Student teacher learning with Ozobots and Makey Makeys during a workshop and field experience
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
This pilot project examines the experiences of a small sample (n = 4) of elementary pre-service teachers (PSTs) as they designed and attempted to implement a series of short lessons, or mini-units, using Ozobots or Makey Makeys during their field experience. Results indicated that, despite the fact that none of the PSTs were able to deliver their mini-units as originally planned, all were able to gain comfort with the tools, recognise their adaptability and articulate how they might be used in future practice. An unanticipated finding, PSTs also reported on cooperating teachers’ (CTs) technological learning, with CTs relying heavily on PSTs for general technological training during the COVID-19 pandemic. These results have important implications regarding PST training and field experiences, namely, providing PSTs with the opportunity to see technology use enacted during their field experiences and matching PSTs with CTs interested in and trained on technological integration.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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