Examining the Use of Worked Example Video Podcasts in Middle School Mathematics Classrooms: A Formative Analysis / Étude sur l'utilisation de podcasts d’exemples pratiques dans des classes de mathématiques à l'école secondaire de premier cycle
Bibliographic record
Abstract
Video podcasts allow students to control when, where, and what they learn, as well as the pace of learning. Considerable research has been conducted in higher education on video podcasts use, but not in middle schools (grades six to eight). This study investigated the use of worked example video podcasts in mathematics classrooms with students 11 to 13 years old. One hundred thirty-six pupils individually watched video podcasts designed to teach basic mathematics concepts. Students were positive about the quality of worked example video podcasts and appreciated the step-by-step, easy to follow explanations, diagrams, and being able to control the pace of learning. Learning performance increased significantly after using worked example video podcasts. There were no gender or grade level differences in attitudes toward worked example video podcasts or learning performance. Les podcasts vidéo permettent aux étudiants de contrôler quand, où, et ce qu'ils apprennent, ainsi que le rythme d'apprentissage. Un grand nombre de recherches ont été menées sur l'utilisation de podcasts vidéo dans l'enseignement supérieur, mais pas dans les écoles secondaires de premier cycle (classes de sixième à huitième). Cette étude a examiné l'utilisation des podcasts vidéo d’exercices pratiques dans des classes de mathématiques avec des élèves de 11 à 13 ans. Cent trente-six élèves ont regardé individuellement des podcasts vidéo conçus pour enseigner des concepts mathématiques de base. L’évaluation des élèves a été positives quant à la qualité de podcasts vidéo et ils ont apprécié les explications par étapes et faciles à suivre, les schémas ainsi que la possibilité de contrôler le rythme de l'apprentissage. La performance d'apprentissage s’est améliorée de manière significative après l'utilisation des podcasts vidéo. Il n'y avait de pas de différence selon le sexe ou le niveau scolaire dans les attitudes envers les podcasts vidéo ou dans la performance d'apprentissage.
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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 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".