Fostering School, University, and Community Relationships through a Family Math Night
Bibliographic record
Abstract
Family Math Nights, first introduced by Stenmark, Thompson and Cossey (1986), “are school-sponsored events in which parents, teachers, and students interact around a mathematics curriculum” (Lopez & Donovan, 2009, p. 220). The research project described in this paper/session sought to investigate the effectiveness of a locally organized Family Math Night that resulted through collaboration between a university faculty of education and a local school division. The event, which was held in a local community school that had may newcomer families and students in attendance, was conceptualized and facilitated by divisional consultants, teachers from the school, university faculty members, and teacher candidates. Evidence from the mixed methods research study indicated that the Family Math Night fostered positive relationships between school, university, and community; engaged parents and students in curriculum-based mathematics activities in a supportive, non-threatening, and fun atmosphere; provided teacher candidates with opportunities to plan for and engage with students in an authentic way; and provided parents with strategies and games they could use at home. Such findings illustrate the promise of Family Math Nights as tools not only for promoting student numeracy, but also for fostering positive school, university, and community relationships.
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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.015 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".