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Record W4414619266 · doi:10.5539/jel.v15n1p166

The Current Situation and Needs for Developing Curriculum to Promote Reading Habits and Reading Literacy Using Isan Local Literature for Primary School Learners

2025· article· en· W4414619266 on OpenAlexvenueno aff
Kamonlak Promma, Prasong Saihong

Bibliographic record

VenueJournal of Education and Learning · 2025
Typearticle
Languageen
FieldComputer Science
TopicEducational Systems and Policies
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumReading (process)LiteracyCurriculum developmentNational curriculumPrimary educationFocus group

Abstract

fetched live from OpenAlex

This research examines the current situations and needs for curriculum development to promote reading habits and reading literacy using Isan local literature for primary school learners. The research process starts with reviewing relevant literature and previous research regarding curriculum development principles, promoting reading habits and reading literacy, and the use of Isan local literature in primary learners. The next process is analyzing the current situation and needs for curriculum development by collecting data from stakeholders through questionnaires and focus group discussions. The research instruments included an analysis record form, a questionnaire on current conditions and needs, and an unstructured interview. The data analysis was conducted using frequency, percentage, mean, and standard deviation. The findings of this study reveal a significant gap between the current teaching practices and the high level of demand for developing a curriculum that promotes reading habits and reading literacy using Isan local literature. Current practices among primary school Thai language teachers were rated at a low level across all components, while the needs for curriculum development were consistently rated at the highest level. In conclusion, the findings validate the need for a curriculum that promotes reading habits and reading literacy through local literature among primary school students.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.901
Threshold uncertainty score0.707

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.013
GPT teacher head0.336
Teacher spread0.322 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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
Published2025
Admission routes1
Has abstractyes

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