ATTENDEES

We are currently working with a third party company who implement data science solutions so it would be helpful for them to lead one of the sessions to give ideas on the types of visualisation can be achieved with the application of analytics. It is likely that they will be providing the visualisation platform but will most likely need to be supplied with the data to populate this through a proxy data source (IT / IS involvement is mentioned below).

Curriculum Managers who are key decision makers on implementing new technology/pedagogy. Some lecturing staff from two or three curriculum areas. Their perspective on which types of analytics would be helpful to analyse course design / outcomes will be important.

Digital Services team should have one IT and one Information Systems staff member attending. It is vital that these staff members are involved at this early stage as they will be facilitating any changes necessary to implement the project. There is some cross over to student records from Information systems so it would be helpful to involve them at the earliest possible stage. Student Records staff are well versed on the nature of data stored in the institution so may provide a valuable perspective when ideas are suggested.

Representatives of the student body: Some of our more active class representatives should be invited to give their perspective on what information would help them and how it would be presented. Our third party data science provider may give examples for the students to consider.

I would also invite along our Data Protection Officer to speak briefly on the implications of data use / profiling, consent and the like.

WORKSHOP

I would aim to keep the number of attendees quite low initially but draw from several areas of expertise. The initial workshop day should be a foundation / idea factory for the larger project. The goal of the workshop would be to produce a short roadmap defining the aims, roles and responsibilities, an idea of what may need to change to make the project work and an evaluation plan.

SCHEDULE

10am – Introduction from Principal

10.15 – introduction to learning analytics from Data Science partner: This early presentation is placed to allow attendees to see real world uses of analytics and think of how they could benefit from their use.

11am – Breakout session (each group considers how they could benefit). Teas / Coffee served during the session

12.15 – Feedback session before lunch. Ideas gathered

12.30 – 1.30 Lunch / Networking opportunities

1.30 – 1.45 Data Protection Officer talks about legal / ethical implications

1.45 – 2.30 Road map workshop

2.30 – 2.45 Breaktime

2.45 – 3.30 Q+A for DPO / Data Scientists / Student Records / IT / Information Systems

3.30 – 4 Roundup session with summaries from flip charts