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Record W7132979766

How Ontario Certified Teachers Use Evidence from Research to Inform their Practice

2024· dissertation· W7132979766 on OpenAlexfundaboutno aff
Heather Elizabeth Clark

Bibliographic record

VenueTSpace · 2024
Typedissertation
Language
FieldSocial Sciences
TopicTeacher Education and Leadership Studies
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsCertificationInclusion (mineral)WorkloadQualitative researchTheme (computing)BurnoutProfessional developmentPreference
DOInot available

Abstract

fetched live from OpenAlex

This qualitative study explored how twelve permanently employed secondary school Ontario Certified Teachers (OCTs) with graduate level degrees and five or more years of experience, use existing research as evidence to inform their professional practice. Commonalities between the experiences shared by teachers during semi-structured interviews were identified as themes in alignment with the conceptual framework used to define the study, which was built upon Malcolm Knowles’ Adult Learning Theory. The interviewed participants indicated that they believe reviewing research is an important way for remaining current in their teaching practice but expressed a preference for prioritizing research shared with them by another trusted professional. Participants found themselves reviewing research about topics that they are individually interested in learning more about and tend to be different from the topics being discussed in the professional development sessions provided by their employer. A recurring theme among the interviews conducted as part of this thesis is that teaching is a very time-consuming profession and any evidence reviewed by a teacher needs to be pursued during their own time. Professional burnout that results from having a prolonged heavy workload is a barrier that limits how much professional learning teachers will actively engage in. Despite the perceived validity of the data obtained from this thesis, limitations of this study include the unique historical timing in which the data was collected, and specific inclusion criteria used for participant selection. It is hoped that future studies can confirm the widespread applicability of this data across individuals and time.

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)0.040
metaresearch head score (Gemma)0.096
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.960
Threshold uncertainty score0.804

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0400.096
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.005
Science and technology studies0.0110.018
Scholarly communication0.0140.006
Open science0.0030.006
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.584
GPT teacher head0.562
Teacher spread0.022 · 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.

Study designQualitative
DomainMethods
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
Published2024
Admission routes2
Has abstractyes

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