Redesigning a Large Lecture Course for Student Engagement: Process and Outcomes
Bibliographic record
Abstract
Using an action-research approach, a large-lecture science course (240 students) was redesigned to improve student engagement in the areas of active and collaborative learning, faculty-student interaction and level of academic challenge. This was mainly achieved through the addition of a half-semester long group project, which replaced half of the lectures and the final exam. The course redesign did not result in more hours spent on teaching and teaching-related activities (grading, assessment preparation, lecturing, lecture preparation) for the instructor – although the redesigned course requires the support of teaching assistants for the project component. Data on students’ perceptions of the modified course and the frequency to which they participated in the engagement activities were collected using the Classroom Survey of Student Engagement (CLASSE). The majority of students reported high levels of engagement in most of the intended areas and were comfortable with the new class design. The CLASSE data also helped identify areas where intended engagement levels were not met. These areas are the focus for future course development and action research questions. Utilisant une approche de type recherche-action, un cours de science offert dans un grand auditorium (240 étudiants) a été reconfiguré afin d’amener les étudiants à s’engager davantage dans un apprentissage actif et collaboratif ainsi que dans leur interaction professeur-étudiants et à relever un défi de nature académique. Pour ce faire, la moitié des cours magistraux ainsi que l’examen final ont été remplacés par un projet de groupe. La reconfiguration du cours ne s’est pas traduite par une augmentation des heures d’enseignement ou des activités liées à l’enseignement (notation, préparation des évaluations, exposé magistral, préparation de l’exposé magistral) – bien qu’elle ait nécessité le soutien des assistants à l’enseignement pour la composante projet de groupe. Les chercheurs ont effectué un sondage en classe afin de recueillir des données sur la perception des étudiants à propos du cours modifié et sur la fréquence à laquelle ils ont participé aux activités favorisant leur engagement. La majorité des étudiants a rapporté un niveau élevé d’engagement dans la plupart des domaines souhaités et a déclaré se sentir à l’aise avec le cours reconfiguré. Les données du sondage ont également permis d’identifier les domaines dans lesquels le niveau d’engagement souhaité n’était pas atteint. Une nouvelle version du cours de même que les questions posées dans le cadre d’une autre recherche-action tiendront principalement compte de ces domaines.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.018 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".