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Record W2079564467 · doi:10.5539/mas.v4n9p147

Effects of Principals’ Support on Teachers’ Self -Efficacy in Integrating e-learning in the Jordanian Discovery Schools

2010· article· en· W2079564467 on OpenAlexvenueno aff
Khader AL-Rawajfih, Soon Fook Fong, Sharifah Norhaidah Syed Idros

Bibliographic record

VenueModern Applied Science · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicGender and Technology in Education
Canadian institutionsnot available
Fundersnot available
KeywordsPerceptionDescriptive statisticsMathematics educationPsychologyVariablesPerspective (graphical)Self-efficacyModerationCapital cityStratified samplingMathematicsStatisticsSocial psychologyGeography

Abstract

fetched live from OpenAlex

This study examines the effect of perceptions of principals’ support of teachers in Jordan Discovery schools on the integration of e-learning into their teaching. 350 teachers were randomly stratified from a total of 2,389 teachers from all the secondary Discovery schools in the four districts (strata) of the capital, Amman. The dependent variable was the integration of e-learning. The independent variable was the perception on the Principals’ support needed for the integration of e-Learning and the moderating variable was the gender and teaching experiences. The responses from the survey were analyzed with descriptive statistics and two-way ANOVA. The findings of this study exhibit moderate levels of self-efficacy. From the perspective of self-efficacy, there were significant differences among the means for main effect for both teachers’ teaching experience and gender on the integration of e-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)0.002
metaresearch head score (Gemma)0.006
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 score0.003
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.011
GPT teacher head0.298
Teacher spread0.287 · 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

Citations2
Published2010
Admission routes1
Has abstractyes

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