Relationships in the Flipped Classroom
Bibliographic record
Abstract
This study examines the effectiveness of flipped classrooms in chemistry, and identifies relationships as a major factor impacting the success of flipped instruction methods. Examination of student interview data reveals factors that affect the development of peer-peer, peer-peer leader, and peer-expert relationships in first-year general chemistry and second-year organic chemistry flipped classrooms. Success was measured in terms of student perceptions of the effectiveness of the instruction, as well as student academic development. Furthermore, analysis of research participant interviews reveals that academic reading circles, open-response multiple-attempt group quizzes, and peer leaders are important elements of a text-centric flipped approach at a small-classroom, commuter-campus university. Student reflections and classroom observations provide further support for these conclusions. Cet étude examine l’efficacité des salles de classe inversées en chimie et identifie la création de liens en tant que facteur important qui affecte la réussite des méthodes d’instruction inversée. L’examen des données provenant d’entrevues avec les étudiants révèle les facteurs qui affectent le développement des rapports d’étudiant à étudiant, d’étudiant à leader et d’étudiant à expert dans un cours inversé de chimie générale de première année et dans un cours de chimie organique de deuxième année. La réussite a été mesurée en termes de perceptions des étudiants de l’efficacité de l’instruction, ainsi que du développement académique des étudiants. De plus, l’analyse des entrevues des participants à la recherche révèle que les cercles de lecture universitaires, les tests de groupes à essais multiples et à réponses ouvertes, ainsi que les leaders de groupes sont des éléments importants d’une approche inversée centrée sur un texte en petite salle de classe, dans une université de banlieusards. Les réflexions des étudiants et les observations en salle de classe soutiennent également ces conclusions.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".