with the VU and HvA, Surf, Internationally Starter engine for ethics board Source of advice for Learning Analytics (related) projects Market research Matchmaking
- 8. Something to take away • Without an LRS we are stuck with data silo’s, dirty data, no clear strategy to work together • Standards decouple components in the infrastructure • Standards support validation across services • Standards and guidelines are mutually supportive • Researcher friendly • Lets look towards a uniform set of guidelines for products services • Lets work with an International community • Let’s look towards data democracy between facilities