Take Out Your Cell Phones - Class is Starting
Bibliographic record
Abstract
Traditionally, cell phones have been considered disruptive to classroom learning. Two years ago, a survey of students in a large first year design course indicated that 88% of students possessed cell phones in the classroom. Instead of trying to enforce acell phone ban, and fight a losing battle, we decided to use the cell phones to our pedagogical advantage. Previously, student interaction in the classroom was a challenge, due to a large class of students in a singlelecture theater. A primary issue was the inability of all except a few students with booming voices to ask questions. Informed primarily by a student design team (from the very course being discussed), we implemented a simple and inexpensive system that allowed students to use their cell phones in the classroom to send questions via Short Message Service (SMS), commonly referred to as “text messages”, to the instructor at the front of the classroom This system has been piloted through its first year of full implementation. Quantitative data on the usage of the system, student and instructor impressions of the system, and future work will be discussed.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".