The effectiveness of web-delivered learning with aboriginal students: Findings from a study in coastal Labrador
Bibliographic record
Abstract
This paper outlines the findings of a study that explores perspectives of e-learning for aboriginal students in five coastal communities in Labrador, Canada. The rural nature of many communities in the province of Newfoundland and Labrador, coupled with a dramatically declining enrollment, has resulted in expanding use of e-learning as a means to provide quality high school curriculum. Recently, a Community University Research Alliance partnered with stakeholders to explore the success of e-learning in the province. Through one of the projects of this alliance, the authors examined the success of this mode of delivery for aboriginal students from the perspective of the students themselves, as well as the perspective of parents and educators. Additionally, student performance was examined in comparison to provincial peers. A wealth of data emerged which affords insights into factors that support and hinder e-learning in coastal areas and also informs educators about the diverse learning characteristics and needs of aboriginal students. As Canadian educators are increasingly challenged to address achievement issues that continue to characterize aboriginal populations, this study offers important data on the viability of e-learning as a mode of curriculum delivery. Résumé : Cet article présente les résultats d’une étude qui explore les perspectives de l’apprentissage en ligne pour les élèves autochtones dans cinq collectivités côtières du Labrador, Canada. Le caractère rural d’un grand nombre de collectivités de la province de Terre-Neuve-et-Labrador, jumelé à une baisse spectaculaire de la scolarisation, a mené à une utilisation accrue de l’apprentissage en ligne comme solution permettant d’assurer un curriculum de qualité au secondaire. Récemment, une alliance de recherche université-communauté a travaillé de pair avec les intervenants afin d’étudier les résultats de l’apprentissage en ligne dans la province. Grâce à l’un des projets de cette alliance, les auteurs ont examiné le succès de ce mode de prestation auprès d’élèves autochtones du point de vue des élèves eux-mêmes, ainsi que du point de vue de leurs parents et de leurs éducateurs. En outre, le rendement des élèves a été comparé à celui de leurs pairs au niveau de la province. Une foule de données en sont ressorties, ce qui permet de mieux comprendre les facteurs qui favorisent et qui entravent l’apprentissage en ligne dans les zones côtières; ces données informent également les éducateurs sur la diversité des caractéristiques et des besoins d’apprentissage des élèves autochtones. Les éducateurs canadiens sont de plus en plus mis au défi de trouver un moyen de surmonter les problèmes de réussite scolaire qui continuent de caractériser les populations autochtones, et cette étude leur fournit des données importantes sur la viabilité de l’apprentissage en ligne comme mode de prestation du curriculum.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".