Notepad:DSALT

Data Stewardship & Analytics for Learning & Teaching (DSALT) Working Group (DRAFT)

Focus: Determine existing, potential, and approved access and use to Student and Instructor data for enhancing teaching and learning at TRU, and propose TRU decision-making on access and use processes, governance and policy.

Deliverables: a) Development of principles and the scope they apply to b) Student consent guidelines and sample c) List of data sources and access rules (relevant systems) d) List of relevant polices & policy needing revising e) Guidelines and mechanisms for review for decisions about technology, policy and implementation for access and use of student data. f) A webpage (repository, hub?) for students, faculty, etc…

Scope: • Whose data: Students’ and Instructors’ data • Sources: all sources within TRU and through TRU agreements (including software agreements)

Governance:

1) Teaching and Learning Committee (larger group, informing, providing insight & review, approvals) – monthly report, review & provide feedback, approve pilots and recommendations, receive working group reports and make decisions. Expertise, transferability, credibility and relevance.

2) Data Stewardship & Analytics for Learning & Teaching (DSALT) working group (meet to receive task group reports & decide next steps; recommend to TLC) - Co-chairs (facilitating, timelines, processes): Brian Lamb & Carolyn Hoessler - Task groups (deliverable focused; work between working group meetings; report to working group taskforce; working meetings with minimal tasks; membership based on specific topics such as data warehouse/storage/accessing; student consent policy; reporting and external release). - (Current) Membership: o IT – Hugh Burley (security and privacy) o IPE – need new o Library/Faculty – Amy Paterson o ID/Faculty – Michelle Harrison o Faculty eLearning Coordinator – Brenna Clarke Gray o Dean – Gregory Anderson o Privacy – Laurel Wale o Faculty – Andrew Fergus (SOBE), Sasha Kondrashov (EDSW) o Student – Dipak Parmar o Student – o Indigenous Representative o Faculty of Student Development (Early Alert? Student Affairs?) o Registrar; Enrollment Services o New (or fill-in) IPE Rep

I) TRU Landscape Scan

Question 1: a) What are all possible uses of student and instructor data for enhancing teaching and learning at TRU? b) Which ones should be used at TRU? - Enhance through research on teaching and learning - Enhance through customized feedback and information for students o E.g., quiz answers and branching - Enhance through early alerts & identifying students missing academic milestones o Pamela Fry’s office - Enhance through program review and continuous improvement - Enhance through promotion and recruitment based on evidence o Stats on retention - Enhance through evaluating student participation and performance - Enhance through evaluating instructor engagement and performance (not currently done, possible in the technology system). - Enhance through partnerships and agreements with software or educational experience providers (e.g., integrating a textbook publisher’s software into the LMS where they can access and use student data). - Connections with alumni (data) - Other, please specify…

Question 2: What are all the existing student and Instructor data sources on campus? Storage & who has access? Approved uses? Who externally has access in agreements and what uses?

Question 3: What policies and guidelines already exist for the use of student and Instructor data? Any identified gaps so far?

Question 4: What unwritten guidelines and “we usually do…”?

II) Peer Institution Landscape scan Governance structures Policies

Sample principles and procedures: - https://www.ed.ac.uk/academic-services/policies-regulations/learning-and-assessment/learning-analytics - UBC o Principles: https://learninganalytics.ubc.ca/ethics-policy/learning-analytics-at-ubc-purpose-and-principles/ o Ethics https://learninganalytics.ubc.ca/ethics-policy/ - University of west London https://www.uwl.ac.uk/sites/default/files/Departments/About-us/uwl_learning_analytics_policy_2018_0.pdf - University of Michigan https://ai.umich.edu/learning-analytics-guiding-principles/ - -

Experience of process samples: - https://ammienoot.com/brain-fluff/learning-analytics-policy-development/ - http://education.okfn.org/learning-analytics-policy-development/

III) Identify gaps in the policies