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Record W2108722309 · doi:10.5539/elt.v5n4p57

A Qualitative Study of ESL College Students’Attitudes about Computer-Assisted Writing Classes

2012· article· en· W2108722309 on OpenAlexvenueno aff
Waleed A. Ghandoura

Bibliographic record

VenueEnglish Language Teaching · 2012
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsBrainstormingPsychologyClass (philosophy)Mathematics educationQualitative researchQualitative propertySample (material)Second language writingPedagogyComputer scienceSecond languageLinguistics

Abstract

fetched live from OpenAlex

The purpose of this qualitative study was to examine a sample of 13 English as a second language (ESL) students’ attitudes about a computer-aided composition (WebCT) class. Participants were enrolled in an introductory writing course. Data from student diaries revealed that students enjoyed and valued the WebCT course and that the course facilitated their acquisition of writing skills. Classroom observations yielded information about the structure of the class in addition to instructor activities, including the success of repeating key ideas and brainstorming about topics in class. Interviews with the students revealed that they thought computers made the acquisition of writing skills easier and faster. Also, students valued the feedback from instructors and fellow classmates alike.

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)0.010
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.010
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0090.007
Scholarly communication0.0040.003
Open science0.0020.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.042
GPT teacher head0.368
Teacher spread0.327 · 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 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

Citations12
Published2012
Admission routes1
Has abstractyes

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