Using a Web-Based Quiz Game as a Tool to Summarize Essential Content in Medical School Classes: Retrospective Comparative Study
Bibliographic record
Abstract
BACKGROUND: Kahoot! is a web-based technology quiz game in which teachers can design their own quizzes via provided game templates. The advantages of these games are their attractive interfaces, which contain stimulating music, moving pictures, and colorful, animated shapes to maintain students' attentiveness while they perform the quizzes. OBJECTIVE: The aim of this study was to evaluate the use of Kahoot! compared with a traditional teaching approach as a tool to summarize the essential content of a medical school class in the aspects of final examination scores and the perception of students regarding aspects of their learning environment and of process management. METHODS: This study used an interrupted time series design, and retrospective data were collected from 85 medical students. Of these 85 students, 43 completed a Kahoot! quiz, while 42 students completed a paper quiz. All students attended a lecture on the topic of bone and joint infection and participated in a short case discussion. Students from both groups received the same content and study material, with the exception that at the end of the lesson, students in the Kahoot! group completed a quiz summarizing the essential content from the lecture, whereas the other group received a paper quiz with the same questions and the teacher provided an explanation after the students had finished. The students' satisfaction was evaluated after the class, and their final examination was held 2 weeks after the class. RESULTS: The mean final examination score in the Kahoot! group was 62.84 (SD 8.79), compared to 60.81 (SD 9.25) in the control group (P=.30). The students' satisfaction with the class environment, learning process management, and teacher were not significantly different between the 2 groups (all P>.05). CONCLUSIONS: In this study, it was found that using Kahoot! as a tool to summarize the essential content in medical school classes involving a lecture and case discussion did not affect the students' final examination scores or their satisfaction with the class environment, learning process management, or teacher.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".