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A large-scale implementation of Predictive Learning Analytics in Higher Education: the teachers' role and perspective

Herodotou, Christothea; Rienties, Bart; Boroowa, Avinash; Zdrahal, Zdenek and Hlosta, Martin (2019). A large-scale implementation of Predictive Learning Analytics in Higher Education: the teachers' role and perspective. Educational Technology Research and Development, 67(5) pp. 1273–1306.

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By collecting longitudinal learner and learning data from a range of resources, Predictive Learning Analytics (PLA) are used to identify learners who may not complete a course, typically described as being at risk. Mixed effects are observed as to how teachers perceive, use, and interpret PLA data, necessitating further research in this direction. The aim of this study is to evaluate whether providing teachers in a distance learning higher education institution with PLA data predicts students’ performance and empowers teachers to identify and assist students at risk. Using principles of Technology Acceptance and Academic Resistance models, a university-wide, multi- methods study with 59 teachers, nine courses, and 1,325 students revealed that teachers can positively affect students' performance when engaged with PLA. Follow- up semi-structured interviews illuminated teachers' actual uses of the predictive data and revealed its impact on teaching practices and intervention strategies to support students at risk.

Item Type: Journal Item
Copyright Holders: 2019 The Authors
ISSN: 1556-6501
Keywords: predictive learning analytics; teachers; student performance; student retention; higher education
Academic Unit/School: Institute of Educational Technology (IET)
Other Departments > Business Development Unit
Other Departments
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Item ID: 62191
Depositing User: Martin Hlosta
Date Deposited: 08 Jul 2019 08:12
Last Modified: 13 Dec 2019 11:20
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