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Team Effectiveness Theory from Industrial and Organizational Psychology Applied to Engineering Student Project Teams: A Research Review
Abstract
Background: Engineering student team projects are frequently used to meet professional learning outcomes. Industrial and organizational psychologists study teams in the industry settings for which we prepare students, yet this research does not effectively inform engineering education. Purpose: This research review sought to demonstrate the relevance of literature on teams literature from industrial and organizational psychology to engineering education and to identify implications for practice and future directions for research. Scope/Method: Phase 1 systematically reviewed 104 articles published from 2007 to 2012 describing engineering and computer science student team projects and sought to answer the following questions: What professional learning outcomes have been met by team projects? What negative student team behaviors have faculty sought to minimize? What literature has been used to inform development of teamwork outcomes? Phase 2 reviewed five team effectiveness constructs selected according to the results of Phase 1: social loafing, interdependence, conflict, trust, and shared mental models. Examples from Phase 1 articles and our own work explain how this research informs facilitation and assessment of engineering student teams. Conclusions: Engineering faculty sought to achieve a variety of outcomes through team projects, including teamwork, communication, sustainability, and consideration of global/societal design context. They sought to avoid social loafing and conflict while building trust to ensure equal team effort. That few Phase 1 articles engaged the literature about team effectiveness indicates there is great opportunity to apply industrial and organizational psychology research to engineering education.
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“Capstone projects exemplify product assessment, reflecting cumulative learning over a course, while simulations can be used in process as - sessments [ 20].”
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Metadata
- Authors
- Borrego, M., Karlin, J., McNair, L. D., & Beddoes, K.
- Venue
- Journal of Engineering Education
- Publisher
- Wiley
- Published
- 2013-10
- Volume
- 102
- Issue
- 4
- Pages
- 472-512
- ISSN
- 1069-4730 (ISSN-L)
- 2168-9830
- OpenAlex
- W1961622147
- Cited by
- 330
- References
- 154
- FWCI
- 65.45
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
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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.