Implementing a Learning Analytics Intervention and Evaluation Framework: what works?

Rienties, Bart; Cross, Simon and Zdrahal, Zdenek (2016). Implementing a Learning Analytics Intervention and Evaluation Framework: what works? In: Kei Daniel, Ben and Butson, Russell eds. Big Data and Learning Analytics in Higher Education: Current Theory and Practice. Heidelberg: Springer, pp. 147–166.

DOI: https://doi.org/10.1007/978-3-319-06520-5_10

URL: https://www.springer.com/gp/book/9783319065199

Abstract

Substantial progress in learning analytics research has been made in recent years to predict which groups of learners are at-risk. In this chapter we argue that the largest challenge for learning analytics research and practice still lies ahead of us: using learning analytics modelling, which types of interventions have a positive impact on learners’ Attitudes, Behaviour and Cognition (ABC). Two embedded case-studies in social science and science are discussed, whereby notions of evidence-based research are illustrated by scenarios (quasi-experimental, A/B-testing, RCT) to evaluate the impact of interventions. Finally, we discuss how a Learning Analytics Intervention and Evaluation Framework (LA-IEF) is currently being implemented at the Open University UK using principles of design-based research and evidence-based research.