The Use of STEAM Education Learning Package to Develop Elementary School Students’ Science Process Skills and Learning Achievement of Physical Properties of Materials
Bibliographic record
Abstract
This study aimed to: 1) assess the impact of a STEAM education learning package on grade 10 students’ science process skills, 2) evaluate its effect on their learning achievement concerning the physical properties of materials, and 3) gauge the students’ satisfaction with the learning package. The participants were 13 grade 10 students from a public school in Thailand, selected through convenience sampling. The study utilized a STEAM Education Learning Activity Package, a Science Process Skills Test, a Learning Achievement Test, and a Learning Satisfaction Questionnaire as instruments. Data analysis involved calculating mean scores, standard deviations, effectiveness indices (E.I, E1/E2), and normalized gains. Results demonstrated significant improvements in both science process skills and learning achievement related to the physical properties of materials. Additionally, the learning package enhanced students’ satisfaction with their learning experience. These findings suggest that the STEAM education learning package could be a valuable tool for improving science education at the elementary school level.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".