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“I Saw a Change”: Enhancing Classroom Equity through Student-Faculty Pedagogical Partnership

2021· article· en· W4405564412 on OpenAlexaffabout
Elizabeth Marquis, Alise de Bie, Alison Cook‐Sather, Srikripa Krishna Prasad, Leslie Patricia Luqueño, Anita Ntem

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicCollaborative Teaching and Inclusion
Canadian institutionsMcMaster University
Fundersnot available
KeywordsGeneral partnershipEquity (law)Gender equityMathematics educationPsychologyPedagogyMedical educationSociologyPolitical scienceBusinessMedicineFinanceSocial science

Abstract

fetched live from OpenAlex

Persistent inequities in access to and experiences of learning in postsecondary education have been well documented. In line with efforts to redress these inequities and develop more just institutions, this study explores the potential for pedagogical partnerships in which students and faculty collaborate on teaching and learning initiatives to contribute to classroom equity. We investigate this issue by drawing on qualitative interviews with students who have participated in extracurricular pedagogical partnership programs in institutions in Canada and the United States, and who identify as members of marginalized groups (e.g., racialized students, 2SLGBTQ+ students, students from religious minorities, disabled students). While much existing research on equity and student-faculty partnership primarily focuses on the outcomes of partnership for participating students, we instead investigate students’ perceptions of the extent to which their partnership efforts contributed to wider impacts—such as developments in faculty thinking and teaching practice and student experiences in the classroom. We also consider challenges students noted connected to power imbalances and faculty resistance, which influence partnership’s capacity to contribute to equity and raise important considerations for those interested in partnership practice. Les inégalités persistantes concernant l’accès et les expériences d’apprentissage dans l’enseignement supérieur ont déjà été bien documentées. Conformément aux efforts déployés pour redresser ces inégalités et créer des établissements plus équitables, cette étude explore le potentiel pour des partenariats pédagogiques dans lesquels les étudiants/les étudiantes et les professeurs/les professeures collaborent sur des initiatives d’enseignement et d’apprentissage afin de contribuer à l’équité en salle de classe. Nous enquêtons sur cette question grâce à des entrevues qualitatives auprès d’ étudiants/d’étudiantes qui ont participé à des programmes de partenariat pédagogique extrascolaires dans des établissements du Canada et des États-Unis, et qui s’identifient en tant que membres de groupes marginalisés (par ex. racialisés, 2SLGNTQ+, minorités religieuses, personnes handicapées). Alors que la plupart de la recherche menée sur l’équité et les partenariats entre professeurs/professeures et étudiants/étudiantes se concentre principalement sur les résultats du partenariat pour les étudiants et les étudiantes qui y participent, de notre côté, nous enquêtons sur les perceptions des étudiants et des étudiantes concernant la portée dans laquelle leurs efforts de partenariat ont contribué à des impacts plus vastes – tels que l’évolution de la réflexion et des pratiques d’enseignement du corps enseignant et les expériences des étudiants et des étudiantes dans la salle de classe. Nous prenons également en considération les défis indiqués par les étudiants et les étudiantes liés aux déséquilibres du pouvoir et à la résistance des professeurs et des professeures, qui influencent la capacité du partenariat à contribuer à l’équité et soulèvent des considérations importantes pour les personnes intéressées à la pratique des partenariats.

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)0.021
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.112

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.029
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0150.013
Scholarly communication0.0160.012
Open science0.0030.032
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0080.001

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 head0.711
GPT teacher head0.691
Teacher spread0.020 · 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 designQualitative
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".

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Citations1
Published2021
Admission routes2
Has abstractyes

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