Considerations for using personal Wi-Fi enabled devices as “clickers” in a large university class
Why this work is in the frame
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Bibliographic record
Abstract
Interactive student response systems, commonly referred to as clickers, have increased in popularity in higher education classrooms as a means to improve engagement and enhance learning. Clicker systems come with handheld devices as well as a radio frequency receiver. A Wi-Fi connection to the receiver is possible, enabling students to use their personal smartphones, tablets, or laptops instead of the handheld device. The objective of this study was to determine the feasibility of students using their personal Wi-Fi enabled devices as clickers in a large university class. In addition, we sought to elicit student perceptions of clicker use in general. Overall, the majority of students preferred using their personal devices, thus saving several minutes of class time in distribution and collection. Students gave very positive feedback on the use of clickers; however, they did not like that clickers could be used to track attendance and participation.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it