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Record W2609308440 · doi:10.5430/wje.v7n2p65

Degree of Availability of Good Teacher Characteristics among the English Language (EL) Teachers of Basic Stage Schools from Their Principals’ Views in Tafila Governorate

2017· article· en· W2609308440 on OpenAlexvenueno aff
Atallah A. Al roud, Mohammad Al.qomoul

Bibliographic record

VenueWorld Journal of Education · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicSchool Choice and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyEnglish languageSignificant differenceDegree (music)Mathematics educationSample (material)PedagogyMathematicsStatistics

Abstract

fetched live from OpenAlex

The study aimed to investigate the Degree of Availability of Good Teacher Characteristics Among English Language(EL) Teachers of Basic Stage Schools from Their Principals’ views in Tafila Governorate. This could be achievedthrough answering the following questions:1-What is the degree of availability of good teacher characteristics among English Language (EL) teachers of basicstage schools from their principals’ views in Tafila Governorate?2-Are there statistically significant differences attributed to the variables of teacher’s gender, and experience?.The sample consisted of (89) male and female teachers which forms about 55% chosen randomly from thepopulation of the study.The results showed that there is a significant difference attributed to gender and no significant difference attributed toexperience or to the interaction of experience and gender. The study found some recommendations.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.047
GPT teacher head0.339
Teacher spread0.292 · 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 designObservational
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
Published2017
Admission routes1
Has abstractyes

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