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Record W1930466794 · doi:10.5539/mas.v9n12p143

The Contribution of Critical Thinking Skills and Metacognitive Awareness on Students’ Learning: Teaching Biology at Senior High School

2015· article· en· W1930466794 on OpenAlexvenueno aff
Firdaus Daud, Ika Ayu Hafsari

Bibliographic record

VenueModern Applied Science · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Critical Thinking Development
Canadian institutionsnot available
Fundersnot available
KeywordsMetacognitionMathematics educationCritical thinkingClass (philosophy)PsychologyPopulationCognitionDemographyComputer scienceSociology

Abstract

fetched live from OpenAlex

This research aimed to examine the contribution of critical thinking skills and metacognitive awareness on biology learning in class XI at a government senior high school in Makassar. The research was a correlational ex post facto study, and the population studied consisted of students attending the selected government Senior High Schools in Makassar for the 2013/2014 academic year. Samples were chosen according to random sampling clusters. The Data was analyzed with descriptive and inferential statistics. Research results showed that (1) Both critical thinking skills and metacognitive awareness contributed positively to biology students’ learning outcomes in class XI, (2) Critical thinking skills contributed positively to biology students’ learning in class XI at senior high school, (3) Metacognitive awareness contributed positively on biology students’ learning outcomes.

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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.027
GPT teacher head0.380
Teacher spread0.353 · 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

Citations7
Published2015
Admission routes1
Has abstractyes

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