As essential facilitators in the process of the formation of future engineers, engineering faculty determine which technologies students learn and adopt during their engineering studies. Faculty members’ ability to accept new and relevant engineering technologies (such as programming languages, software, and instruments) and adopt them in their curriculum directly affects the relevance of engineering graduates’ technical skills. Additionally, by adopting and teaching new and relevant technologies, engineering faculty model life-long technology adoption to their students. This paper summarizes the preliminary results of an NSF project funded through the Directorate for Engineering, Engineering Education and Centers. A main goal of the project is developing an understanding of the factors that support or inhibit engineering faculty technology acceptance. This paper focuses on a portion of the results related to facilitating conditions that support technology adoption that emerged from the qualitative analysis of interview transcripts from engineering faculty at a Midwestern, USA, technologically-focused university. The accompanying poster session will present these findings, as well as provide a deeper understanding of the data related to one facilitating condition – Peers and Mentors.
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Helping Faculty Teach Software Performance Engineering
Over the academic year 2022–23, we discussed the teaching of software performance engineering with more than a dozen faculty across North America and beyond. Our outreach was centered on research-focused faculty with an existing interest in this course material. These discussions revealed an enthusiasm for making software performance engineering a more prominent part of a curriculum for computer scientists and engineers. Here, we discuss how MIT’s longstanding efforts in this area may serve as a launching point for community development of a software performance engineering curriculum, challenges in and solutions for providing the necessary infrastructure to universities, and future directions.
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- Award ID(s):
- 2229704
- PAR ID:
- 10494099
- Publisher / Repository:
- IEEE
- Date Published:
- Journal Name:
- EduPar-24: 14th NSF/TCPP Workshop on Parallel and Distributed Computing Education
- Subject(s) / Keyword(s):
- performance distributed, parallel, and cluster computing data structures and algorithms software performance engineering
- Format(s):
- Medium: X
- Location:
- San Francisco, CA
- Sponsoring Org:
- National Science Foundation
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