A Picture of Chemistry: A Case Study from High Schools (Hakkari Sample)
Bibliographic record
Abstract
This research aims to draw a picture of chemistry lessons based on students’ opinions in Hakkari, Turkey. The research design is a case study. An open-ended qualitative questionnaire consisting of 15 questions was used. The questionnaire was applied to 463 tenth- and eleventh-grade students studying at high schools in Hakkari. The data obtained were analyzed using qualitative and quantitative methods: content analysis, correlation tests, and chi-square tests. As a result, two categories were found: the factors affecting chemistry teaching and the effect of chemistry on students’ daily and future lives. According to this, students’ interest in chemistry is a factor in learning chemistry, the teaching method used by the teacher is an essential factor for chemistry, and having enough knowledge of chemistry affects achievement in other courses. A significant difference was found between female and male students choosing chemistry in their future careers, and the results were in favor of male students. On the contrary, female students thought that chemistry would be more permanent than males thought in their lives. The activities used in chemistry lessons, teachers’ attitudes in the classroom, and the use of chemistry examples in daily life are effective for learning chemistry and choosing chemistry for a future career.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".