Conceptual Analysis of Web 2.0 Technology Use to Enhance Parent–School Relationships
Bibliographic record
Abstract
Parent–school relationships contribute significantly to the quality of students’ education. The Internet, in turn, has started to influence individuals’ way social communication and most school boards in Ontario now use the Internet to communicate with parents, which helps build parent–school relationships. This project comprised a conceptual analysis of how the Internet enhances parent–school relationships to support Ontario school board administrators seeking to implement such technology. The study’s literature review identified the links between Web 2.0 technology, parent–school relationships, and effective parent engagement. A conceptual framework of the features of Web 2.0 tools that promote social interaction was developed and used to analyze websites of three Ontario school boards. The analysis revealed that school board websites used static features such as email, newsletters, and announcements for communication and did not provide access to parents for providing feedback through Web 2.0 features such as instant messaging. General recommendations were made so that school board administrators have the opportunity to implement changes in their school community with feasible modifications. Overall, Web 2.0-based technologies such as interactive communication tools and social media hold the most promise for enhancing parent–school relationships because they can help not only overcome barriers of time and distance, but also improve the parents’ desire to be engaged in children’s education experiences.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.003 |
| 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".