The Evaluation of a Workshop to Promote Interactive Lecturing
Bibliographic record
Abstract
BACKGROUND: The lecture is the most widely used method of teaching in medical education. Although effective lecturing has been described in the literature, many question whether problem-solving skills or attitudes can be transmitted using the traditional lecture. Introducing interactive techniques can promote learner participation and, as a result, can lead to a higher level of learning. This article assesses the effectiveness of interactive learning. DESCRIPTION: A 4-hr workshop has been offered for 4 consecutive years to faculty members in the Faculty of Medicine at McGill University to allow participants to explore interactive techniques and incorporate them into their lectures. For this study, an evaluation was conducted of the workshop given in Spring 1996. The experimental group consisted of the first 60 faculty members to register for the workshop, and the comparison group comprised the 40 individuals on the waiting list. Three instruments were used in the evaluation. An immediate postworkshop questionnaire was completed by the participants. Six months after the session, a 6-month postworkshop questionnaire was completed by the experimental and comparison groups that explored the use of interactive lecturing techniques since the workshop. In addition, 23 individuals from the experimental group and 14 from the comparison group were videotaped 6 months after the session and were scored on a videotape observational grid by an independent rater. EVALUATION: Overall, the workshop was deemed very useful by the majority of the participants. On the 6-month postworkshop questionnaire, the only difference found in the demographic data between the 2 groups was in the number of years of teaching experience. The experimental group had given more interactive lectures over the past 6 months and had used more audience responses, certain types of questions, audience surveys, live interviews, verbal and written cases, and study guides. From the videotape observational data, the experimental group scored higher in questioning and engaging the audience, and in using nonverbal gestures. As well, this group received higher ratings for their interactivity and for the students' responsiveness. CONCLUSIONS: Interactive lectures can increase student participation and involvement in the large class lecture. This 4-hr workshop, designed to promote the use of interactive lecturing techniques, can be considered successful based on self-reports from participants as well as from observational data.
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 | 0.015 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".