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Identifying Talented Software Engineering Students through Data-driven Skill Assessment

2014/11/23 by Jun Lin, Han Yu, Lin, Jun +3
Computer Science · Social Sciences · #Access Control and Trust #FOS: Computer and information sciences #Software Engineering (cs.SE) #Software Engineering Techniques and Practices #Software System Performance and Reliability #cs.SE

paper · pdf · doi:10.48550/arxiv.1411.6197

arxiv created 2014/11/23 · openalex publication_date 2014/11/23 · arxiv updated 2014/11/25 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

For software development companies, one of the most important objectives is to identify and acquire talented software engineers in order to maintain a skilled team that can produce competitive products. Traditional approaches for finding talented young software engineers are mainly through programming contests of various forms which mostly test participants' programming skills. However, successful software engineering in practice requires a wider range of skills from team members including analysis, design, programming, testing, communication, collaboration, and self-management, etc. In this paper, we explore potential ways to identify talented software engineering students in a data-driven manner through an Agile Project Management (APM) platform. Through our proposed HASE online APM tool, we conducted a study involving 21 Scrum teams consisting of over 100 undergraduate software engineering students in multi-week coursework projects in 2014. During this study, students performed over 10,000 ASD activities logged by HASE. We demonstrate the possibility and potentials of this new research direction, and discuss its implications for software engineering education and industry recruitment.

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