Understanding Learning Pathways with Curriculum Analytics

A common challenge in managing academic programmes in higher education is the lack of systematic information about learning connections between courses. This information can help programme directors evaluate curriculum practice and the impacts of different learning pathways on student success and employability. Curriculum analytics have shown the potential to enhance the quality of degree programmes by extracting and analysing curriculum interaction data. This helps to understand how and why students take different pathways througout a programme and what the impact might be on student success and employability. However, little research has looked into systematic adoption of curriculum analytics tools in higher education. 

In light of this, we propose a study to investigate opportunities and concerns related to adopting curriculum analytics. In particular, the study intends to explore prominent challenges that programme directors face in managing a complex curriculum setting to meet the needs of a diverse student body, thereby identifying the interests and needs for analytics tools. 

To this end, seven focus groups will be carried out to engage programme directors and teaching staff directly, and a qualitative analysis approach will be adopted to interrogate the collected data. We expect that the findings of the study will inform the design of a larger study that aims to develop and pilot a curriculum analytics tool to improve the inclusiveness of programme curriculum and student learning experience.

Research areas
Data Society
Research team

PI: Dr Yi-Shan Tsai

Diego Rates (doctoral student)

Professor Dragan Gasevic (supervisor)

Key contact
Dr Yi-Shan Tsai
Funding

Principal's Teaching Award Scheme

Dates
-

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