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Public Internet Forums: Can They Enhance Argumentative Writing Skills of Second Language Learners?

2012· article· en· W2021852342 on OpenAlex
Mathy Ritchie, Catherine Black

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueForeign Language Annals · 2012
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsArgumentativeThe InternetCompetence (human resources)Set (abstract data type)PsychologyPedagogyLinguistic competencePublic universityIntercultural competenceMathematics educationLinguisticsComputer scienceWorld Wide WebPolitical scienceSocial psychology

Abstract

fetched live from OpenAlex

Abstract Improving university students’ writing skills is always a challenge. In a third‐year French composition course, the researchers introduced the use of public Internet discussion forums to see if that would help achieve the argumentative writing skills goals that were set for this study. The results show that participation in the forums had a positive influence on students’ argumentative skills. The forums forced them to choose a topic, read about it, obtain different points of view, and develop their own, therefore entering a community of practice where language accuracy was important. Students felt that it was beneficial to their intercultural competence and that it had a positive impact on their confidence to use their second language because they were able to interact with native speakers.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.204
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.000

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 head0.044
GPT teacher head0.303
Teacher spread0.259 · 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