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Record W4415226439 · doi:10.15173/ijsap.v9i2.5951

Testing students-as-partners theory

2025· article· en· W4415226439 on OpenAlexaffvenue
Laura Lukes, Larissa Rocha

Bibliographic record

VenueInternational Journal for Students as Partners · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Practises and Engagement
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsOperationalizationFeelingCurriculumGeneral partnershipWork (physics)Explanatory model

Abstract

fetched live from OpenAlex

Students as partners (SaP) has emerged as a way to innovate curriculum development and create more inclusive learning experiences for students in postsecondary settings. Popular models of SaP are time intensive, involving student and instructor dyads that meet frequently. Less is known about short-term consultant models of SaP and the impact on students. This study proposes a student-as-partners consultant (SaP-C) model and tests whether it can operationalize the principles of SaP theory. Student responses to a questionnaire (n= 7, 41% response rate), analyzed using an explanatory sequential mixed methods approach, indicate that the SaP-C approach does, according to students’ perspectives, operationalize SaP principles and positively influences students’ feelings of connection to other students and faculty. This model offers instructors an evidence-based, less time-intensive way to work in partnership with students in order to be pedagogically responsive to their perspectives and experiences in course or program design efforts.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.031
metaresearch head score (Gemma)0.103
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.166

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0310.103
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.006
Scholarly communication0.0040.007
Open science0.0030.008
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.101
GPT teacher head0.616
Teacher spread0.515 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations0
Published2025
Admission routes2
Has abstractyes

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