Assessing the Impact of Weekly In-class Pop Quizzes on Student Performance in a Fundamental ECE Course
Bibliographic record
Abstract
This work evaluates the effect of weekly in-class pop quizzes on the learning outcomes of ECE sophomore-level undergraduate students in a signals & systems course at the University of Illinois Urbana-Champaign.The quizzes pursued two goals: to increase class attendance and to motivate students to keep up with the material in a timely manner.While the quizzes may help achieve both goals, in-class pop quizzes may also result in the elevation of students' stress as well as they may negatively impact the students' attitude toward the instructor.We analyze the overall impact of the quizzes on the students' final grades from multiple perspectives.In addition, we examine the students' opinion about the quizzes and the instructor.Finally, we evaluate if the quizzes encouraged students to attend lectures and stay on top of the material.Our findings show that final grades are marginally negatively affected by the quizzes.However, the main reason for that is not the quizzes themselves but the large number of students (∼27%) who missed multiple quizzes.In fact, the quizzes resulted in improving the final grades for those students who attended most of them.In addition, our results indicate that the students agree that quizzes helped them from multiple perspectives: encouraging attendance, promoting frequent review of course material, and preparing them for exams.Despite that, attendance decreased significantly toward the end of the semester.Our findings also demonstrate that students experienced a high level of stress due to quizzes.However, no evidence was found that the quizzes had a significant negative effect on the students' attitude toward the instructors.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".