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Record W1489731915 · doi:10.21432/t26w2k

“We just disagree:” Using deliberative inquiry to seek consensus about the effects of e-learning on higher education

2008· article· en· W1489731915 on OpenAlexvenueno aff
Jennifer H. Kelland, Heather Kanuka

Bibliographic record

VenueCanadian Journal of Learning and Technology · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsnot available
Fundersnot available
KeywordsEducational technologyHigher educationElectronic learningEmerging technologiesPedagogyPsychologySociologyPolitical scienceComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Building on the results of a prior study, the purpose of this qualitative study was to further explore where there is agreement on the effects of e-learning technologies in higher education learning experiences. The results confirm that (1) there are many varied and polarized perspectives about e-learning, and each position should be carefully considered by policymakers and administrators concerned with implementing e-learning technologies; (2) it is unlikely that e-learning experts will ever reach consensus on the effects of e-learning technologies within educational contexts; and, (3) the use of e-learning technologies in higher education will continue to vary based on subject matter, instructors, institutions, contexts, availability of technology and various other factors—not the least of which are the purpose of the learning activities and the epistemological beliefs about higher education. The diversity of opinions that currently exist does not make one view more correct or superior to another. Résumé: Construisant sur les résultats d’une étude antérieure, le but de cette étude qualitative était d’explorer plus à fond s’il y avait consensus sur les effets des technologies de l’eLearning dans les expériences d’apprentissage aux cycles supérieurs. Les résultats confirment que 1) il y a plusieurs perspectives variées et polarisées sur le eLearning, et chaque point de vue devrait être sérieusement considéré par les administrateurs et les rédacteurs de politiques concernés par l’implantation des technologies du eLearning, 2) il est peu probable que les experts en eLearning en arriveront jamais à un consensus sur les effets des technologies du eLearning dans un contexte éducationnel, et 3) l’utilisation des technologies du eLearning aux cycles supérieurs continuera de varier en fonction de la matière, des formateurs, des institutions, des contextes, de la disponibilité de la technologie et d’autres facteurs. Le moindre de ces facteurs n’est pas le but des activités d’apprentissage et les croyances épistémologiques à propos de l’éducation universitaire. La diversité des opinions qui existent présentement ne privilégie pas un point de vue en particulier.

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 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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.830
Threshold uncertainty score0.821

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.033
GPT teacher head0.327
Teacher spread0.294 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations4
Published2008
Admission routes1
Has abstractyes

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