Navigating connection: Exploring how Ontario elementary teachers cultivate relationships in synchronous grade 7 and 8 online classrooms
Bibliographic record
Abstract
Synchronous online elementary learning has evolved as an educational option within public school boards in Ontario after the emergency online learning during the Covid-19 global pandemic of 2020. The ongoing success of this mode of learning relies on teachers who are able to establish trust and nurture relationship building in an online environment. This phenomenological study explores the methods utilized by five grade 7 and 8 teachers to establish rapport and connections between themselves and their students within their synchronous online classrooms during non-emergency learning in 2022-2023 and 2023-2024. Data was obtained through semi-structured interviews, and a thematic analysis was used to generate four themes: developing intentional connections, building digital communities, teacher authenticity, and learning online as a safe space. The findings outline the teaching skills and perceptions shared by the participants, as well as how these teachers considered complex student needs and navigated technology when teaching synchronously in online spaces with grade 7 and 8 students. Synchronous online learning continued to be offered by numerous elementary school boards in Ontario for the 2024-2025 school year. With increased accessible and reliable technology, options other than in-person learning may be more appealing for families as a choice for their children's education. This study has implications in assisting future educators in establishing effective online pedagogy and utilising synchronous formats to establish relational, equitable, inclusive, and safe online learning spaces.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.006 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".