Bibliographic record
Abstract
A technology survey was conducted in a small British Columbia urban school district. The objective was to determine the districts' elementary teachers' support needs, beliefs, and technology adoption stage with regard to the integration of technology in their classrooms. From the data collected, I have provided an additional source of information that could enhance my district's future technology plans. Specifically, the data provide additional information on how the elementary teachers in the District believe the integration of technology can be supported in this District. Past research has found numerous interconnected factors that influence the level of integration of technology in today's classrooms. The analysis of the survey responses indicated that in this District elementary teachers most frequently identify their level of technology adoption at level 5 (adaptation to other contexts), recognize there is a need for a school-based technology support person, and that the teachers need to experiment with technology-enhanced curriculum before they are comfortable with it. The teachers have the technology skills and believe in its usefulness to foster student success however they lack the knowledge to integrate technology throughout the curriculum. The results from the survey suggest that future district technology plans incorporate professional development activities and support structures that recognize their elementary teachers' identified needs, beliefs, and present adoption level in order to encourage the integration of technology in the elementary curriculum.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".