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Record W4316465179 · doi:10.15453/2168-6408.1969

A Narrative Review of Student Evaluations of Teaching in Decolonial Praxis: Implications for Occupational Therapy Higher Education

2023· review· en· W4316465179 on OpenAlexfundno aff
Fatima Hendricks, Michaele Singleton, Asia R Clark, Marina Mishin, Marissa Epps

Bibliographic record

VenueThe Open Journal of Occupational Therapy · 2023
Typereview
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsPraxisScrutinyNarrativeSet (abstract data type)Inclusion (mineral)Promotion (chess)PsychologyPedagogyHigher educationMedical educationMathematics educationMedicineEpistemologySocial psychologyPolitical scienceComputer scienceArt

Abstract

fetched live from OpenAlex

Student evaluations of teaching (SETs) are the primary source for evaluating teaching effectiveness and are used for deciding tenure and promotion. However, as efforts to engage in a decolonial critique of higher education amplify, the use of SETs in teaching and learning requires scrutiny. A narrative review was used to address the research question of SET biases in decolonial praxis and what insights may be useful for OT decolonial praxis. We identify and describe two content areas: (a) SET biases and (b) recommendations for alternatives promoting OT decolonial praxis. A total of 92 articles were sourced from five databases. Of the 92 articles, 44 met the inclusion criteria: peer-reviewed across disciplines, written in English, research conducted in the US, and published between 2011–2021. SETs scores are affected by factors beyond the influence of the instructor. Twenty-nine factors contributing to SETs biases were grouped into three main categories: SETs biases against instructors, other biases from students, and SETs biases in processes. Alternative methodological approaches are highlighted that may mitigate the identified biases for application in decolonial praxis in OT higher education.

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)0.014
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.808
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.001
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 head0.702
GPT teacher head0.719
Teacher spread0.017 · 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
GenreReview

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

Citations2
Published2023
Admission routes1
Has abstractyes

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