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Discipline‐Based Education Research: Understanding and Improving Learning in Undergraduate Science and Engineering
Abstract
Engineering education research (EER) has been on the fast track since 2004 with an exponential rise in the number of Ph.D.s awarded and the establishment of new programs, even entire EER departments. The National Research Council’s Discipline-Based Education Research (DBER) report (National Research Council, 2012) captures the state-of-the-art advances in our understanding of engineering and science student learning and highlights commonalities with other science-based education research programs. The DBER report is the consensus analysis of experts in undergraduate education research in physics, chemistry, biology, geosciences, astronomy, and engineering. The study committee, chaired by Susan Singer, also included higher education researchers, learning scientists, and cognitive psychologists. A central aspect of the DBER report is the focus on and application of research in the education, learning, and social-behavioral sciences to science and engineering curricula design and teaching methods. Froyd, Wankat, and Smith (2012) identified five major shifts in engineering education in the past 100 years: 1. A shift from hands-on and practical emphasis to engineering science and analytical emphasis 2. A shift to outcomes-based education and accreditation 3. A shift to emphasizing engineering design 4. A shift to applying education, learning, and social-behavioral sciences research 5. A shift to integrating information, computational, and communications technology in education
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Cited by
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Metadata
- Authors
- Singer, S., & Smith, K. A.
- Venue
- Journal of Engineering Education
- Publisher
- Wiley
- Published
- 2013-10
- Volume
- 102
- Issue
- 4
- Pages
- 468-471
- ISSN
- 1069-4730 (ISSN-L)
- 2168-9830
- OpenAlex
- W1949744349
- Cited by
- 835
- References
- 484
- FWCI
- 172.23
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.