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Record W3126724393 · doi:10.5539/elt.v14n2p68

An Evaluation of a Fourth Level English Textbook Used in Secondary Schools in Riyadh City

2021· article· en· W3126724393 on OpenAlexvenueno aff
Yusuf Ahmad K. Alsulami

Bibliographic record

VenueEnglish Language Teaching · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsChecklistPsychologyStrengths and weaknessesMathematics educationEnglish languageMedical educationPedagogyMedicine

Abstract

fetched live from OpenAlex

This paper evaluates a textbook called Traveller 4 that is used in the second grade of secondary schools in Riyadh City, Saudi Arabia, considering its general appearance and design, objectives, content, social and cultural contexts, tasks and activities, and usefulness for developing language skills. The paper also reviews the literature concerning textbook evaluation, referring to various theoretical and empirical studies that have contributed to the field of educational material evaluation. The research used a descriptive research model to assess data regarding the assessment of the English textbook and employed a questionnaire to investigate teachers’ perspectives on a range of related items. The questionnaire targeted high school English teachers in Riyadh city and consisted of 40 items, which were divided into six categories. The instrument used in this study to evaluate Traveller 4 was the ESL Textbook Evaluation Checklist. The findings of this research study revealed important points relating to the characteristics of a good textbook and identified strengths, weaknesses, and opportunities to modify the book. This paper concludes with recommendations for improving the textbook.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.060
GPT teacher head0.309
Teacher spread0.248 · 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

Citations12
Published2021
Admission routes1
Has abstractyes

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