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Making good suggestions in analytics-based early alert systems

Making good suggestions in analytics-based early alert systems The purpose of this paper is to answer the following questions: On which early alert system suggestions are students more likely to act? What factors drive students’ decisions to act on early alert system recommendations?Design/methodology/approachThis study examined whether students’ behaviour changed after receiving the results of an early alert system (CDR). In the middle of a semester, 423 students with varying levels of English proficiency were invited to try the CDR and complete a questionnaire that asked about their perception of the tool and whether they planned to act on the recommendations they received.FindingsResults suggested that students mainly planned to take the assessment-related recommendations provided through the CDR to improve their assessment performance. Results also suggested that student anxiety and student ability affected the likelihood that students would act on the recommendations.Practical implicationsThese findings provide useful insights for early alert system designers to establish a system that generates useful recommendations for students.Originality/valueThe findings of this study contribute to the development of early alert systems. Designers can now realise what suggestions can be effectively offered to students. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Applied Research in Higher Education Emerald Publishing

Making good suggestions in analytics-based early alert systems

Journal of Applied Research in Higher Education , Volume 12 (1): 15 – Jan 17, 2020

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Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
2050-7003
DOI
10.1108/jarhe-12-2018-0264
Publisher site
See Article on Publisher Site

Abstract

The purpose of this paper is to answer the following questions: On which early alert system suggestions are students more likely to act? What factors drive students’ decisions to act on early alert system recommendations?Design/methodology/approachThis study examined whether students’ behaviour changed after receiving the results of an early alert system (CDR). In the middle of a semester, 423 students with varying levels of English proficiency were invited to try the CDR and complete a questionnaire that asked about their perception of the tool and whether they planned to act on the recommendations they received.FindingsResults suggested that students mainly planned to take the assessment-related recommendations provided through the CDR to improve their assessment performance. Results also suggested that student anxiety and student ability affected the likelihood that students would act on the recommendations.Practical implicationsThese findings provide useful insights for early alert system designers to establish a system that generates useful recommendations for students.Originality/valueThe findings of this study contribute to the development of early alert systems. Designers can now realise what suggestions can be effectively offered to students.

Journal

Journal of Applied Research in Higher EducationEmerald Publishing

Published: Jan 17, 2020

Keywords: Data mining; Learning analytics; Academic writing; Change of behaviours; Early alert systems; University teaching

References