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Record W2954493679 · doi:10.5539/jel.v8n4p64

Exploring the Differences Between Educational Consultant’s and Teachers’ Perceptions on Teachers’ Needs of Professional Development

2019· article· en· W2954493679 on OpenAlexaffvenue
Nada Wehbe

Bibliographic record

VenueJournal of Education and Learning · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicCollaborative Teaching and Inclusion
Canadian institutionsMcGill University
Fundersnot available
KeywordsPerceptionPsychologyProfessional developmentMedical educationMultimethodologyQualitative researchFaculty developmentPedagogySociologyMedicineSocial science

Abstract

fetched live from OpenAlex

The study aims to investigate whether there is a discrepancy between educational consultants and teachers’ perceptions on teachers’ needs of professional development. The study also intends to answer the following research question: Is there a discrepancy between the perceptions of educational consultants and teachers of teachers’ needs in professional development? Moreover, two sub research questions were addressed: How do teachers perceive their needs for PD? How do educational consultants prepare for PD sessions/programs? The participants of the study are twenty pre/lower elementary school teachers and one educational consultant in Beirut. The methodology used to conduct the study was mixed-methods: a qualitative analysis was conducted for the consultant’s interview questions and a quantitative analysis for the teachers’ questionnaire. Results showed slight differences between the perceptions of teachers on PD and that of the consultant.

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)0.006
metaresearch head score (Gemma)0.028
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.028
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0000.002
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 head0.075
GPT teacher head0.359
Teacher spread0.284 · 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
Published2019
Admission routes2
Has abstractyes

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