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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Board 359: Potential Interventions to Promote Engineering Technology Adoption among Faculty
During the current 4th industrial revolution, technology is changing at an ever increasing pace [1]. Thus, it is essential that engineering educators continually adopt and teach new engineering technologies to both keep their technologies relevant for graduates entering industry, as well as to model lifelong learning for their students. In fact, ABET requires faculty to teach relevant tools for modern engineering, as well as equip students with life-long learning skills [2]. However, the time restrictions on faculty are well documented [3 - 4] and can make learning new technologies difficult or impossible. This poster summarizes the preliminary results of an NSF project funded through the Directorate for Engineering, Engineering Education and Centers. It builds on our research that identified potential interventions to promote faculty adoption of new engineering technologies. Participants at a workshop at the IEEE Frontiers in Education Conference were presented with those preliminary results and asked to brainstorm ways the interventions could be implemented on their campuses, barriers to their implementation, and methods to overcome those barriers. The workshop was designed to provide peer review of the research results to determine if they would be considered relevant for institutions beyond the original research focus. An additional workshop goal was to expand on the existing set of proposed interventions by gathering ideas from faculty at other institutions. In this manner, the workshop both confirmed and expanded our data. The poster and this accompanying paper will present results of that brainstorming and will include proposed methods for reducing time constraints on faculty, support structures for faculty technology adoption, and human resources to support learning of new technologies.
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- Award ID(s):
- 2024970
- PAR ID:
- 10439919
- Date Published:
- Journal Name:
- 2023 ASEE Annual Conference & Exposition
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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This work-in-progress paper shares preliminary results from a research project that addresses three primary objectives: (1) to develop a conceptual model of technology adoption among engineering faculty through qualitative interview research; (2) to propose an adaption of existing models for technology adoption with appropriate constructs for engineering faculty; and (3) to propose one or more specific interventions to increase faculty adoption of new engineering technologies. In this paper, we focus primarily on the work in progress to meet the first objective. Specifically, we highlight how our preliminary findings about the factors affecting technology adoption, identified from interviews with engineering faculty, align with or differ from factors in previous models for technology adoption. Subjective norm, voluntariness, utility, technology cost, and facilitating conditions, were all preliminary factors found in our data that align at least somewhat with constructs from previous models [1], [2]. Time, access to the technology, efficiency/ease of work, and self regulation are factors that we have identified which are absent from the most widely applied models of technology adoption. We consider what our findings might imply in engineering education contexts.more » « less
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This Workshop will present the results from a study exploring the facilitating conditions which support the adoption of new engineering technologies among engineering faculty. Suggested interventions to promote greater technology adoption among faculty will be reviewed. Participants will discuss ways to build upon these suggested interventions and leave with concrete ideas about how to promote faculty technology adoption on their campuses.more » « less
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This work in progress paper we explain our process of co-sharing secondary qualitative data from separate projects funded by the National Science Foundation to better understand factors which influence faculty technology adoption in engineering education and provide a high-level presentation of preliminary results. Study A conducted 21 interviews of engineering faculty at a Midwestern US, STEM-centered university. These faculty were interviewed about the factors influencing their adoption and teaching of new engineering technologies, with a focus on programming languages, software, and instrumentation. Technology adoption models were applied as a theoretical lens for results analysis. Study B conducted 9 interviews with faculty in the College of Engineering at a Southern US university on the adoption of online laboratories in their instructional settings. The interviews focused on how faculty make use of online laboratories in electrical engineering as an essential resource. Innovation and propagation theories were applied as a theoretical lens for data analysis. The two data sets were co-shared for secondary analysis by each research group, using their own theoretical approaches. Preliminary findings lead us to believe that co-sharing of secondary data can expand qualitative data sets while providing a means for theoretical triangulation, improving data analysis.more » « less
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