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Adding dispositions to create pedagogy-based Learning Analytics

Tempelaar, Dirk; Rienties, Bart and Nguyen, Quan (2017). Adding dispositions to create pedagogy-based Learning Analytics. Zeitschrift für Hochschulentwicklung, 12(1) pp. 15–35.

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URL: http://www.zfhe.at/index.php/zfhe/article/view/993
DOI (Digital Object Identifier) Link: https://doi.org/10.3217/zfhe-12-01/02
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Abstract

This empirical study aims to demonstrate how Dispositional Learning Analytics (DLA) can provide a strong connection between Learning Analytics (LA) and pedagogy. Where LA based models typically do well in predicting course performance or student drop-out, they lack actionable data in order to easily connect model predictions with educational interventions. Using a showcase based on learning processes of 1080 students in a blended introductory quantitative course, we analysed the use of worked-out examples by students. Our method is to combine demographic and trace data from learning-management systems with self-reports of several contemporary social-cognitive theories. Students differ not only in the intensity of using worked-out examples but also in how they positioned that usage in their learning cycle. These differences could be described both in terms of differences measured by LA trace variables and by differences in students’ learning dispositions. We conjecture that using learning dispositions with trace data has significant advantages for understanding student’s learning behaviours. Rather than focusing on low user engagement, lessons learned from LA applications should focus on potential causes of suboptimal learning, such as applying ineffective learning strategies.

Item Type: Journal Item
ISSN: 2219-6994
Academic Unit/School: Learning Teaching and Innovation (LTI) > Institute of Educational Technology (IET)
Learning Teaching and Innovation (LTI)
Item ID: 49056
Depositing User: Bart Rienties
Date Deposited: 11 Apr 2017 14:50
Last Modified: 12 Apr 2017 03:51
URI: http://oro.open.ac.uk/id/eprint/49056
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