ALDinHE Conference 2026: our online presentation summarised
- Debbie Holley
- Jun 17
- 3 min read
An amazing conference every year! the 'Association for Learning Developers in Higher Education' summer conference this year had a main theme of 'Adapting, sharing and advocating effective learning development practice to promote student learning' and we presented our recent work thinking about how to make use of Learning Analytics for wider collaborations across teams and disciplines.
Designing with Data:
The Pivotal Role of Learning Developers in Data-Informed Learning Design
Andrew Kitchenham, David Biggins, Debbie Holley
Our talk suggested that Learning Developers play a pivotal role in shaping inclusive and effective student learning experiences across higher education institutions. Institutions are fast adopting learning analytics (LA) and other data-driven technologies, and these offer new opportunities for earlier and more targeted interventions that can support a broader and more diverse student population (Kitchenham et al, 2025).
However, the creation, interpretation and dissemination of data within institutions are often contested, as Scheffel et al (2022) argue, between the institutional (macro) and instructor/learning developer (micro) levels. At a macro level, institutional data practices are frequently driven by external accountability measures, performance metrics, and regulatory requirements (Tate, 2023). At a micro level, educators and learning developers seek to use data to understand the granular realities of student learning, including engagement, transition, belonging, and skills development (Law and Laing, 2020).
These competing priorities can marginalise student-centred interpretations of data and limit the extent to which analytics meaningfully inform learning design (Kitchenham et al, op.cit.). Our presentation argued that learning developers occupy a critical advocacy position within this landscape. Positioned between institutional strategy and everyday learning practice, learning developers can act as advocates for students by interrogating dominant data narratives, foregrounding equity and inclusion, and defining analytics to create pedagogically meaningful insights.
Using illustrative examples from units we lead, namely computer sciences, business and nursing, to compare and contrast the macro and micro perspectives, our session demonstrated how learning developers can use data to identify points of friction in the student journey, co-design responsive learning resources, and advocate for student-centred, ethical, and context-sensitive data practices.
For me, (a data avoider!) one of the most engaging parts of the session was sharing the 'data machine' created by Andrew, which animated and made visual the possible ways in which between data sets could be drawn upon to inform practice.
Example One: the (mythical) nursing unit
Reflecting on the delivery and engagement of the unit this year, my colleague believes that students were more engaged and that the higher attendance rates are responsible for the increase of 5% average mark. She has reached out to Charlie, one of the Learning Developers, in the hope that he may be able to help her collate some data that shows that there is a correlation between attendance and achievement.
Examples from from years two and three added a wider range of data sets to model how data can be accessed to draw upon and inform our pedagogic practices. Contact us for further information or the slides....(Andrew for data sets; David for data analysis and Debbie for pedagogy)
About ALDinHE:
ALDinHE is committed to representing and supporting all those working in the field of Learning Development (LD) in the UK. We aim to cultivate a community of practice, promote discussion and ideas exchange, and further the professional development of our members by offering training opportunities and quality assurance. (click here to find out more )
Some key readings - or contact us - we have a very extensive list!
Kitchenham, A., Holley, D., & Biggins, D. (2025). Unlocking the data dungeons of higher education. In Proceedings of INTED 2025.
Komljenovic, J., Sellar, S., & Birch, K. (2025). Turning universities into data-driven organisations: Seven dimensions of change. Higher Education, 89(5), 1369–1386. Law, N., & Liang, L. (2020). A multilevel framework and method for learning analytics integrated learning design. Journal of Learning Analytics, 7(3), 98–117.
Scheffel, M., Tsai, Y. S., Gašević, D., & Drachsler, H. (2022). Learning analytics policies. In D. Gašević, G. Siemens, & S. Dawson (Eds.), Handbook of learning analytics (pp. 232–240). Society for Learning Analytics Research.
Tate, A. (2023). A nudge for positive behaviours: Digital nudging in higher education. Journal of Learning Development in Higher Education, (28). https://doi.org/10.47408/jldhe.vi28.1026
Comments