Perception and behavior of high school students towards developing problem solving and creativity skills to solve physics assignments
Bibliographic record
Abstract
This study aimed to explore the learning approaches and preferences of high school students in Vietnam when studying physics. A survey was completed by 2,040 students from ten different schools on improving problem-solving and creativity skills to solve physics assignments. The survey included eight topics related to homework, exchange, problem-solving tactics, and an emphasis on real-life applications of physics concepts. The results showed that the majority of students preferred essay-style calculus homework and sometimes exchanged and discussed ideas with their peers. In addition, most students focused on only some of the steps involved in solving physics problems, self-analyzed and expanded their solutions, and related the exercise content to real-life situations. The study also found that students preferred physics exercises with clear facts and suggestive questions, while a quarter of students preferred exercises with specific facts and clear questions. Furthermore, only a small percentage of students had a deep understanding of the ten core competencies outlined in the General Education Program of 2018. These findings have important implications for physics teachers in Vietnam, indicating the need for more opportunities for discussion and encouraging a comprehensive problem-solving approach. The study suggests incorporating more real-life applications of physics concepts into teaching to help students see the relevance of what they are learning.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".