Examining the influence of the RIASEC theory within the Holland code on students’ academic performance in their chosen disciplines among the context of higher education

The utilisation of the RIASEC Theory, based on the Holland Code, has gained substantial popularity in the realm of career planning. Nevertheless, only a limited number of studies have explored the potential influence of the six personality types identified in the Realistic-Investigative-Artistic-Social-Enterprising-Conventional Theory (RIASEC Theory) on students’ academic performance in their chosen subjects. In light of the subject suitability recommendations for different personality types provided by the career mapping outlined in the Hong Kong Association of Careers Masters and Careers Guidance Handbook, the present study aimed to investigate whether the six personality types of N = 1104 undergraduate students enrolled in a university in Hong Kong had an impact on their performance in four self-selected disciplines (Supply Chain Management, Applied Computing, Psychology and Culture and Creative Industry). Nevertheless, the present study hypothesises that six distinct personality types in the RIASEC Theory influence students’ performance in their chosen disciplines. Concurrently, an extensive evaluation was conducted employing a Machine Learning approach to identify the personality types that significantly impact students’ selection of academic disciplines However, the findings revealed that the present study did not build a Linear regression model that established a clear association between these six different personality types and academic performance in the chosen disciplines. Nonetheless, employing the Mean Decrease Impurity (MDI) method of Random Forest in Machine Learning, the current study successfully predicted the personality types that were most likely to influence students’ future subject choices. Specifically, the results indicated that the Artistic personality trait exerted the strongest influence on students’ selection of the four subjects. Consequently, the outcomes of this study offer valuable insights for informing future research endeavours pertaining to the application of the RIASEC theory within the field of education.

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Publication Details

Journal
Cogent Education
Published
2024-08-13
DOI
https://doi.org/10.1080/2331186x.2024.2391274
Citations
5
Primary Topic
Higher Education Governance and Development
Type
article
Field-Weighted Citation Impact
11.16
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article

Examining the influence of the RIASEC theory within the Holland code on students’ academic performance in their chosen disciplines among the context of higher education

Ran Wei
5 citations
Cogent Education
Higher Education Governance and Development
11.16
article

Examining the influence of the RIASEC theory within the Holland code on students’ academic performance in their chosen disciplines among the context of higher education

Ran Wei
article en
5 citations

Abstract

The utilisation of the RIASEC Theory, based on the Holland Code, has gained substantial popularity in the realm of career planning. Nevertheless, only a limited number of studies have explored the potential influence of the six personality types identified in the Realistic-Investigative-Artistic-Social-Enterprising-Conventional Theory (RIASEC Theory) on students’ academic performance in their chosen subjects. In light of the subject suitability recommendations for different personality types provided by the career mapping outlined in the Hong Kong Association of Careers Masters and Careers Guidance Handbook, the present study aimed to investigate whether the six personality types of N = 1104 undergraduate students enrolled in a university in Hong Kong had an impact on their performance in four self-selected disciplines (Supply Chain Management, Applied Computing, Psychology and Culture and Creative Industry). Nevertheless, the present study hypothesises that six distinct personality types in the RIASEC Theory influence students’ performance in their chosen disciplines. Concurrently, an extensive evaluation was conducted employing a Machine Learning approach to identify the personality types that significantly impact students’ selection of academic disciplines However, the findings revealed that the present study did not build a Linear regression model that established a clear association between these six different personality types and academic performance in the chosen disciplines. Nonetheless, employing the Mean Decrease Impurity (MDI) method of Random Forest in Machine Learning, the current study successfully predicted the personality types that were most likely to influence students’ future subject choices. Specifically, the results indicated that the Artistic personality trait exerted the strongest influence on students’ selection of the four subjects. Consequently, the outcomes of this study offer valuable insights for informing future research endeavours pertaining to the application of the RIASEC theory within the field of education.

Cogent EducationVol. 11(1)
Hang Seng University of Hong Kong (HK), University of Hong Kong (HK)
Quality Education
Openalex Percentile: Top 2%
Higher Education Governance and Development
11.16
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