INVESTIGATING THE ASSOCIATION BETWEEN TURKISH FRESHMAN’S MULTIPLE INTELLIGENCE PROFILES AND UNIVERSITY ENTRANCE EXAM PERFORMANCE
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Even though curriculum designers in Turkey considered Gardner’s multiple intelligence theory as one of the most important theories during the curricula reform in 2005, the university entrance examination system is still on the basis of the two intelligence areas only, mathematical-logical and linguistics intelligence. The aim of this study was to investigate the relation between students’ multiple intelligence profiles, gender, and the university entrance exam performance. Results of the study indicated that linguistic and logical-mathematical intelligences were the most dominant intelligence areas of the participants. Also, there was a statistically significant difference in participants’ dominant intelligence areas with respect to gender and the university entrance exam scores. Findings from this study suggest reconsiderations in using only one examination to guide students with different abilities and skills through career options and provide insights into considering alternative ways of university entrance exams that may move beyond only measuring linguistic and mathematical intelligences. Article visualizations:
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.010 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it