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Record W1630383339 · doi:10.21432/t20k64

The Interplay of Content and Community in Synchronous and Asynchronous Communication: Virtual Communication in a Graduate Seminar

2002· article· en· W1630383339 on OpenAlexvenueaboutno aff
Richard A. Schwier, Shelly Balbar

Bibliographic record

VenueCanadian Journal of Learning and Technology · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsnot available
Fundersnot available
KeywordsAsynchronous communicationAsynchronous learningComputer scienceClass (philosophy)Computer-mediated communicationGraduate studentsDistance educationMultimediaMathematics educationSynchronous learningPedagogyTeaching methodPsychologyCooperative learningTelecommunicationsWorld Wide WebArtificial intelligence

Abstract

fetched live from OpenAlex

A group of graduate students and an instructor at the University of Saskatchewan experimented with the use of synchronous communication (chat) and asynchronous communication (bulletin board) in a theory course in Educational Communications and Technology for an eight-month period. Synchronous communication contributed dramatically to the continuity and convenience of the class, and promoted a strong sense of community. At the same time, it was viewed as less effective than asynchronous communication for dealing with content and issues deeply, and it introduced a number of pedagogical and intellectual limitations. We concluded that synchronous and asynchronous strategies were suitable for different types of learning, and what we experienced was a balancing act between content and community in our group. A combination of synchronous and asynchronous experiences seems to be necessary to promote the kind of engagement and depth required in a graduate seminar.

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)0.009
metaresearch head score (Gemma)0.019
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 score0.009
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0040.003
Scholarly communication0.0040.002
Open science0.0010.004
Research integrity0.0020.001
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 head0.029
GPT teacher head0.288
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

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

Citations89
Published2002
Admission routes2
Has abstractyes

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