Spatial Skills Activities in the Middle School Mathematics Teachers' Toolkit: The Impact of Spatial Skill Activities on Mathematical Thinking
Bibliographic record
Abstract
This study investigated the impact of the incorporation of spatial skill activities into their pedagogical repertoire by middle school mathematics teachers on the mathematical reasoning of their students. Current research suggests that success in spatial reasoning is a strong predictor of success in STEM fields, and is known to be strong in successful mathematicians (Newcombe, 2013; Tepylo Moss, 2013; Uttal et al., 2012). In this study, teachers replaced starter activities three or more times per week with hands-on spatial skill problems that required mental rotation and spatial visualization to solve. While there have been many studies linking spatial skill to success in mathematics, there are few studies that attempt to establish a relationship through intervention in a middle school classroom. Findings suggest that incorporating spatial skill activities into mathematics lessons had a positive impact on both the teachersâ reflective practice and the studentsâ learning skills. While there was some improvement in mathematical reasoning, it was not possible to definitively attribute this to the spatial skill activities.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".