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Conceptual Difficulties Experienced by Trained Engineers Learning Educational Research Methods

Borrego, Maura·2007·Journal of Engineering Education

Abstract

This paper describes conceptual difficulties that may be experienced by engineering faculty as they become engineering education researchers. Observation, survey, and assessment data collected at the 2005 NSF‐funded Rigorous Research in Engineering Education workshop were systematically analyzed to uncover the five difficulties encountered by engineering faculty learning to design rigorous education studies: (1) framing research questions with broad appeal, (2) grounding research in a theoretical framework, (3) fully considering operationalization and measurement of constructs, (4) appreciating qualitative or mixed‐methods approaches, and (5) pursuing interdisciplinary collaboration. The first four can be understood in terms of disciplinary consensus; they represent explicit steps in education research that are implicit in technical engineering research because there is greater consensus of methods and standards. This work better frames the issue of rigor in engineering education research by clarifying the fundamental differences that prevent application of traditional engineering standards of rigor directly to engineering education research.

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Metadata

Authors
Borrego, M.
Venue
Journal of Engineering Education
Publisher
Wiley
Published
2007-04
Volume
96
Issue
2
Pages
91-102
ISSN
  • 1069-4730 (ISSN-L)
  • 2168-9830
OpenAlex
W2071410515
Cited by
200
References
0
FWCI
43.51
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Conceptual Difficulties Experienced by Trained Engineers Learning Educational Research Methods. https://app.cochat.ai/papers/10.1002/j.2168-9830.2007.tb00920.x
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Borrego, M. (2007). Conceptual Difficulties Experienced by Trained Engineers Learning Educational Research Methods. Journal of Engineering Education. https://doi.org/10.1002/j.2168-9830.2007.tb00920.x

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.