Conceptualising evaluative judgement for sustainable assessment in higher education
Open accessAbstract
This chapter introduces a framework for evaluative judgement that underpins discussion in subsequent chapters. We start by identifying what we mean by evaluative judgement and examining why it is a necessary idea for organising courses and designing assessments. We suggest that the development of students’ evaluative judgement is an important and underexplored aspect of assessment which enables us to consider the longer-term influence of assessment activities on learning. We conclude by examining how common assessment practices – such as rubrics, exemplars, self-assessment, peer assessment and feedback – can be better tailored towards developing students’ evaluative judgement.
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?
Feedback literacy is not a fixed attribute but a developmental capacity that emerges through participation in purposefully structured feedback encounters that require active engagement with evaluative processes.
“Critically, feedback literacy is not a fixed attribute that students either possess or lack, but a developmental capacity that emerges through participation in purposefully structured feedback encounters that require active engagement with evaluative processes rather than passive receipt of commentary [3, 10, 19].”
From Making AI-Generated Feedback Matter: A Large-Scale Study of Feedback Workflows and Student Enactment (2026) · cites this paper as [19]
Cited by
Sorted by citations
Thinking to learn: managing the risks of outsourcing to GenAI
Chase, A.-M., & Galvin, K. (2026) · Assessment & Evaluation in Higher Education · doi:10.1080/02602938.2026.2620055 · Cited by 8 · see citing works
Making AI-Generated Feedback Matter: A Large-Scale Study of Feedback Workflows and Student Enactment
Alsaiari, O., Baghaei, N., Lodge, J. M., Gaševi'c, D., Winstone, N., & Khosravi, H. (2026) · arXiv · doi:10.48550/arxiv.2608.11625
“…literacy is not a fixed attribute that students either possess or lack, but a developmental capacity that emerges through participation in purposefully structured feedback encounters that require active engagement with evaluative processes rather than passive receipt of commentary [3, 10, 19].”
- Authors
- Ajjawi, R., Tai, J., Dawson, P., & Boud, D.
- Venue
- Developing Evaluative Judgement in Higher Education
- Publisher
- Routledge
- Published
- 2018-04-19
- Pages
- 7-17
- OpenAlex
- W2913795098
- Cited by
- 39
- References
- 0
- Citations by year
- 2026: 6 · 2025: 1 · 2024: 6 · 2023: 4 · 2022: 3 · 2021: 5 · 2020: 10 · 2019: 4
- FWCI
- 30.49
- Type
- book chapter
- Language
- en
- Open access
- green
- figshare.com
- Licence
- cc-by
- Locations
- Routledge eBooks (publishedVersion)
- Own your potential (DEAKIN) (submittedVersion)
- Middlesex University Research Repository (Middlesex University Of London) (submittedVersion)
- Figshare (submittedVersion, cc-by)
- UTS ePRESS (University of Technology Sydney) (submittedVersion)
- Topics
- Social Sciences › Education › Student Assessment and Feedback
- Social Sciences › Education › Evaluation of Teaching Practices
- Social Sciences › Education › Educational Assessment and Pedagogy
- Keywords
- evaluative judgments, sustainable assessment, higher education assessment, assessment design, course organization, learning outcomes, rubrics, exemplars, self-assessment, peer assessment, feedback
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
