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Asynchronous and synchronous online teaching: Perspectives of Canadian high school distance education teachers

2010· article· en· W1927480589 on OpenAlexafffundabout
Elizabeth Murphy, María A. Rodríguez‐Manzanares, Michael K. Barbour

Bibliographic record

VenueBritish Journal of Educational Technology · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsMemorial University of NewfoundlandUniversité Laval
FundersCanadian Council on Learning
KeywordsAsynchronous communicationAffordanceComputer scienceTroubleshootingOnline teachingDistance educationMathematics educationTeaching methodComputer-mediated communicationOnline discussionPedagogyMultimediaPsychologyWorld Wide WebThe InternetHuman–computer interactionTelecommunications

Abstract

fetched live from OpenAlex

Abstract This paper presents the results of an inductive, interpretive analysis of the perspectives of 42 Canadian high school distance education (DE) teachers on asynchronous and synchronous online teaching. The paper includes a conceptual overview of the affordances and constraints of each form of teaching. Findings provided insight into the following aspects of asynchronous and synchronous online teaching: degree of use; the tools used; the contexts in which each occur; students' preferences; and limitations. Pedagogy emerged as more important than media for both asynchronous and synchronous online teaching. Synchronous online teaching relied on teacher‐ rather than student‐centred approaches. Asynchronous online teaching provided support for self‐paced, highly independent forms of secondary DE supplemented by synchronous online teaching for answering questions and troubleshooting.

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)0.005
metaresearch head score (Gemma)0.009
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 score0.128
Threshold uncertainty score0.285

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.004
Science and technology studies0.0260.011
Scholarly communication0.0080.002
Open science0.0020.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0050.000

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 head0.006
GPT teacher head0.289
Teacher spread0.284 · 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

Citations279
Published2010
Admission routes3
Has abstractyes

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