An Evaluation of Impostor Phenomenon in Data Science Students

Lindsay Duncan, Gita Taasoobshirazi (), Ashana Vaudreuil, Jitendra Sai Kota and Sweta Sneha
Additional contact information
Lindsay Duncan: School of Data Science and Analytics, Kennesaw State University, Kennesaw, GA 30144, USA
Gita Taasoobshirazi: School of Data Science and Analytics, Kennesaw State University, Kennesaw, GA 30144, USA
Ashana Vaudreuil: Healthcare Management and Informatics, Kennesaw State University, Kennesaw, GA 30144, USA
Jitendra Sai Kota: School of Data Science and Analytics, Kennesaw State University, Kennesaw, GA 30144, USA
Sweta Sneha: Healthcare Management and Informatics, Kennesaw State University, Kennesaw, GA 30144, USA

IJERPH, 2023, vol. 20, issue 5, 1-13

Abstract: 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.

Keywords: impostor phenomenon; impostor syndrome; data science; gender; motivation; perfectionism (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/1660-4601/20/5/4115/pdf (application/pdf)
https://www.mdpi.com/1660-4601/20/5/4115/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jijerp:v:20:y:2023:i:5:p:4115-:d:1080136

Access Statistics for this article

IJERPH is currently edited by Ms. Jenna Liu

More articles in IJERPH from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().