{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,8]],"date-time":"2025-09-08T06:24:39Z","timestamp":1757312679947},"reference-count":21,"publisher":"Tsinghua University Press","issue":"2","license":[{"start":{"date-parts":[[2018,10,11]],"date-time":"2018-10-11T00:00:00Z","timestamp":1539216000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJCS"],"published-print":{"date-parts":[[2018,11,29]]},"abstract":"<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title>\n<jats:p>Today\u2019s software engineers often work in teams to develop complex software systems. Therefore, successful software engineering in practice require team members to possess not only sound programming skills such as analysis, design, coding and testing but also soft skills such as communication, collaboration and self-management. However, existing examination-based assessments are often inadequate for quantifying students\u2019 soft skill development. The purpose of this paper is to explore alternative ways for assessing software engineering students\u2019 skills through a data-driven approach.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title>\n<jats:p>In this paper, the exploratory data analysis approach is adopted. Leveraging the proposed online agile project management tool \u2013 Human-centred Agile Software Engineering (HASE), a study was conducted involving 21 Scrum teams consisting of over 100 undergraduate software engineering students in multi-week coursework projects in 2014.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Findings<\/jats:title>\n<jats:p>During this study, students performed close to 170,000 software engineering activities logged by HASE. By analysing the collected activity trajectory data set, the authors demonstrate the potential for this new research direction to enable software engineering educators to have a quantifiable way of understanding their students\u2019 skill development, and take a proactive approach in helping them improve their programming and soft skills.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title>\n<jats:p>To the best of the authors\u2019 knowledge, there has yet to be published previous studies using software engineering activity data to assess software engineers\u2019 skills.<\/jats:p>\n<\/jats:sec>","DOI":"10.1108\/ijcs-07-2018-0014","type":"journal-article","created":{"date-parts":[[2018,10,11]],"date-time":"2018-10-11T08:31:06Z","timestamp":1539246666000},"page":"123-135","source":"Crossref","is-referenced-by-count":5,"title":["Towards data-driven software engineering skills 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