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Record W2160307704 · doi:10.5539/jel.v3n4p96

Effects of Outdoor School Ground Lessons on Students’ Science Process Skills and Scientific Curiosity

2014· article· en· W2160307704 on OpenAlexvenueno aff
Kan Lin Ting, Nyet Moi Siew

Bibliographic record

VenueJournal of Education and Learning · 2014
Typearticle
Languageen
FieldPsychology
TopicPsychological and Educational Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCuriosityMathematics educationPsychologyTest (biology)Control (management)Significant differenceProcess (computing)Science educationTreatment and control groupsSocial psychologyComputer scienceMathematicsStatistics

Abstract

fetched live from OpenAlex

The purpose of this study was to investigate the effects of outdoor school ground lessons on Year Five students’ science process skills and scientific curiosity. A quasi-experimental design was employed in this study. The participants in the study were divided into two groups, one subjected to the experimental treatment, defined as “eco-hunt” group and the other had no experimental treatment, defined as control group. This study used intact four classes which consisted of 119 students and randomly assigned to the treatment (n = 63) and control groups (n = 56). Students’ science process skill was measured by a self-developed Science Process Skills Test and students’ scientific curiosity was measured using Children Scientific Curiosity Scale adapted from Harty and Beall (1984). The results showed a significant difference in post-test mean scores between students in “eco-hunt” group and control group in both students’ science process skills and scientific curiosity. Follow-up comparisons on the dimensions of science process skills and scientific curiosity were analyzed and discussed. The findings of this study will provide a framework for science teachers to teach students through interesting and meaningful outdoor activities.

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)0.000
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.028
GPT teacher head0.454
Teacher spread0.426 · 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

Citations43
Published2014
Admission routes1
Has abstractyes

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