Implementing Investigative Labs and Writing Intensive Reports in Large University Physics Courses
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Undergraduate physics programs are increasingly facing pressure from university and college administration, industry, and funding agencies to improve training of our undergraduates. Increasingly, tertiary institutions have redefined their graduate profiles and mission statements to encompass more than just content knowledge, including skills that will help students succeed in today’s fast-paced world. Many physics departments have started to incorporate the results of physics education research and cognitive science, by adopting more active pedagogies. Student Centered Active Learning Environment with Upside-down Pedagogies (SCALE-UP) is one such educational innovation that has spread widely around the United States and abroad. While initially developed for large-enrollment university physics courses, the approach is being used in a variety of disciplines and class sizes so the acronym has evolved to reflect this. SCALE-UP integrates the lab, “lecture,” and tutorial sections of the course in a reformed classroom to allow large-enrollment university courses to benefit from interactive instruction. This article explains how the University of Auckland developed more open-ended, resourceful lab activities to be completed by large classes that enhance understanding of physics while developing transferable writing-related and critical thinking skills.
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.
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 | 0.005 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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