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Student feedback to improved retention: using a mixed-methods approach to extend specific feedback to a generalisable concept

Calvert, Carol and Hilliam, Rachel (2018). Student feedback to improved retention: using a mixed-methods approach to extend specific feedback to a generalisable concept. Open Learning: The Journal of Open, Distance and e-learning, 34(1) pp. 103–117.

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DOI (Digital Object Identifier) Link: https://doi.org/10.1080/02680513.2018.1552580
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Abstract

Across the Higher Education (HE) sector student feedback is used to feed into university processes and guide decision making. In this study, data gathered allowed the authors to investigate a hitherto neglected, but important, cohort of successful students – those who succeeded when all the odds were stacked against them. The identified group of students had relatively low predictive probabilities of passing their module, and yet despite all the odds passed. These identified students were interviewed by phone which yielded a much richer data set than is often available from student surveys. The advice they considered to be important to future students included specific guidance to get ahead, to plan and to contact their own academic tutor. Based on this advice an opportunity for future students to have a flexible early start on a specific module was created. A 4% increase in the number of registered students who subsequently started the module was maintained through to module completion.

Item Type: Journal Item
Copyright Holders: 2018 The Open University
ISSN: 1469-9958
Project Funding Details:
Funded Project NameProject IDFunding Body
The OU centre for STEM pedagogy (eSTEeM)Not SetThe Open University (OU)
Keywords: Predictive probabilities; retention; student feedback; qualitative; quantitative; mixed methods
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Mathematics and Statistics
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Item ID: 58116
Depositing User: Rachel Hilliam
Date Deposited: 04 Dec 2018 15:06
Last Modified: 04 Dec 2019 23:12
URI: http://oro.open.ac.uk/id/eprint/58116
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