Higher education institutions would like to give students choice in their studies and want as many as possible to be successful. However, In module based qualifications, it is often difficult to establish how each module serves students aiming for a particular study outcome: with modules often linked to many qualifications. Without this information universities can neither fully understand the impact of student choice or give useful advice to students as they decide which modules to study.
We describe an approach that is being developed within The Open University, UK, to understand the impact of student module study choices on progression through qualifications. This session will describe how the data model and this pathway approach can yield valuable insights that were previously not readily accessible. We will show how we can follow the ongoing study of a single cohort from their first module, take a snapshot of an entire undergraduate degree qualification and explore how one qualification is represented in a dataset spanning several years. We will reflect on the approach we have taken, including challenges faced and the impact of this work.
The Open University offers the Open degree, which has a very high level of student choice and is the most popular qualification offered by the institution. The Open degree has thousands of potential pathways and in any given year, Open degree graduates could possibly each have taken a different study path. However, even relatively tightly constrained qualifications with perhaps just one point of choice during each study level, or year, can rapidly diverge into many potential study paths – fragmenting the original cohort. Therefore, understanding the differing rates of completion, success, and continuation as students opt for these many different routes is highly complex yet can provide great insight to qualification and module teams, as well as learning designers as to how effective different pathways are and where interventions or corrections might be required. This pathway approach would be of relevance to colleagues in other institutions as they determine to explore what we could perhaps describe as ‘the health of curriculum’ alongside increasing understanding of the student experience on diverse module pathways towards qualification completion.
Edwards, Chris (2017). Understanding student experience in the age of personalised study. In: ALT Online Winter Conference 2017, 12-13 Dec 2017.
Clow, Doug, Coughlan, Tim, Cross, Simon, Edwards, Chris, Gaved, Mark, Herodotou, Christothea, Nguyen, Quan, Rienties, Bart, Thorne, Sam and Ullmann, Thomas (2019). Scholarly insight Winter 2019: a Data wrangler perspective, Open University UK, Milton Keynes.
Ullmann, Thomas; Lay, Stephanie; Cross, Simon; Edwards, Chris; Gaved, Mark; Jones, Edwina; Hidalgo, Rafael; Evans, Gerald; Lowe, Sue; Calder, Kathleen; Clow, Doug; Coughlan, Tim; Herodotou, Christothea; Mangafa, Chrysoula and Rienties, Bart (2018). Scholarly insight Spring 2018: a Data wrangler perspective. Open University UK, Milton Keynes.
Chris Edwardsjoined 3 years, 6 months ago
Samuel Leatjoined 3 years, 6 months ago
Bijoya Sen Guptajoined 3 years, 7 months ago
Karen Howiejoined 3 years, 7 months ago
Neil J. Davidsonjoined 3 years, 7 months ago
Paul Smythjoined 3 years, 7 months ago
lmcbainjoined 3 years, 7 months ago
Rich Goodmanjoined 3 years, 7 months ago
Dr Julie Vocejoined 3 years, 8 months ago
ALTjoined 3 years, 9 months ago