Exploring the use of Virtual Field Trips with elementary school teachers: A collaborative action research approach
Bibliographic record
Abstract
This research examines how elementary school teachers, when supported, use Virtual Field Trips (VFTs) to address the curricula in meaningful ways. I conducted a qualitative study with six teachers, in a collaborative action research context over a six month period. The teachers, five males and one female, all taught either grade five or six and utilized Virtual Field Trips within a variety of curricula areas including science, social studies, music and language arts. In addition, the thesis examines resulting integration of technology into the regular classroom program as a product of the utilization of Virtual Field Trips. The process of collaborative action research was applied as a means of personal and professional growth both for the participants and the researcher/facilitator. By the end of the research study, all participants had learned to integrate Virtual Field Trips into their classroom program, albeit with different levels of success and in different curricula areas. The development of attitudes, skills and knowledge for students and teachers alike was fostered through the participation in Virtual Field Trips. A common concern regarding the utilization of Virtual Field Trips was the time spent locating an appropriate site that met curricula expectations. Participation in the collaborative action research process allowed each teacher to grow professionally, personally and socially. Each participant strongly encouraged the utilization of a long term project with a common area of exploration as a means for positive professional development. Implications and recommendations for future research on the utilization of Virtual Field Trips, as well as the viability of collaborative action research to facilitate teacher development are presented.
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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 | 0.035 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.009 | 0.019 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".