Learning and teaching with emerging technologies: Preservice pedagogy and classroom realities
Bibliographic record
Abstract
This study was guided by the following research objectives: (1) investigating the relationship between the teacher education curriculum and field placements; (2) investigating how the technology experiences of teacher candidates in a teacher education program affect their experiences in a field placement experience; and (3) investigating situational, institutional, and/or dispositional variables that influence the integration of instructional technologies by teacher candidates in placements. Thirty-two teacher candidates in a consecutive teacher education program in Ontario completed questionnaires; additional interviews were conducted with four of these individuals. The data suggests that the participants in the required technology class were highly influenced by their faculty instructors' and mentor teachers' uses of technology, and the majority of the participants had very little experience with using technology for pedagogical and constructivist purposes. Technology integration in placements was ultimately dependent on the access and availability of resources, previous experience with available resources, technical support, and funding.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".