Innovative Practices for Innovators: Walking the Talk Online Training for Online Teaching
Bibliographic record
Abstract
When e-learning companies initiate changes to learning opportunities for students, it is incumbent upon them to also change the learning opportunities for those expected to teach with their products. In other words, e-learning companies must learn to ‘walk the talk’ and rethink the traditional training format for site-based inservice, training and conference presentation. It is imperative that the teachers and instructors providing online learning be afforded the same learning experiences they are expected to provide students. This paper reports on inservice opportunities provided by Odyssey Learning Systems Inc. (Odyssey) and critically assesses how that training mirrored the learning environment created through use of its product in educational settings with students (Odyssey Learning Systems is a privately owned Canadian company that develops computer-managed learning solutions, supports development and distribution of content for its software Nautikos™ and provides technical and professional support for customers and learning sites. There are currently over 200 sites operating around the world serving educational, corporate and non-profit organizations. Odyssey is headquartered in Vancouver, British Columbia, Canada with subsidiary offices in Saskatchewan and Ontario.). In short, did the company model what it preached about its own software? In the case study presented, it is the thesis of the paper that Odyssey functioned as a learning organization and modeled the type of learning experiences for its clients it intends its clients to provide for their students. It is a further thesis of the paper that changes to a learning environment provided through technology will not occur until teachers and instructors are provided the same opportunities to learn with technology they are expected to offer their students.
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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 | 0.016 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.014 | 0.015 |
| Scholarly communication | 0.020 | 0.018 |
| Open science | 0.003 | 0.024 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.014 | 0.004 |
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".