Towards data-driven software engineering skills assessment

被引:0
|
作者
Lin J. [1 ,5 ]
Yu H. [2 ]
Pan Z. [3 ]
Shen Z. [2 ]
Cui L. [4 ]
机构
[1] The Joint NTU-UBC Research Centre of Excellence in Active Living for the Elderly (LILY), Nanyang Technological University
[2] School of Computer Science and Engineering, Nanyang Technological University (NTU)
[3] Interdisciplinary Graduate School, Nanyang Technological University (NTU)
[4] School of Computer Science and Technology, Shandong University
基金
新加坡国家研究基金会;
关键词
Agile software engineering; Crowd-sourced design and engineering; Task-oriented crowdsourcing; Tools and platforms to support crowd science and engineering;
D O I
10.1108/IJCS-07-2018-0014
中图分类号
学科分类号
摘要
Purpose: Today’s 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’ soft skill development. The purpose of this paper is to explore alternative ways for assessing software engineering students’ skills through a data-driven approach. Design/methodology/approach: In this paper, the exploratory data analysis approach is adopted. Leveraging the proposed online agile project management tool – 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. Findings: 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’ skill development, and take a proactive approach in helping them improve their programming and soft skills. Originality/value: To the best of the authors’ knowledge, there has yet to be published previous studies using software engineering activity data to assess software engineers’ skills. © 2018, Jun Lin, Han Yu, Zhengxiang Pan, Zhiqi Shen and Lizhen Cui.
引用
收藏
页码:123 / 135
页数:12
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