Gagne's and Laurillard's Models of Instruction Applied to Distance Education: A theoretically driven evaluation of an online curriculum in public health
Bibliographic record
Abstract
<P class=abstract>This article presents an overview of the instructional models of Gagne, Briggs, and Wager (1992) and Laurillard (1993, 2002), followed by student evaluations from the first year of an online public health core curriculum. Both online courses and their evaluations were developed in accordance with the two models of instruction. The evaluations by students indicated that they perceived they had achieved the course objectives and were generally satisfied with the experience of taking the courses online. However, some students were dissatisfied with the feedback and learning guidance they received; these students&rsquo; comments supported Laurillard&rsquo;s model of instruction. Discussion captured in this paper focuses on successes of the first year of the online curriculum, suggestions for solving problem areas, and the importance of the perceived relationship between teacher and student in the distance education environment.</P>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".