Best Practices and Challenges towards Positive Parent-Teacher Relationships & Parental Involvement at the Secondary School Level
Bibliographic record
Abstract
Parental involvement in students’ education is an integral component towards achieving the highest degree of possible success (Huntsinger & Jose, 2009, p. 398). However, there is a trend towards lowered levels of parental involvement in a student’s education once they reach the secondary school level (Adams & Christenson, 2000, p. 491). The goal of this qualitative research paper was to asses what methods teachers use to involve parents in students’ secondary education, where challenges can arise, and where positive changes can be made. The data was collected using semi-structured interviews with three participants employed by Ontario secondary schools, specifically in the Peel region. These interviews revealed potential efforts that can me made towards communicating with parents, which was cited by my participants as the most important method to promote parental involvement. First, communication must be positive to successfully invite parents towards student success efforts. Second, parents will be receptive to opportunities for school involvement if they are engaged by the school community. Finally, teachers must utilize different communication practices to contact the variety of parents they will encounter. These findings suggest that teachers would benefit from further development of their skills for interacting with parents during pre-service teaching programs, as well as for the need of an increase in school specific strategies geared towards getting parents involved and knowledgeable of their children’s education.
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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 | 0.011 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.006 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".