“We just disagree:” Using deliberative inquiry to seek consensus about the effects of e-learning on higher education
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.118 | 0.152 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.011 | 0.031 |
| Scholarly communication | 0.013 | 0.017 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".