This is a second release of the Jisc learning analytics service on-boarding guidelines and is targeted at universities and colleges in the UK . We would welcome any feedback sent to setup.analytics@jisc.ac.uk.
These guidelines are aimed at institutions who are interested in implementing the Jisc learning analytics service and are looking to undertake some initial steps to prepare for implementation of the full service, the student app or to gather data in the learning records warehouse.
Most institutions start off with some small pilots as an initial step to implementing learning analytics. This guide is to help you set up an initial pilot.
Ideally institutions should complete all the Steps below but you may already have addressed some. Here are the key documents to get you started.
- To participate in institutional readiness follow Stage 2: Discovery see the Learning analytics discovery toolkit. Download the Jisc Learning Analytics On-boarding Checklist (Microsoft Word)
- If you are ready to start implementing the Jisc learning analytics service see Stage 3 which will provide instructions on contacting Jisc when we will then discuss which stages you should complete to be ready for implementation.
Institutions should maintain their own record of progress using the Jisc Learning Analytics On-boarding Checklist. This can be shared with the Jisc team to show progress and completion of each stage.
Getting started
The links below will take you to specific guidance on completing the steps in each stage. It is not suggested that you need to work on the steps in sequence and to help you the guidance says which steps are a pre-requisites for completion, so you don’t jump too far ahead. You may need to revisit some steps as you progress and learn more about your requirements.
The rating stars in the guidance are an indication of the complexity, effort and time required (for someone with the necessary skills and authority).
Download: Jisc Learning Analytics On-boarding Checklist (Microsoft Word)
Download: Jisc Learning Analytics Readiness Questionnaire (Microsoft Word)
Stage 1: Orientation
1. Sign up to the analytics Jisc mail list
2. Review the analytics blog
3. Attend a Jisc webinar, network meeting or workshop.
Stage 2: Discovery
4. Decide on institutional aims for learning analytics
5. Strategic alignment, senior management approval and you have a nominated project lead
6. Undertake the readiness assessment
7. Arrange a verification meeting with Jisc to discuss the outcomes and possible next steps
8. Start to address readiness recommendations
Stage 3: Culture and Organisation Setup
9. Legal and ethical policy considerations in hand
10. Decision on learning analytics products to pilot
11. Senior management approval and scope of learning analytics project/pilot
12. Jisc order and service agreement signed (if required) and/or contracts with suppliers
Stage 4: Data Integration (Live data)
See the Data Collection Toolkit to help you undertake the steps below
13 Contact Jisc to arrange a kick off meeting to start data integration
14. Undertake a data and systems audit
15. Install and evaluate the VLE data plugin(s) on a test system at your institution
16. Extract student data, transform to UDD and validate.
17. Install VLE (or other activity) data plugin(s) on live system, activate for live data upload to LRW
18. View uploaded LRW data using data explorer to check quality (at his stage a pilot implementation may take place see Stage 5)
Stage 4: Data Integration (Historic data and predictive modelling)
See the Data Collection Toolkit to help you undertake the steps below
19. Extract historical student data, transform to UDD, extract historical VLE (or other activity) data
20. Work with Jisc/supplier to build predictive model
21. View uploaded LRW data using data explorer to check quality
Stage 5. Implementation Roll-Out/Planning
22: Plan the implementation of learning analytics products, including a communication plan
23: Select student groups for the pilot and engage staff/students
22. Configure access to products and understand the analytics data
23. Develop an intervention approach to best support students and develop curriculum
24. Review and evaluate, identify new data collection processes required