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Record W2005919075 · doi:10.1080/09500693.2013.826841

Comparison of Taiwanese and Canadian Students' Metacognitive Awareness of Science Reading, Text, and Strategies

2013· article· en· W2005919075 on OpenAlexaboutno aff
Jingru Wang, Shin-Feng Chen, I-Yao Fang, Ching-Ting Chou

Bibliographic record

VenueInternational Journal of Science Education · 2013
Typearticle
Languageen
FieldPsychology
TopicEducational Strategies and Epistemologies
Canadian institutionsnot available
FundersNational Science Council
KeywordsMetacognitionReading (process)Reading comprehensionComprehensionPsychologyMathematics educationScience educationCognitionComputer scienceLinguistics

Abstract

fetched live from OpenAlex

This study used a Chinese-language version of the Index of Science Reading Awareness to explore the science reading metacognition and comprehension of Taiwanese students. Structural equation modelling results confirmed the underlying model comprised three clusters of metacognitive knowledge: beliefs and confidence in science reading, knowledge of structure of science text, and knowledge of science reading strategies. The main contribution of the current research was to provide evidence about the relationship between metacognitive awareness and comprehension of science text. In addition, data comparisons to Canadian (British Columbia) benchmarks from the original development revealed that metacognitive awareness of science reading deteriorated from elementary to middle school in both countries, and there were no significant differences of metacognitive awareness of science reading between Canadian and Taiwanese students. Instructional suggestions for raising students' metacognitive awareness on science reading were discussed.

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)0.005
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 score0.356
Threshold uncertainty score0.715

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.043
GPT teacher head0.454
Teacher spread0.411 · 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

Citations20
Published2013
Admission routes1
Has abstractyes

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