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Record W2757148403 · doi:10.5539/ijel.v7n6p148

Native and Non-native English Speaking Teachers’ Teaching Styles and Their Effect on Their EFL Saudi Students’ Achievement and Enjoyment of Learning English at Taif University

2017· article· en· W2757148403 on OpenAlexvenueno aff
Nasrah Mahmoud Ismaiel

Bibliographic record

VenueInternational Journal of English Linguistics · 2017
Typearticle
Languageen
FieldPsychology
TopicEmotional Intelligence and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyLearning stylesEnglish languageMathematics educationPedagogy

Abstract

fetched live from OpenAlex

The present research is going to assess the discrepancies between native and non-native instructors working at Taif University. The subjects have been 609 Saudi men and women EFL learners presenting themselves in a great English language plan at the preparatory year Science, Humanities and Health at Taif University. Moreover, 51 teachers (20) males and (31) females who are teaching staff members of the Taif University English Language Centre (TUELC) participated during the research. The research followed a descriptive analytical method. The Conti (1990) Principles of Adult Learning Scales (PALS) was used. Learning English Enjoyment questionnaire (LEEQ) that was developed by the researcher was used, too. Primary areas of investigation were teaching styles, students’ achievement and students’ enjoyment of learning English. Collectively, results provide some strong evidence that show a positive connection between native English speaking teachers’ styles and the students’ achievement and enjoyment. The effect of instruction experience, like the periods of instructing was considered in the present research. In addition, native and nonnative instructors who speak English are regarded also various in such domains as instruction strategies in the classes, levels of teaching tactical effectiveness.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.018
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.172
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.022
GPT teacher head0.330
Teacher spread0.307 · 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 teacher head, not a consensus.

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

Citations9
Published2017
Admission routes1
Has abstractyes

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