Guidelines for using empirical studies in software engineering education

Author:

Fagerholm Fabian1,Kuhrmann Marco2,Münch Jürgen13

Affiliation:

1. Department of Computer Science, University of Helsinki, Helsinki, Finland

2. Institute for Applied Software Systems Engineering, Clausthal University of Technology, Goslar, Germany

3. Herman Hollerith Center (HHZ), Reutlingen University, Böblingen, Germany

Abstract

Software engineering education is under constant pressure to provide students with industry-relevant knowledge and skills. Educators must address issues beyond exercises and theories that can be directly rehearsed in small settings. Industry training has similar requirements of relevance as companies seek to keep their workforce up to date with technological advances. Real-life software development often deals with large, software-intensive systems and is influenced by the complex effects of teamwork and distributed software development, which are hard to demonstrate in an educational environment. A way to experience such effects and to increase the relevance of software engineering education is to apply empirical studies in teaching. In this paper, we show how different types of empirical studies can be used for educational purposes in software engineering. We give examples illustrating how to utilize empirical studies, discuss challenges, and derive an initial guideline that supports teachers to include empirical studies in software engineering courses. Furthermore, we give examples that show how empirical studies contribute to high-quality learning outcomes, to student motivation, and to the awareness of the advantages of applying software engineering principles. Having awareness, experience, and understanding of the actions required, students are more likely to apply such principles under real-life constraints in their working life.

Funder

Tekes, the Finnish Funding Agency for Technology and Innovation

Publisher

PeerJ

Subject

General Computer Science

Reference65 articles.

1. Exploring machine learning methods to automatically identify students in need of assistance;Ahadi,2015

2. Experiences and results from tailoring and deploying a large process standard in a company;Armbrust;Software Process: Improvement and Practice,2008

3. Classroom experiments;Ball,2012

4. Experimentation in software engineering;Basili;IEEE Transactions on Software Engineering,1986

Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. SQMetrics: An Educational Software Quality Assessment Tool for Java;Knowledge;2023-09-29

2. Evaluating classifiers in SE research: the ECSER pipeline and two replication studies;Empirical Software Engineering;2022-11-08

3. The Covid 19 Pandemic and its Effects on Agile Software Development;2022 The 5th International Conference on Software Engineering and Information Management (ICSIM);2022-01-21

4. Why does the experiment fail with students? An Experience;14th Innovations in Software Engineering Conference (formerly known as India Software Engineering Conference);2021-02-25

5. Formative Assessment Activities to Advance Education: A Case Study;Journal of Information Technology Education: Innovations in Practice;2021

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3