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Record W4413486423 · doi:10.5430/jct.v14n3p292

The Mediating Role of Students’ Metacognitive Awareness between Teachers’ Reading Strategies and Students’ Reading Performance

2025· article· en· W4413486423 on OpenAlexvenueno aff
Jing Wang, Xiao Xiao

Bibliographic record

VenueJournal of Curriculum and Teaching · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Critical Thinking Development
Canadian institutionsnot available
Fundersnot available
KeywordsReading (process)MetacognitionPsychologyMathematics educationDevelopmental psychologyCognitionLinguistics

Abstract

fetched live from OpenAlex

This study focused on the impact of teachers’ reading strategies on students’ reading performance, with a specific emphasis on the role of TOEFL reading instructors in training institutions. The primary objective was to investigate how the reading strategies employed by TOEFL teachers influence students’ reading performance, and to determine the mediating effect of students’ metacognitive awareness. The participants were teachers and students from TOEFL training institutions in Henan, China. A cross-sectional research design was adopted, and data were collected through questionnaires. The findings indicated that students’ metacognitive awareness plays a significant mediating role between teachers’ reading strategies and students’ reading performance. However, this mediating effect was found to be negative, suggesting that teachers’ reading strategies did not enhance students’ metacognitive awareness. On the contrary, these strategies may have inadvertently hindered its development, thereby exerting an indirect negative impact on students’ reading performance. These results carry important implications not only for improving TOEFL preparation but also for advancing the broader practice of English reading instruction.

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)0.001
metaresearch head score (Gemma)0.007
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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.369
Teacher spread0.353 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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