Abstract
Employers expect engineering graduates to be prepared for their entry-level positions in the rapidly advancing civil engineering industry. Employability, defined as developing capabilities for successful and sustainable career development, can help explain students’ preparedness for the workforce. While prior studies identified various skills needed for employment from the perspective of working professionals, it is unclear if students understand what is required for their careers, how to develop skills through diverse experiences, and who can assist them with their career preparation. To illuminate students’ employability, this study used interviews with 13 civil engineering students and a deductive analytic approach. An employability framework was used as a theoretical lens to explore civil engineering students’ perceptions and experiences of preparing for their careers by using five key elements: professional skills, experience, career development learning, emotional intelligence, and degree-specific knowledge. This study identified three themes that explicated civil engineering students’ development of employability. Our findings indicated (1) students developed career motivation inside and outside the classroom; (2) students participated in school organizations and internships to improve professional skills and emotional intelligence; and (3) students expressed uncertainty about learning professional skills in class. The findings highlight the importance of students’ development of career motivation, participation in out-of-class activities, and the role of educators in facilitating career preparation. These findings imply management and academia can help improve students’ employability by communicating knowledge and skills required in the workforce and bridging the gap between industry expectations and academic preparation.
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Data Availability Statement
Some or all data, models, or code generated or used during the study are confidential in nature (i.e., the names of the interview participants) and may only be provided with restrictions (e.g., anonymized data).
Acknowledgments
The authors gratefully acknowledge the National Science Foundation for supporting this work under Award Nos. 1463802 and 1931371. Any opinions, findings, conclusions, or recommendations expressed here are those of the authors and do not necessarily reflect the views of the National Science Foundation.
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Received: Jun 11, 2021
Accepted: Jan 7, 2022
Published online: Feb 28, 2022
Published in print: Jul 1, 2022
Discussion open until: Jul 28, 2022
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