In-service Science Teachers' Readiness of Integrating Augmented Reality
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 paper investigates the readiness degree among in-service science teachers in Ma'an Governorate for integratingaugmented reality in teaching according to Technological, Pedagogical and Content Knowledge TPACK frameworkand its domains. The study sample consisted of (60) in-service science teachers enrolled voluntary in the study. Theresearcher used descriptive statistics, ANCOVA and T-test. The data analyses revealed significant differences amongteachers' readiness in a high degree. Paired sample t-test showed female teachers' readiness higher than male teachersat all of the TPACK the domains. Results of ANCOVA revealed that experience of teachers' readiness do not differsignificantly. The study recommended the focus on integrating augmented reality within learning environments.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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