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.

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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.

Item Type:	Book Section
Copyright Holders:	2016 Springer
ISBN:	3-319-06520-3, 978-3-319-06520-5
Academic Unit/School:	Learning and Teaching Innovation (LTI) > Institute of Educational Technology (IET) Learning and Teaching Innovation (LTI) Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi) Faculty of Science, Technology, Engineering and Mathematics (STEM)
Research Group:	Centre for Research in Computing (CRC)
Item ID:	45023
Depositing User:	Bart Rienties
Date Deposited:	22 Dec 2015 16:52
Last Modified:	11 Dec 2018 17:53
URI:	http://oro.open.ac.uk/id/eprint/45023
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