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Record W4410074605 · doi:10.33650/ijit.v1i1.3429

The Effect of Distance Education: A Meta-Analytic Assessment of Simonson's Equity Theory based on Synchronous and Asynchronous

2022· article· en· W4410074605 on OpenAlexafffund
Roger S. Bensilva

Bibliographic record

VenueInternational Journal of Instructional Technology · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsConcordia University
FundersSocial Sciences and Humanities Research Council of CanadaConcordia UniversityLouisiana State University
KeywordsAsynchronous communicationDistance educationEquity (law)Computer scienceEconometricsMathematics educationPsychologyArtificial intelligenceMathematicsPolitical scienceTelecommunicationsLaw

Abstract

fetched live from OpenAlex

Simonson, Schlosser and Hanson (1999) argue that a new theory called “equivalency theory” is needed to account for the unique features of the “teleconferencing” (synchronous) model of DE that is prevalent in many North American universities. Based on a comprehensive meta-analysis of the comparative literature of DE (Bernard, Abrami, Lou, Wozney, Borokhovski, Wallet, Wade, Fiset, & Huang, in press), we are able to assess empirically whether equivalency has been achieved in prior comparative DE research. This paper includes a brief summary of the results of the split between synchronous and asynchronous patterns of DE, and addresses the implications these data have for developing separate theories of DE for synchronous (i.e., group-based) and asynchronous (i.e., individualized) applications. We examine data based on achievement, attitude and retention outcomes and coded study features (i.e., methodological, pedagogical and media) relating to them.

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)0.197
metaresearch head score (Gemma)0.283
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.803
Threshold uncertainty score0.990

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1970.283
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0110.044
Bibliometrics0.0170.011
Science and technology studies0.0010.004
Scholarly communication0.0050.006
Open science0.0040.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.012
GPT teacher head0.371
Teacher spread0.359 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designMeta-analysis
DomainMethods
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

Citations0
Published2022
Admission routes2
Has abstractyes

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