A collaborative autoethnographic analysis of industry-academia collaboration for software engineering education development
Date
2022-06
Journal Title
Journal ISSN
Volume Title
Publisher
Canadian Engineering Education Association
Abstract
As engineering educators seek to prepare students for future careers, it can be challenging to keep course materials current with industry practices and knowledge. Students also often experience a disconnect between their studies and perceived relevance to future industry roles. This study examines the potential impact of an industry-academia collaboration on the development and improvement of software engineering education while addressing these issues. A collaborative autoethnographic approach is used to concurrently analyze the experiences of both industry and academic participants in the collaboration. Common themes across the collected personal reflections show that varied benefits were experienced by all stakeholders while contributing to an improved student experience.
Description
Keywords
industry-academia, collaboration, course design, software engineering, autoethnography
Citation
Marasco, E., Barcomb, A., Dwomoh, G., Eguia, D., Jaffary, A., Johnson, G., Leonard, L., Shupe, R. (2022). A collaborative autoethnographic analysis of industry-academia collaboration for software engineering education development. Proceedings of the 2022 Canadian Engineering Education Association (CEEA-ACEG22) Conference. Canadian Engineering Education Association.