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Record W4391325633 · doi:10.23977/aetp.2024.080109

Literature Review on Self-efficacy and Chinese Learning Motivation of Deaf Students

2024· article· en· W4391325633 on OpenAlexvenueno aff
Yang Yuliang

Bibliographic record

VenueAdvances in Educational Technology and Psychology · 2024
Typearticle
Languageen
FieldPsychology
TopicHearing Impairment and Communication
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologySelf-efficacyMathematics educationCognitive psychologyDevelopmental psychologySocial psychology

Abstract

fetched live from OpenAlex

The 14th Five-Year Plan of Action for the Development and Improvement of Special Education emphasizes the need to promote the high-quality development of special education. As an important object of special education, the learning condition of deaf students has always been the focus of scholars' attention. In order to further meet their own learning and development needs, deaf students need to continuously improve their learning ability, improve learning strategies, improve the motivation of Chinese learning, and enhance self-efficacy. In this paper, the literature on self-efficacy and Chinese learning motivation of deaf students is systematically reviewed. Among them, the self-efficacy of deaf students includes three aspects: the learning efficacy of deaf students in primary and secondary schools, the academic self-efficacy of deaf college students and their career decision-making self-efficacy. The Chinese learning motivation of deaf students includes two parts: writing motivation, learning strategy and motivation.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.303
Threshold uncertainty score0.396

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.015
GPT teacher head0.425
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 teacher head, 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

Citations1
Published2024
Admission routes1
Has abstractyes

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