Comparison of Interdisciplinary History and Science Concepts from the Cognitive Aspect with Word Association Test
Bibliographic record
Abstract
This study aims to compare and contrast the connotations of the concepts of "science" and "history" that were formedin the minds of students attending both Faculty of Science and Letters, History Department and Faculty of Education,Science Education Department at Ağrı İbrahim Çeçen University. The participants of the study are 173 students fromthe History Department, including the whole education level of the department and 71 students from ScienceEducation Department including all classes. The participants were asked what they mean by the concepts of"science" and "history" and what connotations they made. Survey method is used in a descriptive research model.The Word Association Test (WAT) related to history and science has been utilized as a data collection tool.According to findings received after the analysis, it is found that there was no significant difference betweencognitive sentence structures of the students, who are attending different disciplines, towards both the concept ofhistory and science. As a result of the Word Association Test, although there are some differences according to thedepartments of education, many concepts in general are similar. When examining the cognitive sentence structuresfor the concepts, there is a need for research on the interrelationship of basic concepts with special areas. Thus, thisresearch gains more importance.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".