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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.
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Co-sharing secondary qualitative research data to understand technology adoption in engineering education courses
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.
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- Award ID(s):
- 2024970
- PAR ID:
- 10548039
- Publisher / Repository:
- IEEE
- Date Published:
- Edition / Version:
- 18-21 October 2023
- ISSN:
- 2377-634X
- ISBN:
- 979-8-3503-3642-9
- Page Range / eLocation ID:
- 1 to 5
- Subject(s) / Keyword(s):
- secondary data sharing qualitative research technology adoption engineering education
- Format(s):
- Medium: X Size: 361 kb Other: pdf
- Size(s):
- 361 kb
- Location:
- College Station, TX, USA
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/FIE58773.2023.10342944
