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Record W4403430045 · doi:10.15173/ijsap.v8i2.5670

A students-as-partners-inspired approach to assessment rubric design

2024· article· en· W4403430045 on OpenAlexvenueno aff
Christina Do, Hugh Finn, Andrew Brennan, Janie Brown, Anna Tarabasz

Bibliographic record

VenueInternational Journal for Students as Partners · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Practises and Engagement
Canadian institutionsnot available
FundersCurtin University of Technology
KeywordsRubricMathematics educationComputer sciencePsychology

Abstract

fetched live from OpenAlex

The global popularity of the students-as-partners (SaP) model in the higher education sector demonstrates that students, through their lived experiences, have valuable perspectives to contribute to shaping university curricular and co-curricular experiences. While there are numerous inherent benefits associated with facilitating SaP arrangements, incorporating such practices to influence curricular change can be difficult in highly regulated and accredited courses. This article presents a successfully trialled SaP-inspired model involving assessment rubric design in the Bachelor of Laws degree offered at Curtin University in Australia, which is subject to multiple layers of regulation at national and state levels by public and private bodies. The SaP-inspired model presented in the paper is a useful starting point for academics wanting to engage in SaP co-creation of curricular initiatives in contexts that are not especially conducive to SaP, for example, heavily regulated and accredited courses. This article further contributes to existing SaP literature as it presents qualitative and quantitative data collected from the students who engaged in the SaP-inspired model, as well as data collected from students who experienced the SaP-inspired outputs first hand. This article commences with a student reflection on the SaP-inspired model, written by Ryan Kirby who participated in the workshop and assisted in the creation of the assessment rubric and supplementary materials.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.528
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0030.001
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.152
GPT teacher head0.613
Teacher spread0.461 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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