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Record W2162107240 · doi:10.1558/cj.v24i1.59-75

A Comparison of Chat Room Productivity

2007· article· en· W2162107240 on OpenAlexaboutno aff
Robert Sanders

Bibliographic record

VenueCALICO Journal · 2007
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsClass (philosophy)Task (project management)VocabularyChat roomQuarter (Canadian coin)Duration (music)Online chatMathematics educationPsychologyProductivityComputer scienceMedical educationWorld Wide WebThe InternetArtificial intelligenceLinguisticsMedicineEngineering

Abstract

fetched live from OpenAlex

Language production of Spanish students using synchronous CMC (chat) during class time was compared with that of students meeting outside of class. The study included about 100 participants enrolled in 10 sections of a first-quarter Spanish course at a US university. Students in the control group spent 30 minutes of their weekly class time in computer labs completing a chat room assignment. Students in the experimental group planned their own schedules for meeting 30 minutes each week, outside of class time, in chat rooms. Transcripts of the chat sessions were analyzed for duration, turns, words, vocabulary, socially appropriate comments, and comments off task. Production was greater when students met with their own work groups outside of class. The implication of the study is that greater student collaboration and responsibility result in greater production while conserving class time and technology resources.

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)0.003
metaresearch head score (Gemma)0.021
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.021
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.085
GPT teacher head0.344
Teacher spread0.258 · 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

Citations21
Published2007
Admission routes1
Has abstractyes

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