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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.
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Changing the Paradigm: Developing a Framework for Secondary Analysis of EER Qualitative Datasets
This paper reports on a project funded through the Engineering Education and Centers (EEC) Division of the National Science Foundation. Since 2010, EEC has funded more than 500 proposals totaling over $150 million through engineering education research (EER) programs such as Research in Engineering Education (REE) and Research in the Formation of Engineers (RFE), to enhance understanding and improve practice. The resulting archive of robust qualitative and quantitative data represents a vast untapped potential to exponentially increase the impact of EEC funding and transform engineering education. But tapping this potential has thus far been an intractable problem, despite ongoing calls for data sharing by public funders of research. Changing the paradigm of single-use data collection requires actionable, proven practices for effective, ethical data sharing, coupled with sufficient incentives to both share and use existing data. To that end, this project draws together a team of experts to overcome substantial obstacles in qualitative data sharing by building a framework to guide secondary analysis in engineering education research (EER), and to test this framework using pioneering data sets. Herein, we report on accomplishments within the first year of the project during which time we gathered a group of 13 expert qualitative researchers to engage in the first of a series of working meetings intended to meet our project goals. We came into this first workshop with a potentially limiting definition of secondary data analysis and the idea that people would want to share existing datasets if we could find ways around anticipated hurdles. However, the workshop yielded a broader definition of secondary data analysis and revealed a stronger interest in creating new datasets designed for sharing rather than sharing existing datasets. Thus, we have reconceived our second phase as one that is a cohesive effort based on an inclusive “open cohort model” to pilot projects related to secondary data analysis.
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- Award ID(s):
- 2039871
- PAR ID:
- 10392042
- Date Published:
- Journal Name:
- 2022 ASEE Annual Conference & Exposition
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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This work-in-progress paper draws from the ongoing “The Distributed System of Governance in Engineering Education” project’s qualitative dataset. The Governance project uses an ethnomethodological approach to understand the practice of engineering education reform. The dataset contains oral interview data from both academic institutions and organizations with roles in engineering education governance such as ABET. The academic institutions in the study are representative of the range of engineering schools in US—research intensive, predominately undergraduate, private, public, MSI, etc.—and interview subjects span the administrative spectrum from faculty to department chairs to provosts. This work-in-progress uses this data set to probe two research questions: 1) To what extent, and how, do academic administrators and policy makers in higher education draw on insights from engineering education research (EER) in deriving policies and making decisions? 2) To what extent do the issues and challenges articulated by administrators match those articulated or identified by EER community? The initial analysis of interview data from over seventy subjects from fifteen universities was done from a symbolic interactionism perspective. Initial findings are that university administrators are generally not aware of engineering education and the engineering education research body of knowledge is not generally used in day-to-day decision making. This may be due to the fact the concerns expressed by administrators are often misaligned with EER priorities. The authors seek feedback on how to better understanding “invisible channels” through which EER findings may find their way into administrative decisions as well as other means by which EER influences governance processes other than through established administrative channels.more » « less
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This work-in-progress paper draws from the ongoing “The Distributed System of Governance in Engineering Education” project’s qualitative dataset. The Governance project uses an ethnomethodological approach to understand the practice of engineering education reform. The dataset contains oral interview data from both academic institutions and organizations with roles in engineering education governance such as ABET. The academic institutions in the study are representative of the range of engineering schools in US—research intensive, predominately undergraduate, private, public, MSI, etc.—and interview subjects span the administrative spectrum from faculty to department chairs to provosts. This work-in-progress uses this data set to probe two research questions: 1) To what extent, and how, do academic administrators and policy makers in higher education draw on insights from engineering education research (EER) in deriving policies and making decisions? 2) To what extent do the issues and challenges articulated by administrators match those articulated or identified by EER community? The initial analysis of interview data from over seventy subjects from fifteen universities was done from a symbolic interactionism perspective. Initial findings are that university administrators are generally not aware of engineering education and the engineering education research body of knowledge is not generally used in day-to-day decision making. This may be due to the fact the concerns expressed by administrators are often misaligned with EER priorities. The authors seek feedback on how to better understanding “invisible channels” through which EER findings may find their way into administrative decisions as well as other means by which EER influences governance processes other than through established administrative channels.more » « less
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This work-in-progress paper draws from the ongoing “The Distributed System of Governance in Engineering Education” project’s qualitative dataset. The Governance project uses an ethnomethodological approach to understand the practice of engineering education reform. The dataset contains oral interview data from both academic institutions and organizations with roles in engineering education governance such as ABET. The academic institutions in the study are representative of the range of engineering schools in US—research intensive, predominately undergraduate, private, public, MSI, etc.—and interview subjects span the administrative spectrum from faculty to department chairs to provosts. This work-in-progress uses this data set to probe two research questions: 1) To what extent, and how, do academic administrators and policy makers in higher education draw on insights from engineering education research (EER) in deriving policies and making decisions? 2) To what extent do the issues and challenges articulated by administrators match those articulated or identified by EER community? The initial analysis of interview data from over seventy subjects from fifteen universities was done from a symbolic interactionism perspective. Initial findings are that university administrators are generally not aware of engineering education and the engineering education research body of knowledge is not generally used in day-to-day decision making. This may be due to the fact the concerns expressed by administrators are often misaligned with EER priorities. The authors seek feedback on how to better understanding “invisible channels” through which EER findings may find their way into administrative decisions as well as other means by which EER influences governance processes other than through established administrative channels.more » « less
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This paper describes a peer reviewer mentoring program called the Engineering Education Research Peer Review Training (EER PERT) project and serves as a pilot study on longitudinal effects on researchers’ productivity and the impact of their work, differences in these factors for those who review journal manuscripts and those who review grant proposals, and what aspects of peer review training (knowledge, resources, collaborations, etc.) participants actually carry forward in their own research. Overall, the project seeks to investigate how engineering education research (EER) scholars develop skills and schema for reviewing scholarship, particularly in terms of developing constructive reviews that build expertise and advance knowledge. The Journal of Engineering Education (JEE) Mentored Reviewer Program constitutes the first phase of the EER PERT project. In this paper, we report on goals, structure and activities for the JEE Mentored Reviewer Program, pilot data from participants’ applications and exit surveys that will inform the EER PERT project in terms of participants’ developing skills and schema for reviewing and conducting EER, and provide initial suggestions from the training program that may benefit scholars new to EER.more » « less
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