Implementing Best Practices within International Distance Education Initiatives: Lessons Learned from the Mexico-Canada Distance Education Project
Bibliographic record
Abstract
: The Open School, a division of the Open Learning Agency of British Columbia, was involved in a three-year project (1996-1998) in Mexico with the goal of providing wider access to basic education through the creation of technology-based instructional materials for basic education. This paper elaborates on the model and discusses some of the lessons learned in the design and management of collaborative, technology-based distance education and distributed learning projects. Instrumentalizando las mejores practicas en iniciativas internacionales de Educacion a Distancia En esta presentacion se tomaran en cuenta las lecciones aprendidas en el diseno y en la administracion colaborativa de proyectos a distancia, realizados entre la Open School de Canada y el Instituo Latinoamericano de la Comunicacion Educativa de Mexico. Durante esta colaboracion se empleo una version modificada del Enfoque Logico Integrado (LFA), que es un metodo integrado para la administracion y evaluacion de programa...
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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 | 0.017 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.013 | 0.007 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".