Establishing school-family partnerships in distance education contexts: Pedagogical engagement in isolated settings
Bibliographic record
Abstract
This investigation examines school-family partnership relationships in rural and remote settings. The study highlights the teaching-learning relationships of classroom teachers, parents as instructors/supervisors, and students as they make sense of numeracy and literacy outcomes in distance education contexts. The case study data provide insights into how the distance education provider (the school) interacts with families to facilitate young students’ learning experiences. At present, the school and the families they engage with have access to limited technological resources. This investigation considers learning engagement in these increasingly unusual settings and postulates the effect new technologies may have on pedagogical practices in the future. Cette etude examine les relations dans les partenariats ecole-famille en regions rurales et isolees. L’etude illustre les relations enseignement-appresntissage d’enseignants en salle de class, de parents comme instructeurs/superviseurs et etudiants qui s’approprient la numeratie et la litteratie en education a distance. Les donnees de l’etude de cas offrent un regard sur la facon dont l'etablissement a distance (l’ecole) interagit avec les familles pour faciliter l’experience d’apprentissage des jeunes apprenants. Actuellement, l’ecole et les familles avec lesquelles elle s’engage ont des ressources technologiques limitees. Cette etude tient compte de l’engagement a l’apprentissage dans ces environnements de plus en plus inhabituels et postule sur l’effet que les nouvelles technologies peuvent avoir sur les pratiques pedagongiques dans l’avenir.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".