Measures of engagement in the first three weeks of higher education predict subsequent activity and attainment in first year undergraduate students:a UK case study


Effective use of learning analytics systems has been purported to confer various benefits to learners in terms of both attainment and retention. There is, however, little agreement on which data are meaningful or useful. Whilst measures of engagement might correlate with outcomes, thereby retrospectively ‘predicting’ them, there are fewer studies which attempt to predict using ‘live’ system data in a face-to-face teaching environment. This study reports an analysis of week by week data from a learning analytics system which monitored 1,602 first year UK undergraduates. Uniquely, although students could view their own data, no formal interventions took place. Results showed that students who obtained the highest end-of-year marks were more likely to be in a higher engagement quintile as early as the first 3–4 weeks, and that early engagement was highly predictive of future engagement. Students who started in a higher engagement quintile, but their engagement decreased, were more likely to have higher marks than those that started in a lower quintile and then increased their engagement. Early measures of engagement are therefore predictive of future behaviour and of future outcomes, a finding which has important implications for universities wishing to improve student outcomes.

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Divisions: College of Business and Social Sciences > School of Social Sciences & Humanities > Centre for Critical Inquiry into Society and Culture (CCISC)
College of Business and Social Sciences > Aston Business School
College of Business and Social Sciences > Aston Business School > Operations & Information Management
College of Business and Social Sciences > School of Social Sciences & Humanities
College of Health & Life Sciences > Clinical and Systems Neuroscience
College of Health & Life Sciences > School of Optometry > Vision, Hearing and Language
Aston University (General)
Additional Information: This is an Accepted Manuscript of an article published by Taylor & Francis Group in Assessment & Evaluation in Higher Education on 27/9/2020, available online at:
Uncontrolled Keywords: Learning analytics,attainment,higher education,student engagement,Education
Publication ISSN: 1469-297X
Last Modified: 16 Jul 2024 07:17
Date Deposited: 07 Sep 2020 12:20
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Related URLs: https://www.tan ... rnalCode=caeh20 (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2021
Published Online Date: 2020-09-27
Accepted Date: 2020-09-05
Authors: Summers, Robert
Higson, Helen (ORCID Profile 0000-0003-3433-2823)
Moores, Elisabeth (ORCID Profile 0000-0003-3997-0832)



Version: Accepted Version

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