Art, music, and play as a teaching aid: applying creative uses of Universal Design for Learning in a prison science class
Bibliographic record
Abstract
Science, technology, engineering, and mathematics (STEM) subjects can be rigid in their teaching structure, creating barriers to education for students with more complex learning needs. As a result, there has been an increased need for compassionate pedagogy and adaptive education practices to provide multi-modal learning experiences—often referred to as Universal Design for Learning (UDL). Here, we outline our work in teaching science in prison that applies UDL principles to create different educational access points which are not solely focused on rote learning and reading text (which some students struggle with). We use creative practices, including art, music, and play, as a teaching aid for science subjects such as climate change, sleep, and space exploration. The key findings here being that the application of UDL principles combined to produce a positive classroom experience in a science class—with students feeling more that science is for everyone of every neurotype. Although our work here is tailored to the restrictive prison environment, the application of its core principles to education are fundamental practices that could be beneficial to a wide audience.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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 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".