Establishing the critical elements that determine authentic assessment
Open accessAbstract
This study sought to determine the critical elements of an authentic learning activity, design them into an applicable framework and then use this framework to guide the design, development and application of work-relevant assessment. Its purpose was to formulate an effective model of task design and assessment. The first phase of the study identified from the literature critical elements that determined assessment as being authentic, and presented these to practitioners and experts for feedback. In phase two, it codified the elements into a framework that was then applied to the redesign of assessments in an army course. Phase three involved student evaluation of the redesigned assessment activities. This led to further review and revision of elements in phase four. The study outcomes suggest that it is possible, by identifying and codifying individual elements, to determine the ways in which the authenticity of an individual assessment activity might be enhanced. The paper concludes with a literature update on the framework elements that lead to suggestions for further research.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Assessment methods aligned with professional practice can enhance student engagement and learning outcomes.
“These findings support the authentic assessment literature suggesting that assessment methods aligned with professional practice can enhance student engagement and learning outcomes (Ashford-rowe, Herrington, and Brown 2014;Fawns et al. 2025).”
From Utilising one-on-one interactive oral assessments as the major final assessment within a bioscience course (2025) · cites this paper as Ashford-rowe, Herrington, and Brown 2014
Cites
Effects of learning skills interventions on student learning: a meta-analysis.
Hattie, J., Biggs, J., & Purdie, N. (1996) · Review of Educational Research · doi:10.3102/00346543066002099 · Cited by 1,106 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Authentic assessment: creating a blueprint for course design
Villarroel, V., Bloxham, S., Bruna, D., Bruna, C., & Herrera-Seda, C. (2018) · Assessment & Evaluation in Higher Education · doi:10.1080/02602938.2017.1412396 · Cited by 560 · see citing works
Sotiriadou, P., Logan, D., Daly, A., & Guest, R. (2020) · Studies in Higher Education · doi:10.1080/03075079.2019.1582015 · Cited by 265 · see citing works
Kofinas, A. K., Tsay, C. H., & Pike, D. (2025) · British Journal of Educational Technology · doi:10.1111/bjet.13585 · Cited by 207 · see citing works
Using principles of authentic assessment to redesign written examinations and tests
Villarroel, V., Boud, D., Bloxham, S., Bruna, D., & Bruna, C. (2020) · Innovations in Education and Teaching International · doi:10.1080/14703297.2018.1564882 · Cited by 157 · see citing works
Vlachopoulos, D., & Makri, A. (2024) · Studies in Educational Evaluation · doi:10.1016/j.stueduc.2024.101425 · Cited by 144 · see citing works
Race with the machines: assessing the capability of generative AI in solving authentic assessments
Nguyen Thanh, B., Vo, D. T. H., Nguyen Nhat, M., Pham, T. T. T., Thai Trung, H., & Ha Xuan, S. (2023) · Australasian Journal of Educational Technology · doi:10.14742/ajet.8902 · Cited by 87 · see citing works
“The benefits of authentic assessments, including the enhancement of higher-order thinking skills, the fostering of transferable skills in contextualised settings and the boosting of students’ motivation and overall learning (Ashford-Rowe et al., 2014; Villarroel et al., 2018), are well documented.”
BackgroundHigher education assessment practice in the era of generative AI tools
(2024) · Journal of Applied Learning & Teaching · doi:10.37074/jalt.2024.7.1.28 · Cited by 37 · see citing works
Authentic and Creative Assessment in a World with AI
Miserandino, M. (2025) · Teaching of Psychology · doi:10.1177/00986283241260370 · Cited by 15 · see citing works
Beyond Detection: Redesigning Authentic Assessment in an AI-Mediated World
Kickbusch, S., Ashford-Rowe, K., Kemp, A., Boreland, J., & Huijser, H. (2025) · Education Sciences · doi:10.3390/educsci15111537 · Cited by 17 · see citing works
Self-citationDavey, S. K., Birbeck, D., Nallaya, S., Sallows, G., & Della Vedova, C. B. (2025) · Assessment & Evaluation in Higher Education · doi:10.1080/02602938.2025.2502577 · Cited by 9 · see citing works
- Authors
- Ashford-Rowe, K., Herrington, J., & Brown, C.
- Affiliations
- Australian Catholic University (AU)
- University of Wollongong (AU)
- Corresponding author
- Ashford-Rowe, Kevin
- Venue
- Assessment & Evaluation in Higher Education
- Publisher
- Informa UK Limited
- Published
- 2013-07-24
- Volume
- 39
- Issue
- 2
- Pages
- 205-222
- ISSN
- 0260-2938 (ISSN-L)
- 1469-297X
- OpenAlex
- W2056855739
- Cited by
- 390
- References
- 1
- Citations by year
- 2026: 56 · 2025: 39 · 2024: 64 · 2023: 50 · 2022: 37 · 2021: 36 · 2020: 29 · 2019: 26 · 2018: 13 · 2017: 13 · 2016: 16 · 2015: 8 · 2014: 3
- FWCI
- 43.54
- Type
- journal article
- Language
- en
- Open access
- green
- eprints.qut.edu.au
- Licence
- cc-by-nc
- Locations
- Assessment & Evaluation in Higher Education (publishedVersion)
- QUT ePrints (Queensland University of Technology) (submittedVersion, cc-by-nc)
- Research Bank (Australian Catholic University) (submittedVersion)
- Murdoch University Research Portal (submittedVersion)
- Research Online (University of Wollongong) (submittedVersion)
- Topics
- Social Sciences › Education › Student Assessment and Feedback
- Social Sciences › Education › Problem and Project Based Learning
- Social Sciences › Education › Educational Assessment and Pedagogy
- Keywords
- authentic assessment, authentic learning tasks, task design, military education, assessment authenticity
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 ›
Are you an author, or do you see a problem with this page? Request a review
