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Record W2122287849 · doi:10.5539/elt.v8n9p167

The Effects of CMC Applications on ESL Writing Anxiety among Postgraduate Students

2015· article· en· W2122287849 on OpenAlexvenueno aff
Supyan Hussin, Mohamed Abdullah Yahya Al Raweeh, Noriah Ismail, Soo Kum Yoke

Bibliographic record

VenueEnglish Language Teaching · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyAnxietySecond language writingWriting processEnglish languageGraduate studentsMedical educationMathematics educationPedagogySecond languageLinguistics

Abstract

fetched live from OpenAlex

This study investigates the effects of the CMC applications on the ESL/EFL writing anxiety. This is a descriptive study using a mixed-method that adopted both quantitative and qualitative approaches. Three instruments were employed to answer the research questions of the current study which are Second Language Writing Anxiety Inventory (SLWAI), Semi-structured Interview, and Documents Observation. The respondents consisted of twenty eight post-graduate ESL/EFL students who enrolled in the elective course of Computer Application in ESOL (SKBI6133) at the Faculty of Social Sciences and Humanities, School of English Language Studies, National University of Malaysia (UKM). The findings showed a significant change in their attitudes toward writing after they had engaged in writing process approach and CMC applications in the course. In addition, the respondents perceived that there was a positive effect of on their writing performance and improvement on their writing anxiety level particularly through the use of CMC applications.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.220
Threshold uncertainty score0.706

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.011
GPT teacher head0.264
Teacher spread0.254 · 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 designQualitative
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

Citations33
Published2015
Admission routes1
Has abstractyes

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