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Record W1629411692 · doi:10.21432/t2g30c

Asynchronous CMC, Collaboration and the Development of Critical Thinking in a Graduate Seminar in Applied Linguistics

2005· article· en· W1629411692 on OpenAlexvenueno aff
Zsuzsanna Ittzés Abrams

Bibliographic record

VenueCanadian Journal of Learning and Technology · 2005
Typearticle
Languageen
FieldArts and Humanities
TopicDiscourse Analysis in Language Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAsynchronous communicationCritical thinkingPsychologyComputer-mediated communicationPedagogyQualitative researchMathematics educationApplied linguisticsContext (archaeology)Higher educationComputer scienceSociologyLinguisticsPolitical science

Abstract

fetched live from OpenAlex

A primary objective of graduate education, and often promoted by peer collaboration tasks, is the development of critical thinking skills. The present study compares how graduate students enrolled in a qualitative research design course in applied linguistics utilized asynchronous computer-mediated communication (ACMC) and face-to-face interactions to critique field-specific research, to design and conduct their own research projects, and to engage in professional discourse in and out of class. The analyses reveal that 1) it was impossible to measure the development of critical thinking skills within one semester, and 2) rather than ACMC serving as a spring-board for such development prior to or in collaboration with classroom exchanges, ACMC and face-to-face interactions served different social and intellectual purposes in the process of practicing critical thinking skills. While face-to-face exchanges were preferred when discussing previous research, only in the ACMC context were students willing to critique each other’s work.

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)0.013
metaresearch head score (Gemma)0.053
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 score0.013
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.053
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0030.004
Scholarly communication0.0060.004
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.259
Teacher spread0.246 · 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

Citations38
Published2005
Admission routes1
Has abstractyes

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Same venueCanadian Journal of Learning and TechnologySame topicDiscourse Analysis in Language StudiesFrench-language works237,207