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Record W3024277640 · doi:10.7202/1069771ar

VALIDATION OF A TYPOLOGY OF NOVICE TEACHERS’ SUPPORT NEEDS AND COMPARATIVE ANALYSIS BASED ON SOCIODEMOGRAPHIC CHARACTERISTICS

2020· article· en· W3024277640 on OpenAlexaffvenue
Geneviève Carpentier, Joséphine Mukamurera, Mylène Leroux, Sawsen Lakhal

Bibliographic record

VenueMcGill Journal of Education / Revue des sciences de l éducation de McGill · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicTeacher Professional Development and Motivation
Canadian institutionsUniversité du Québec en OutaouaisUniversité de SherbrookeUniversité de Montréal
Fundersnot available
KeywordsTypologyConfirmatory factor analysisField (mathematics)PsychologyRelation (database)Applied psychologyComputer scienceSociologyStructural equation modelingMathematics

Abstract

fetched live from OpenAlex

The first years of teaching are challenging. Knowledge of the kind of support new teachers require is essential. Existing typologies date back from the 1980s and the early 2000s. The aim of this article is twofold: 1) to validate a typology of novice teachers’ support needs using confirmatory factor analysis and 2) to compare these needs in relation to different sociodemographic characteristics (gender, age, employment status, teaching level, and field of study). The quantitative data were drawn from a survey (N = 156) of new teachers. The validated typology highlights five types of support needs. Some key differences emerge from the comparative analyses based on respondents’ age, employment status, and field of study. The results presented could help serve as a framework for better targeting the support to be offered to beginning teachers.

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)0.013
metaresearch head score (Gemma)0.032
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.996
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.032
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0050.002
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
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 head0.401
GPT teacher head0.447
Teacher spread0.046 · 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".

Quick stats

Citations2
Published2020
Admission routes2
Has abstractyes

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Same venueMcGill Journal of Education / Revue des sciences de l éducation de McGillSame topicTeacher Professional Development and MotivationFrench-language works237,207