‘There was very little room for me to be me’: the lived tensions between assessment standardisation and student diversity
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Higher education aims to educate diverse professionals to operate in an increasingly complex world. Yet, academic assessment practices still rely upon standardisation, namely, that all students should demonstrate their achievement in ways that are largely comparable, if not identical. In this study, we theorise assessment standardisation as a technology of normalisation upon student diversity and identities. Our study is located in one of the most complex learning settings in higher education: placements. We theorise how diverse students navigate the tensions arising from standardised assessment situations that assess highly personalised forms of learning in complex assessment settings. Our data material consists of longitudinal interviews with 16 disabled university students in Australia before, during, and after a placement. Our findings show that assessment suppresses and normalises students’ diverse identities, calling into question the inclusivity of such assessment practices. We discuss how assessment provides students with narrow ways of forming their professional identities. While this is the case for all students, the social consequences of assessment standardisation might be more crucial for those who do not fit the ‘norm’ set by assessment, such as disabled students in our case.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it