Bridging SQL Mastery and Career Confidence for Undergraduate Students Through Simulated Job Interviews

Employers increasingly prioritize candidates who can solve real-world Structured Query Language (SQL) problems, particularly during technical interviews. However, many undergraduate students feel underprepared for these interviews because they have not engaged in the deep learning needed to apply SQ...

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Vydáno v:Journal of information systems education Ročník 36; číslo 4; s. 331 - 341
Hlavní autoři: Zheng, Dailin, Chen, Yu, Albert, Leslie J
Médium: Journal Article
Jazyk:angličtina
Vydáno: West Lafayette EDSIG 01.10.2025
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ISSN:1055-3096, 2574-3872
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Shrnutí:Employers increasingly prioritize candidates who can solve real-world Structured Query Language (SQL) problems, particularly during technical interviews. However, many undergraduate students feel underprepared for these interviews because they have not engaged in the deep learning needed to apply SQL concepts confidently. Additionally, students often fail to recognize the career relevance of SQL skills. This Teaching Tip introduces an immersive SQL lesson designed to bridge the gap between conceptual learning and practical application. The lesson includes a mock SQL technical interview, where students apply their knowledge to solve real-world business problems, class discussions on SQL-related careers, and a post-interview debrief to foster reflection and feedback. Results from pre- and post-lesson surveys indicate significant benefits, including enhanced student confidence in their SQL knowledge, student intention to continue learning and using SQL in the future, and student confidence in their ability to perform well in real SQL interviews. Open-ended survey responses support these findings and further reveal that the SQL lesson positively impacts students by clarifying concepts, reinforcing learned skills, and demonstrating the applicability of SQL in realworld scenarios. This approach demonstrates a practical and scalable framework for integrating immersive professional experiences into technical coursework that may be adapted to different class types (e.g., adopting an abridged version) and different courses (e.g., data analysis).
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ISSN:1055-3096
2574-3872
DOI:10.62273/YPKC5140