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Saima Ritonummi; Valtteri Siitonen; Markus Salo; Henri Pirkkalainen – Journal of Workplace Learning, 2024
Purpose: The purpose of this study is to investigate the barriers that prevent workers in the software industry from experiencing flow in their work. Design/methodology/approach: This study was conducted by using a qualitative critical incident technique-inspired questionnaire. Findings: The findings suggest that workers in the software industry…
Descriptors: Barriers, Computer Software, Computer Science, Attention Control
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Andrew Millam; Christine Bakke – Journal of Information Technology Education: Innovations in Practice, 2024
Aim/Purpose: This paper is part of a multi-case study that aims to test whether generative AI makes an effective coding assistant. Particularly, this work evaluates the ability of two AI chatbots (ChatGPT and Bing Chat) to generate concise computer code, considers ethical issues related to generative AI, and offers suggestions for how to improve…
Descriptors: Coding, Artificial Intelligence, Natural Language Processing, Computer Software
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Georgia M. Kapitsaki – IEEE Transactions on Education, 2024
Contribution: Reporting of students' view on the use of preparatory sprint and virtual meetings, as well as on the workload effort in combination with coding artifacts in a Scrum-variant project-based course. Background: Scrum has been adopted to a large extent in Software Engineering (SE) courses. Relevant aspects have been examined in the…
Descriptors: College Faculty, College Students, Computer Software, Programming