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Record W2014451376 · doi:10.5539/elt.v7n3p150

The Evaluation of “English Textbook 2” Taught in Iranian High Schools from Teachers’ Perspectives

2014· article· en· W2014451376 on OpenAlexvenueno aff
Touran Ahour, Bayezid Towhidiyan, Mahnaz Saeidi

Bibliographic record

VenueEnglish Language Teaching · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicSecond Language Learning and Teaching
Canadian institutionsnot available
Fundersnot available
KeywordsSyllabusLikert scaleChecklistPsychologyMathematics educationCurriculumChristian ministrySubject (documents)PedagogyMedical educationLibrary scienceMedicineComputer science

Abstract

fetched live from OpenAlex

The purpose of this study was to investigate the appropriateness of “English Textbook 2” for Iranian EFL second grade high school students from the teachers’ perspectives. The participants of the study consisted of 25 English teachers (8 females and 17 males) randomly selected from different high schools in Boukan, Iran. The evaluation of the textbook was conducted quantitatively through an adapted checklist developed by Litz (2005). The checklist was a 5-point Likert scale and three criteria including subject and content, activities, and skills out of seven criteria in Litz’s checklist were selected for this study. The results of the study revealed that teachers’ perceptions about these criteria were not favorable in general. The results of this study can be helpful for teachers to use appropriate teaching techniques to compensate for the deficiencies of the textbook and the materials developers and syllabus and curriculum designers in Ministry of Education and other pedagogical experts to revise the current textbook or adopt a new textbook instead.

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)0.004
metaresearch head score (Gemma)0.013
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 score0.004
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.252
Teacher spread0.237 · 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

Citations31
Published2014
Admission routes1
Has abstractyes

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