Middle School Teachers' Successes and Challenges in Supporting Students' Mathematical Communication Using Manipulatives and Technology in a Professional Development Study
Bibliographic record
Abstract
The case studies of four inner-city Grade 6 educators involved in a year-long Professional Development (PD) study were examined to determine: a) successes and challenges teachers face supporting students' mathematical communication, b) teachers' manipulatives and technology use to support communication, and c) the study's effects on teachers' attitudes and beliefs. The Ten Dimensions of Mathematics Education Framework (McDougall, 2004) was used to examine the findings. Teachers had success with learning environment, student tasks and teachers’ comfort with mathematics. Teachers faced many challenges, primarily in learning environment, communicating with parents, and teacher’s comfort with mathematics. Teachers provided varied integration of manipulative use, and need to continue to integrate technology, to support mathematics communication. It was determined that, while the PD study was greatly successful in providing support towards aligning teachers' attitudes and beliefs with current mathematical practices, PD alone is insufficient for improving teachers' attitudes.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".