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Record W7118120959 · doi:10.23977/aetp.2025.090617

A Study on the Relationship between Inner Speech, Oral Learning Strategy, and Speaking Anxiety of English Major College Students

2025· article· W7118120959 on OpenAlexvenueno aff
Kaijie Zhang, Xin Zhao

Bibliographic record

VenueAdvances in Educational Technology and Psychology · 2025
Typearticle
Language
FieldPsychology
TopicCommunication in Education and Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsAnxietyPublic speakingSelf-efficacy

Abstract

fetched live from OpenAlex

This study investigated the use of inner speech among English majors and its relationship with oral learning strategy and speaking anxiety. Using a mixed-methods approach, 80 first-year English majors from a university completed questionnaires, and semi-structured interviews were conducted with 3 of these students. The findings revealed that: (1) Students' overall frequency of inner speech use was at a moderate to high level, with evaluative/motivational inner speech being the most frequent and the presence of other voices the least frequent; (2) The overall frequency of inner speech use showed moderately significant positive correlations with both the frequency of oral learning strategy (r=0.318) and the level of speaking anxiety (r=0.328). This research provides guidance for encouraging students to use positive inner speech, optimizing learning strategies, alleviating anxiety, and designing targeted teacher interventions.

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)0.004
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.070
GPT teacher head0.480
Teacher spread0.410 · 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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