Application of the Problem Based Learning Model ( PBL ) To Improve Critical Thinking Skills and Mastery of Concepts on Environmental Pollution Materials
Bibliographic record
Abstract
The Problem Based Learning Model (PBL) is a learning model that is highly recommended in the implementation of the National Curriculum. This research is to obtain an overview of the implementation of PBL in learning environmental pollution in an effort to improve critical thinking skills and mastery of concepts. This research was carried out by the quasi-experimental method, namely the pretes-postes control design. The study subjects were 73 students who were divided into control groups and experimental groups. The data obtained comes from the completion of the critical thinking test problem in the form of a description and mastery of the concept in the form of multiple choices. The results of the study explain that the acquisition of critical thinking skills with higher value PBL learning ( average - = 82.1) compared with conventional learning ( average - =61.4 ) with a calculated t value of 28.34 (p 0.05). Mastery of concepts with PBL learning gets a higher score ( average - average = 76) compared to conventional learning ( average - 0.05TAG. The results showed that the PBL learning model was able to improve critical thinking and mastery of the concept of students in class X environmental pollution material at Senior High School 1 Dramaga.
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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 | 0.002 | 0.003 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".