Bibliographic record
Abstract
The purpose of this study was to develop a framework focusing on multicultural contexts and science education contents, and to analyze 3rd to 6th grade elementary science curricula of the 2007 revised Ontario science and technology in Canada with the 2009 revised and 2015 revised national science curricular in Korea. The framework’s horizontal axis was divided into four levels: the contribution approach, the additive approach, the transformation approach and the social action approach, while its vertical axis was comprised of ‘situation’, ‘components’ and ‘performance.’ Based on the criteria, the author quantitatively compared the curricula of the two countries. Furthermore, examples concerned with multicultural contexts were discerned from the goals, expectations, strands, topics, assessment and other considerations for program planning in science. In the 2007 revised Ontario curriculum for science and technology, it clarified that the diversity of student cultural backgrounds should not only be respected and supported for adjustment to the new learning environment, but also that it should be considered as intercultural education perspectives. On the other hand, the 2009 revised and 2015 revised Korean national curriculum for science did not deliver on the importance of multicultural science education as written instructions. This study suggested that the Korean national curriculum for science needs to have learning materials showing respect for cultural diversity or diverse people working on scientific activities or careers. Moreover, definite directions and perspectives on multicultural science education should be established in the national science curriculum. The results of this study could be useful for the development, reconstitution, or improvement of science curriculum for teaching multicultural students concurrently.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".