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Interest–Major Fit predicts study satisfaction and/or achievement? Comparing different ways of assessment.

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Title: Interest–Major Fit predicts study satisfaction and/or achievement? Comparing different ways of assessment.
Authors: Messerer, Laura Aglaia Sophia (AUTHOR), Merkle, Belinda (AUTHOR), Karst, Karina (AUTHOR), Janke, Stefan (AUTHOR)
Source: Studies in Higher Education. Nov2025, Vol. 50 Issue 11, p2404-2416. 13p.
Subjects: Achievement, Grade point average, Predictive validity, Scientific method, Student well-being, Higher education, Vocational interests
Abstract: Prospective students and higher educational institutions often share the matching goal to ensure an optimal fit between the demands of study programs and the student profile. A strong personal fit is meant to facilitate long-term study satisfaction and optimal performance. However, to truly understand the impact of such a fit, we must first reach a consensus on how to measure the construct. At this point, researchers and higher education practitioners are debating different avenues in this regard: In the past, the fit has often been measured by assessing vocational interests tied to potential occupations that are attainable through a study program (Interest–Vocation Fit). Here, we argue that more specific measures tailored to the respective major (Interest–Major Fit) have more predictive power. We compare the two operationalizations of fit as predictors of performance and study satisfaction in a sample of 455 German university students who participated in a longitudinal survey study. We found that the different measures of personal fit were associated with subsequent university GPA and study satisfaction. Moreover, we found that Interest–Major Fit was more closely associated with these outcome measures compared to Interest–Vocation Fit. We also found that only Interest–Major Fit has incremental predictive power for study satisfaction beyond high school GPA. These findings should be helpful to researchers interested in the intricacies of measuring fit and higher education practitioners aiming to develop diagnostic tools alike. Such tools may in turn assist prospective students in finding the major that caters best to their personal needs and interests. [ABSTRACT FROM AUTHOR]
Copyright of Studies 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.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Interest–Major Fit predicts study satisfaction and/or achievement? Comparing different ways of assessment.
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  Data: <searchLink fieldCode="AR" term="%22Messerer%2C+Laura+Aglaia+Sophia%22">Messerer, Laura Aglaia Sophia</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Merkle%2C+Belinda%22">Merkle, Belinda</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Karst%2C+Karina%22">Karst, Karina</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Janke%2C+Stefan%22">Janke, Stefan</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Studies+in+Higher+Education%22">Studies in Higher Education</searchLink>. Nov2025, Vol. 50 Issue 11, p2404-2416. 13p.
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  Data: <searchLink fieldCode="DE" term="%22Achievement%22">Achievement</searchLink><br /><searchLink fieldCode="DE" term="%22Grade+point+average%22">Grade point average</searchLink><br /><searchLink fieldCode="DE" term="%22Predictive+validity%22">Predictive validity</searchLink><br /><searchLink fieldCode="DE" term="%22Scientific+method%22">Scientific method</searchLink><br /><searchLink fieldCode="DE" term="%22Student+well-being%22">Student well-being</searchLink><br /><searchLink fieldCode="DE" term="%22Higher+education%22">Higher education</searchLink><br /><searchLink fieldCode="DE" term="%22Vocational+interests%22">Vocational interests</searchLink>
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  Data: Prospective students and higher educational institutions often share the matching goal to ensure an optimal fit between the demands of study programs and the student profile. A strong personal fit is meant to facilitate long-term study satisfaction and optimal performance. However, to truly understand the impact of such a fit, we must first reach a consensus on how to measure the construct. At this point, researchers and higher education practitioners are debating different avenues in this regard: In the past, the fit has often been measured by assessing vocational interests tied to potential occupations that are attainable through a study program (Interest–Vocation Fit). Here, we argue that more specific measures tailored to the respective major (Interest–Major Fit) have more predictive power. We compare the two operationalizations of fit as predictors of performance and study satisfaction in a sample of 455 German university students who participated in a longitudinal survey study. We found that the different measures of personal fit were associated with subsequent university GPA and study satisfaction. Moreover, we found that Interest–Major Fit was more closely associated with these outcome measures compared to Interest–Vocation Fit. We also found that only Interest–Major Fit has incremental predictive power for study satisfaction beyond high school GPA. These findings should be helpful to researchers interested in the intricacies of measuring fit and higher education practitioners aiming to develop diagnostic tools alike. Such tools may in turn assist prospective students in finding the major that caters best to their personal needs and interests. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Studies 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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        Value: 10.1080/03075079.2024.2413867
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        Text: English
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      – SubjectFull: Predictive validity
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      – SubjectFull: Student well-being
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              Text: Nov2025
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              Y: 2025
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