Are Argumentation Skills Can Describe Understanding Concepts?
Bibliographic record
Abstract
Objective: Based on the several aspects, one aspect is quite important in the process of learning science, namely communicating. Argumentation is one of communication skills. Are argumentation can describe understanding concepts? Method: This study uses a literature review method from thirteen articles. Results: Argumentation skills can describe understanding concepts. Interpretation of the correlation coefficient shows that argumentation skills strongly correlate with understanding concepts. It is because argumentation skills positively correlate with critical thinking and logic skills. Argumentation skills can improve students' critical thinking level and logical skills in the thinking process. Everyone has good argumentation skills if has good critical thinking and good logic skills. Novelty: Argumentation skills are one of the communication skills that improve understanding of concepts. Argumentation skills are moderators for high-order thinking skills. It can occur because the components of argumentation skills are claim, evidence, and reasoning. Someone can meet all the argumentation skills components with good thinking.
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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 | 0.014 | 0.090 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.005 | 0.014 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".