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Record W4206815847 · doi:10.52547/johepal.2.4.121

A Case Study of Teacher Candidates’ Experiences: Writing the Pilot Math Proficiency Test in Ontario, Canada

2021· article· en· W4206815847 on OpenAlexaffabout
Ardavan Eizadirad, Jennifer Holm, Steve Sider

Bibliographic record

VenueJournal of Higher Education Policy And Leadership Studies · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicEducation Systems and Policy
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsTest (biology)Mathematics educationPsychologyGeology

Abstract

fetched live from OpenAlex

The focus of this article is on the introduction, justification, and enactment of the Mathematics Proficiency Test (MPT) by the provincial government in Ontario, Canada as a mandatory certification requirement for newly certified teachers. This article contextualizes the socio-political factors leading to the enactment of a MPT for newly certified teachers, developed and administered by the Education Quality and Accountability Office (EQAO), which was ostensibly to mitigate the trend of declining math scores in elementary schools. It then shifts to examine the experiences of the first cohort of teacher candidates from a Canadian university who participated in writing the pilot MPT in February and March of 2020. Data was collected via survey responses administered through Qualtrics software. Survey invitations were sent to all teacher candidates who graduated in 2020 or 2021 with 50 of the 130 eligible teacher candidates responding. A thematic analysis of survey responses was conducted to discuss emerging findings about teacher candidates' experiences before, the day of, and after writing the MPT as a case study. On December 17, 2021 the Ontario Superior Court of Justice ruled the MPT unconstitutional due to having an adverse impact on entry to the teaching profession for racialized teacher candidates.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.195
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.229
GPT teacher head0.417
Teacher spread0.188 · 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.

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".

Quick stats

Citations0
Published2021
Admission routes2
Has abstractyes

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