Comparative analysis of science education systems of Turkey and Canada [Türkiye ile Kanada fen eǧitiminin kargılagtırmalı olarak Gncelenmesi]
Bibliographic record
Abstract
This study was aimed to examine the similarities and the differences between the science education systems and the science and technology programs of 6th-8th grades of elementary schools of Turkey and Canada (Ontario). Comparisons for Turkey and Canada (Ontario) science education systems were made in terms of "the aims". The similarities and the differences between Turkey, 2005 Science and Technology Program (TSTP) and Ontario1998, Science and Technology Curriculum (OSTC) were analyzed with respect to structure, strands and the units and the grade level, content, student achievements of unit of "Light" (TSTP) and "Optics" (OSTC). According to the comparison results main differences were; TSTP was a document of 412 pages and OSTC was a document of 110 pages, TSTP was more detailed according to OSTC. TSTC had 7 strands, OSTC had 5 strands. While TSTP units were designed spirally for each grade, OSTC units were not designed spirally. There were differences in the grade level, content and the student achievements of unit of "Light" (TSTP) and "Optics" (OSTC). Beside these differences, there were similarities between TSTP and OSTC in adopting of constructivist approach, student-centered teaching, the vision of scientific literacy, the importance of scientific process skills and relationship of Science-Technology-Society-Environment, teaching of how to use technology and knowledge, importance of students' differences.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".