Analysis of the Relationship between Quadrilaterals Achievement Levels and Van Hiele Geometric Thinking Levels of the Seventh Grade Students
Bibliographic record
Abstract
In this study, it was aimed to examine the relation between seventh-grade students' quadrilaterals achievement levels and Van Hiele geometric thinking levels. Survey method was used. The sample of the study was 160 students from the three different districts of Kayseri, as Melikgazi, İncesu, and Tomarza. Van Hiele geometric thinking test and quadrilaterals achievement test, which was developed by the first researcher, were used to collect the data. Descriptive statistics such as mean, frequency, and standard deviation and percentage tables Pearson correlation analysis which was applied to analyze the relationship between the quadrilaterals achievement test and Van Hiele geometry thinking test scores of the seventh-grade students and independent samples t-test was used to for analysis. The results of the study indicated that Van Hiele geometric thinking levels of the seventh school students were lower than expected levels. A high level of correlation was found between quadrilaterals achievement levels and their Van Hiele geometric thinking levels of the seventh-grade students. As a result of the study, quadrilaterals achievement test and Van Hiele geometric thinking test were measuring the students’ geometric abilities in the same direction.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".