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Record W3217294697 · doi:10.21432/cjlt27948

Online Teacher Professional Development in Canada: A Review of the Research

2021· review· en· W3217294697 on OpenAlexaffvenueabout
Pamela Beach, Elena Favret, Alexandra Minuk

Bibliographic record

VenueCanadian Journal of Learning and Technology · 2021
Typereview
Languageen
FieldSocial Sciences
TopicTeacher Education and Leadership Studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsProfessional developmentThematic analysisFaculty developmentEducational researchPsychologyPedagogyQualitative researchSociologySocial science

Abstract

fetched live from OpenAlex

This paper presents findings from a systematic review of 11 studies examining online teacher professional development (oTPD) in Canada between 2000-2020. A thematic content analysis of the articles led to four main themes associated with research on oTPD: 1. knowledge exchange; 2. reflective practice; 3. multifaceted learning opportunities; and 4. just-in-time support. The study contexts, research methods, and other relevant study characteristics are also reviewed and discussed. The results shed light on the current research trends on oTPD in Canada and highlight the need for continued research in this area. Data from diverse research methods across Canada’s geographical regions can contribute to greater insight into the types of oTPD occurring in Canada and how various platforms and professional development opportunities can best support teachers’ professional learning.

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)0.011
metaresearch head score (Gemma)0.034
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.956
Threshold uncertainty score0.378

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.034
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0240.046
Science and technology studies0.0030.002
Scholarly communication0.0060.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.265
GPT teacher head0.477
Teacher spread0.212 · 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 designSystematic review
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

Citations14
Published2021
Admission routes3
Has abstractyes

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