Promoting Reflective Physics Teaching Through the Use of Collaborative Learning Annotation System
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
Effective physics teaching requires extensive knowledge of physics, relevant pedagogies, and modern educational technologies that can support student learning. Acquiring this knowledge is a challenging task, considering how fast modern technologies and expectations of student learning outcomes and of teaching practices are changing Therefore 21st-century physics teachers should be supported in developing a different way of thinking about technology-enhanced physics teaching and learning. We call it Deliberate Pedagogical Thinking with Technology, and base it on the original Pedagogical Content Knowledge and Technological Pedagogical Content Knowledge frameworks. However, unlike the two aforementioned frameworks, the Deliberate Pedagogical Thinking with Technology emphasizes not only teachers’ knowledge, but also their attitudes and dispositions about using digital tools in order to support student learning. This paper examines how an online system that allows an ongoing discussion of videos uploaded on it by the students can support reflection in physics teacher education. Examples of using such a system in physics teacher education and teacher-candidates’ feedback on their experiences with it are also 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.
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 | 0.003 | 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 | 0.002 |
| 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