A Case Study of Virtual Kindergarten Teachers in Technology-Enhanced Classrooms
Bibliographic record
Abstract
With the threat of future global pandemics and the possible necessity to mandate schools to transition to temporary online learning, it is imperative to provide kindergarten teachers with effective pedagogical practices using technological devices and resources in virtual classrooms. To address this challenge, this case study aims to discover 1) the attitudes and beliefs towards digital screen-based technologies or resources in the virtual classroom, 2) the benefits and challenges of teaching and learning in virtual kindergarten classrooms, 3) the digital screen-based technological tools or resources FDK educators are currently implementing, 4) how educators used the tools or resources to document play-based learning virtually, 5) and what do educators need to integrate technology into their virtual pedagogical practices effectively. Using semi-structured interviews from 11 early childhood educators and one teacher-researcher from virtual kindergarten classrooms in Ontario, Canada, a thematic content analysis from the typed transcripts and reflective notes was adopted to generate emerging themes. The findings demonstrated that 1) educators had a similar positive attitude towards technology in kindergarten as in other countries worldwide, 2) the benefits and challenges of virtual teaching and learning, 3) update on what types of technological devices and resources educators especially in the virtual milieu, are using, 4) and ways to support successful technology integration into virtual pedagogical practices. The findings from this study, in conjunction with other current research, provide practical recommendations for virtual kindergarten educators, parents, school boards, and policymakers.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".