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An Evaluation of Impostor Phenomenon in Data Science Students
Impostor Phenomenon (IP), also called impostor syndrome, involves feelings of perceived fraudulence, self-doubt, and personal incompetence that persist despite one’s education, experience, and accomplishments. This study is the first to evaluate the presence of IP among data science students and to...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10001774/ https://www.ncbi.nlm.nih.gov/pubmed/36901122 http://dx.doi.org/10.3390/ijerph20054115 |
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author | Duncan, Lindsay Taasoobshirazi, Gita Vaudreuil, Ashana Kota, Jitendra Sai Sneha, Sweta |
author_facet | Duncan, Lindsay Taasoobshirazi, Gita Vaudreuil, Ashana Kota, Jitendra Sai Sneha, Sweta |
author_sort | Duncan, Lindsay |
collection | PubMed |
description | Impostor Phenomenon (IP), also called impostor syndrome, involves feelings of perceived fraudulence, self-doubt, and personal incompetence that persist despite one’s education, experience, and accomplishments. This study is the first to evaluate the presence of IP among data science students and to evaluate several variables linked to IP simultaneously in a single study evaluating data science. In addition, it is the first study to evaluate the extent to which gender identification is linked to IP. We examined: (1) the degree to which IP exists in our sample; (2) how gender identification is linked to IP; (3) whether there are differences in goal orientation, domain identification, perfectionism, self-efficacy, anxiety, personal relevance, expectancy, and value for different levels of IP; and (4) the extent to which goal orientation, domain identification, perfectionism, self-efficacy, anxiety, personal relevance, expectancy, and value predict IP. We found that most students in the sample showed moderate and frequent levels of IP. Moreover, gender identification was positively related to IP for both males and females. Finally, results indicated significant differences in perfectionism, value, self-efficacy, anxiety, and avoidance goals by IP level and that perfectionism, self-efficacy, and anxiety were particularly noteworthy in predicting IP. Implications of our findings for improving IP among data science students are discussed. |
format | Online Article Text |
id | pubmed-10001774 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-100017742023-03-11 An Evaluation of Impostor Phenomenon in Data Science Students Duncan, Lindsay Taasoobshirazi, Gita Vaudreuil, Ashana Kota, Jitendra Sai Sneha, Sweta Int J Environ Res Public Health Article Impostor Phenomenon (IP), also called impostor syndrome, involves feelings of perceived fraudulence, self-doubt, and personal incompetence that persist despite one’s education, experience, and accomplishments. This study is the first to evaluate the presence of IP among data science students and to evaluate several variables linked to IP simultaneously in a single study evaluating data science. In addition, it is the first study to evaluate the extent to which gender identification is linked to IP. We examined: (1) the degree to which IP exists in our sample; (2) how gender identification is linked to IP; (3) whether there are differences in goal orientation, domain identification, perfectionism, self-efficacy, anxiety, personal relevance, expectancy, and value for different levels of IP; and (4) the extent to which goal orientation, domain identification, perfectionism, self-efficacy, anxiety, personal relevance, expectancy, and value predict IP. We found that most students in the sample showed moderate and frequent levels of IP. Moreover, gender identification was positively related to IP for both males and females. Finally, results indicated significant differences in perfectionism, value, self-efficacy, anxiety, and avoidance goals by IP level and that perfectionism, self-efficacy, and anxiety were particularly noteworthy in predicting IP. Implications of our findings for improving IP among data science students are discussed. MDPI 2023-02-25 /pmc/articles/PMC10001774/ /pubmed/36901122 http://dx.doi.org/10.3390/ijerph20054115 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Duncan, Lindsay Taasoobshirazi, Gita Vaudreuil, Ashana Kota, Jitendra Sai Sneha, Sweta An Evaluation of Impostor Phenomenon in Data Science Students |
title | An Evaluation of Impostor Phenomenon in Data Science Students |
title_full | An Evaluation of Impostor Phenomenon in Data Science Students |
title_fullStr | An Evaluation of Impostor Phenomenon in Data Science Students |
title_full_unstemmed | An Evaluation of Impostor Phenomenon in Data Science Students |
title_short | An Evaluation of Impostor Phenomenon in Data Science Students |
title_sort | evaluation of impostor phenomenon in data science students |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10001774/ https://www.ncbi.nlm.nih.gov/pubmed/36901122 http://dx.doi.org/10.3390/ijerph20054115 |
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