Moving Towards Sustainable Policy and Practice – A Five Level Framework for Online Learning Sustainability | Progresser vers des politiques et des pratiques durables : un cadre à cinq niveaux pour un apprentissage en ligne durable
Bibliographic record
Abstract
This paper addresses the issue of sustainability in online learning in higher education. It introduces and discusses a five-level framework for helping higher education institutions to make the transition from enterprise to sustainable policy and practice in online learning. In particular, it responds to evidence in the literature regarding the lack of sustainability in online learning in higher education. Influenced by Maslow’s hierarchy of needs, this framework is characterized by three different clusters: basic needs, institutional motivation, and stakeholders’ motivations. It is presented hierarchically within five different levels. Examples are provided for each of the levels and suggestions are given to how institutions should respond to each level.Cet article traite de la question de la durabilité dans l’apprentissage en ligne pour l’éducation supérieure. Un cadre de travail à cinq niveaux y est introduit et fait l’objet d’une discussion. Ce cadre a pour but d’aider les établissements d’enseignement supérieur à faire la transition des initiatives complexes aux politiques et pratiques durables en matière d’apprentissage en ligne.. Ce cadre répond notamment aux données probantes de la documentation concernant le manque de durabilité dans l’apprentissage en ligne pour l’éducation supérieure. Influencé par la hiérarchie des besoins de Maslow, le cadre se caractérise par trois grappes différentes : les besoins de base, la motivation de l’établissement et les motivations des intervenants. Il est présenté de façon hiérarchique, en cinq niveaux différents. Des exemples sont fournis pour chacun des niveaux, et des suggestions sont offertes sur la manière dont les établissements devraient réagir à chaque niveau.
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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 | 0.022 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.010 | 0.054 |
| Scholarly communication | 0.030 | 0.028 |
| Open science | 0.004 | 0.016 |
| Research integrity | 0.011 | 0.010 |
| Insufficient payload (model declined to judge) | 0.006 | 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".