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Are satisfied students simply happy people in the first place? The role of trait affect in student satisfaction.

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Title: Are satisfied students simply happy people in the first place? The role of trait affect in student satisfaction.
Authors: T. T. Phua, Florence1 f.phua@reading.ac.uk, H. Dericks, Gerard2, R. Thompson, Edmund3, Enders, Jürgen3
Source: Assessment & Evaluation in Higher Education. May2024, Vol. 49 Issue 3, p302-319. 18p.
Subject Terms: *Student attitudes, *Doctor of philosophy degree, *Universities & colleges, *Data analysis, Organization management
Abstract: We propose and test the proposition that innate personality differences in trait affect explain significant variance in student satisfaction. Using three standard measures of trait affect and data from a student sample (n = 409) of PhD candidates across science, social science and humanities in 63 universities from 20 countries, we find that 24% of variance in student satisfaction is accounted for by trait affect. We also find that both discipline studied and research orientation of university have moderating effects on the relationship between trait affect and student satisfaction. Our findings suggest student satisfaction scores need to be viewed with caution because, in part, they merely reflect individual-level trait affect that - like all innate personality traits - academics, university administrators and education ministers alike are powerless to alter. Our findings indicate that governments, universities and other organisations gathering student satisfaction data could usefully adopt measures to control for trait affect. Our findings also raise the possibility that universities might strategically incorporate innate affect in their student selection criteria to game satisfaction ratings. [ABSTRACT FROM AUTHOR]
Copyright of Assessment & Evaluation in Higher Education is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: <searchLink fieldCode="JN" term="%22Assessment+%26+Evaluation+in+Higher+Education%22">Assessment & Evaluation in Higher Education</searchLink>. May2024, Vol. 49 Issue 3, p302-319. 18p.
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  Data: We propose and test the proposition that innate personality differences in trait affect explain significant variance in student satisfaction. Using three standard measures of trait affect and data from a student sample (n = 409) of PhD candidates across science, social science and humanities in 63 universities from 20 countries, we find that 24% of variance in student satisfaction is accounted for by trait affect. We also find that both discipline studied and research orientation of university have moderating effects on the relationship between trait affect and student satisfaction. Our findings suggest student satisfaction scores need to be viewed with caution because, in part, they merely reflect individual-level trait affect that - like all innate personality traits - academics, university administrators and education ministers alike are powerless to alter. Our findings indicate that governments, universities and other organisations gathering student satisfaction data could usefully adopt measures to control for trait affect. Our findings also raise the possibility that universities might strategically incorporate innate affect in their student selection criteria to game satisfaction ratings. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Assessment & Evaluation in Higher Education is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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              Text: May2024
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