Copy the page URI to the clipboard
Rienties, Bart; Cross, Simon and Zdrahal, Zdenek
(2016).
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.
Viewing alternatives
Item Actions
Export
About
- Item ORO ID
- 45023
- Item Type
- Book Section
- ISBN
- 3-319-06520-3, 978-3-319-06520-5
- Academic Unit or School
-
Institute of Educational Technology (IET)
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)
- Copyright Holders
- © 2016 Springer
- Depositing User
- Bart Rienties