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Assessing the Non-Cognitive Domains: Measuring What Matters Well

Assessing the Non-Cognitive Domains: Measuring What Matters Well

James G. M. Crossley
Copyright: © 2020 |Pages: 26
ISBN13: 9781799804208|ISBN10: 1799804208|EISBN13: 9781799804215
DOI: 10.4018/978-1-7998-0420-8.ch048
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MLA

Crossley, James G. M. "Assessing the Non-Cognitive Domains: Measuring What Matters Well." Learning and Performance Assessment: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, IGI Global, 2020, pp. 1021-1046. https://doi.org/10.4018/978-1-7998-0420-8.ch048

APA

Crossley, J. G. (2020). Assessing the Non-Cognitive Domains: Measuring What Matters Well. In I. Management Association (Ed.), Learning and Performance Assessment: Concepts, Methodologies, Tools, and Applications (pp. 1021-1046). IGI Global. https://doi.org/10.4018/978-1-7998-0420-8.ch048

Chicago

Crossley, James G. M. "Assessing the Non-Cognitive Domains: Measuring What Matters Well." In Learning and Performance Assessment: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, 1021-1046. Hershey, PA: IGI Global, 2020. https://doi.org/10.4018/978-1-7998-0420-8.ch048

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Abstract

Good assessment assures attainment and drives learning. In vocational and practical programmes, the important learning outcomes are non-cognitive skills and attitudes - for example, dexterity, situational awareness, professionalism, compassion, or resilience. Unfortunately, these domains are much more difficult to assess. There are three main reasons. First, the constructs themselves are tacit - making them difficult to define. Second, performance is highly variable and situation-specific. Third, significant assessor judgement is required to differentiate between good and poor performance, and this brings subjectivity. The chapter reviews seven existing strategies for addressing these problems: delineating the constructs, using cognitive assessments as a proxy, making the subjective objective, sampling across performances and opinions, using outcome measures as a proxy, using meta-cognition as a proxy, and abandoning the existing measurement paradigm. Given the limitations of these strategies, the author finishes by offering three promising ways forward.

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