Design Evaluation of a Simulation for Teacher Education
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
Recent calls to improve the quality of education in schools have drawn attention to the importance of teachers’ preparation for work in classroom settings. Although the practicum has long been the traditional means for pre-service teachers to learn and practice classroom teaching, it does not always offer student teachers the time, safe practice experiences, repetition, or extensive feedback needed for them to gain adequate knowledge, skills, and confidence. Well-designed simulations can augment the practicum and address these gaps. This study evaluated the design of simSchool (v.1), an online simulation for pre-service teachers, using student teachers’ ratings of selected factors, including realism, appropriateness of content and curriculum, appropriateness for target users, and user interaction. Based on these ratings, the study identified strengths and weaknesses, and suggested improvements for the software. Participant ratings varied considerably but indicated that certain aspects of the simulation, such as its educational value, classroom challenges, and simulated student characteristics, were moderately well received. However, user interface navigation and the range and realism of simulated teacher–student interactions should be improved.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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