“Terrorism plus Canada in the 1960’s equals hell frozen over”: Learning about the October Crisis with computer technology in the Canadian classroom
Bibliographic record
Abstract
This study investigated the role and impact of a digital history program (the Virtual Historian©) on students’ historical thinking and reasoning about a controversial episode in Canadian history. The purpose was to examine whether the use of the Virtual Historian©, a web-based inquiry program to teach Canadian history, improves the learning of a key episode in the school curriculum (French-English relations and the October Crisis, 1970). Using a quasi-experimental design, two Ontario Grade 10 classes were assigned to a treatment group (Virtual Historian©) and comparison group (classroom lessons) on the topic. Findings indicate that using the Virtual Historian© can significantly increase students’ understanding of the subject-matter and their ability to think and write historically more than classroom inquiry-based lessons. Résumé : Cet article présente les résultats d’une étude quasi-expérimentale menée auprès de deux groupes d’élèves ontariens de la 10e année inscrit au cours d’histoire du Canada. L’étude avait pour but d’examiner le rôle et l’impact des technologies de l’information et des communications (TIC), et plus particulièrement d’un nouveau didacticiel en histoire canadienne, l’historien virtuel©, sur l’apprentissage d’un épisode marquant de l’histoire scolaire (la Crise d’octobre, 1970). Les résultats de l’étude indiquent que les élèves du groupe expérimental (l’historien virtuel©) ont développé une meilleure compréhension de l’histoire et de la Crise d’octobre que ceux du groupe de comparaison (enseignement en classe).
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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".