Workplace Learning Ecology of Software Engineers and Implications for Teaching and Learning
To prepare students for the future workforce, it is important to provide them with knowledge and guidance about professional software engineering practices. One critical element of workplace practices is learning on the job. There are few studies of how software engineers learn on the job and little focus within the literature on how this understanding can help train students. In this paper, we present a qualitative interview-based field study of workplace learning among professional software engineers. We conducted in-depth interviews with ten software engineers and analyzed the data using thematic analysis based on the learning ecologies framework. In our findings, we identify and discuss professionals’ motivation and reasons for learning, the different resources they use to learn, the challenges they face in their learning, and their views on the relationship between formal education and on the job learning. We draw implications of the findings for teaching and learning, and future research.
Wed 31 JulDisplayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change
13:00 - 14:20 | Project Management and Student Perceptions in Software Engineering Research Track at Room 2 Chair(s): Ivana Bosnić University of Zagreb, Faculty of Electrical Engineering and Computing | ||
13:00 20mTalk | Workplace Learning Ecology of Software Engineers and Implications for Teaching and Learning Research Track Aditya Johri George Mason University, USA, Aayushi Hingle , Brent Jesiek , Russ Korte , Cory Brozina | ||
13:20 20mTalk | ScrumBoard: A Project Management Tool Purpose-Built for Software Engineering Education Research Track Matthew Minish University of Canterbury, Christchurch, New Zealand, Fabian Gilson University of Canterbury, Matthias Galster University of Canterbury | ||
13:40 20mTalk | Who is that girl? Drawing a portrait of a female student in Software Engineering Research Track | ||
14:00 20mTalk | University Students' Perception and Expectations of Generative AI tools for Software Engineering Research Track |
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