2. Project Environment Governance and Direction Project Delivery
University
LTC
LTMG
LA Steering Committee
Technical WG
Policy WG
Interventions WG
Evaluation WG
CLIPP
Academic Director
TEL & LA Project Manager
Project Officer
TEL Officer
Academic Services
Corporate Student Systems
Senior Systems Programmer
Students’ Union
Programme Directors
The first is nice in that it talks about learners and the learning environment and optimising these. Learners and their contexts.
The second for me crystallises that idea of actionable insights. We are looking for things to do. We have defined problems (questions) that we want to understand.
Governance and Direction
Project Delivery
Pilot Students 2

3. Background
December 2015 – retention and progression project to support students repeating, trailing and restarting modules led to identification of need for learning analytics
January 2016 – identification of Jisc Effective Learning Analytics Project
March 2016 – meeting between Aston technical staff, Jisc and Blackboard to assess institutional readiness
March 2016 – presentation of Jisc project to Learning Technologies Management Group including representatives from the Students’ Union
April 2016 – data access agreement discussions start
May 2016 – preparatory work for development of server required by Tribal
September 2016 – data access agreement signed
October 2016 – Tribal begin data extraction and cleansing
October / November 2016 – HEFCE Catalyst bid submitted / successful
December 2016 – Blackboard building block installed and data harvesting commenced

4. First Steps Steering Committee Jisc Code of Practice Working Groups
Policy - Jisc Learning Analytics Policy and Student Guide
Technical
Interventions
Evaluation
Staff and Student Consultations
Students’ Union - Survey
Project Website and

5. Two Projects in One Effective Learning Analytics
Pathfinder Institution
Catalyst Call A
Small-scale ‘experimental’ innovation in learning and teaching project

6. Analytics Plus
Enhancing retention and progression of undergraduate students through effective and co-ordinated advancement of institutional learning analytics
Identify full-time undergraduate students who may be at risk of non- progression or withdrawal at the earliest possible opportunity and before exams or assignments have been failed to empower students to take responsibility for their achievements and to enable individual staff to take on the role of change agents through effective, targeted, assertive interventions with students.

7. Definitions of Learning Analytics
The measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs. Siemens, G. (2011). Analytics is the process of developing actionable insights through problem definition and the application of statistical models and analysis against existing and/or simulated future data. Cooper, A (2012) The application of big data techniques such as machine based learning and data mining to help learners and institutions meet their goals. Jisc (2017).
The first is nice in that it talks about learners and the learning environment and optimising these. Learners and their contexts.
The second for me crystallises that idea of actionable insights. We are looking for things to do. We have defined problems (questions) that we want to understand. 7

8. Architecture

9. Data Sources
SITS
Demographics
Attainment
Engagement

10. Outputs Tribal Student Insight staff dashboard
Jisc Study Goal student app

11. Outputs
Jisc Data Explorer staff dashboard

12. Pilot Projects Undergraduate 1st year BSc Human Resource Management
30 students
Piloting Student Insight staff dashboard
Undergraduate 1st year BSc Computer Science with Business
30-40 students
Piloting Student Insight staff dashboard
Undergraduate 1st year BSc Neuroscience
30 students
Piloting Student Insight staff dashboard
Undergraduate 1st year BSc English
35-40 students
Piloting Student Insight staff dashboard
Undergraduate Full Time Course representatives
50 students
Piloting Study Goal student app

13. Next Steps  April / August 2018
Students’ Union engagement
Develop learning analytics / personal tutoring interventions packages in Blackboard and pilot interventions
Pilot Student Insight, Study Goal, Data Explorer
Evaluation of systems, predictions, and interventions
Evaluation of retention?
Requirements specification

14. Lessons Learnt Project Retention or success
Risk of failure or measure of engagement
Predictive analytics?
App, dashboard, or VLE
Institutional
Change agents
Attainment data