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Record W1922200387 · doi:10.19173/irrodl.v11i1.774

"Can you hear me, Hanoi?" Compensatory mechanisms employed in synchronous net-based English language learning

2010· article· en· W1922200387 on OpenAlex

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe International Review of Research in Open and Distributed Learning · 2010
Typearticle
Languageen
FieldComputer Science
TopicIntelligent Tutoring Systems and Adaptive Learning
Canadian institutionsnot available
Fundersnot available
KeywordsNet (polyhedron)Computer scienceLinguisticsArtificial intelligencePsychologyNatural language processingMathematicsPhilosophy

Abstract

fetched live from OpenAlex

writes that the ability to remove the constraints of time and place is a major hallmark of computer-mediated communication (CMC) but that it also supports real-time synchronous forms of interaction. He suggests that "synchronous technologies create a strong network bond because each of the participants must be present at the same time in order to communicate" (Ahern, 2008, p. 99). Kenning (2010, p. 6), expanding on the work of Ciekanski and Chanier (2008, p. 173) would have us view the synchrony and asynchrony as a matter of degree where "face-to-face offers greater simultaneity than audio networks, audio than textchat and text chat than a shared word processor." At Dalarna University, Sweden, we offer modes of communication at many points of Kenning's continuum with a web-based learning platform, including asynchronous document exchange and collaborative writing tools, e-mail, recorded lectures in various formats, live streamed lectures with the possibility of text questions to the lecturer in real time, textchat, and our audiovisual seminars in Marratech or Adobe Connect. Our online students live in many countries around the world and come to our online learning spaces from profoundly different physical realities, so the synchronous seminar is a shared experience that is quite separate from the physical environment in which the students find themselves.

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)0.009
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.810
Threshold uncertainty score0.885

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.002
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 head0.035
GPT teacher head0.363
Teacher spread0.328 · 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