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Record W4320505686 · doi:10.2991/978-2-494069-05-3_107

Comparison Research of Scientific Thinking Cultivation in Primary and Secondary Education Between Ontario and China

2022· book-chapter· en· W4320505686 on OpenAlexaffabout
Yina Yao

Bibliographic record

VenueProceedings of the 2022 International Conference on Science Education and Art Appreciation (SEAA 2022) · 2022
Typebook-chapter
Languageen
FieldSocial Sciences
TopicEducation and Critical Thinking Development
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsChinaPrimary (astronomy)Mathematics educationGeographyEngineering ethicsEngineeringPsychologyArchaeologyPhysics

Abstract

fetched live from OpenAlex

Cultivation of scientific thinking has become an important goal in the development of primary and secondary schools in various countries.Although the cultivation of scientific thinking has been widely recognized in China, there are still shortcomings in the overall observation and research of the cultivation of scientific thinking in primary and secondary schools.In order to compare the current situation of scientific thinking education in China, this paper concludes the current situation and challenges faced by China in cultivating scientific thinking for primary and secondary school students, and Ontario's advantages in cultivating scientific thinking from the theoretical, policy and implementation levels.Through the comparative study of the two places, this paper suggests the model of scientific thinking training in Ontario primary and secondary schools can be used for Chinese primary and secondary school scientific thinking.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.148
Threshold uncertainty score0.298

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.008
Science and technology studies0.0040.002
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.094
GPT teacher head0.398
Teacher spread0.304 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2022
Admission routes2
Has abstractyes

Explore more

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