TiltTray: A 3D-Printed Apparatus to Teach Inclined-Plane Physics Through Smartphone Portrait-Landscape Transitions
Bibliographic record
Abstract
Today’s students are increasingly immersed in a landscape of screens and handheld digital devices through which a good deal of their interactions with the world around them are mediated. Physics educators, meanwhile, continue to rely on traditional human interactions with the physical world, such as sliding down a ramp or throwing a baseball, in order to illustrate fundamental concepts in physics. Regrettably, these interactions are decreasingly representative of the kinds of everyday activities that our students engage in, reducing their degree of engagement with the material. A new opportunity lies in the behavior of smartphones in response to sustained tilted orientations, which has for some time become a familiar mechanism of interaction between students and many of the mobile apps that they engage with on a daily basis. Here we demonstrate how a methodical investigation of this digital-era mechanism can be used to introduce the inclined plane, a standard topic in most introductory mechanics courses. We also present an open-source 3D-printed apparatus designed to support this investigation and the experiences from well over 1000 students in three different colleges.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.047 | 0.009 |
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".