Online Teacher and On-Site Facilitator Perceptions of Parental Engagement at a Supplemental Virtual High School
Bibliographic record
Abstract
Just as they have in face-to-face courses, parents will likely play an important role in lowering online student attrition rates, but more research is needed that identifies ways parents can engage in their students’ online learning. In this research we surveyed and interviewed 12 online teachers and 12 on-site facilitators regarding their experiences and perceptions of parental engagement. Guided by the Adolescent Community of Engagement framework, our analysis found that teachers and facilitators valued parents’ engagement when parents advised students on course enrollments, nurtured relationships and communication with and between students, monitored student progress, motivated students to engage in learning activities, organized and managed students’ learning time at home, and instructed students regarding study strategies and course content when able. Teachers and facilitators also identified obstacles that parents faced when attempting to engage in their children’s online learning as well as obstacles that teachers and facilitators encountered when they attempted to support parents.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".