Marasco, EmilyBarcomb, AnnDwomoh, GloriaEguia, DanielJaffary, AbbasJohnson, GarthLeonard, LanceShupe, Ryan2022-06-242022-06-242022-06Marasco, 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.http://hdl.handle.net/1880/114775https://dx.doi.org/10.11575/PRISM/39858As 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.engUnless otherwise indicated, this material is protected by copyright and has been made available with authorization from the copyright owner. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.industry-academiacollaborationcourse designsoftware engineeringautoethnographyconference paper