Technology Integration Preparedness and its Influence on Teacher-Efficacy
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 inquiry has identified the establishment of positive self-efficacy beliefs as an important component in the overall process of successfully preparing new teachers for the classroom. Similarly, in-service teachers who reported high levels of efficacy for teaching confirmed feeling confident in their ability to design and implement enriching instructional experiences. This article presents findings from a quantitative, descriptive study regarding teacher-efficacy related to technology integration. Utilizing a six-point Likert-type survey with an open-ended question, the research instrument was administered to a sample of approximately 350 pre-service and in-service teachers within the Province of Nova Scotia, with a response rate of 48%. Analysis of quantitative research findings illustrated no statistically significant difference between the pre-service and in-service teachers’ perceptions regarding their preparedness to integrate technology into their teaching. However, responses to the open-ended questions revealed examples from practice where teachers from both segments of the sample experienced feelings of low self- efficacy related to technology 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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