Attitude towards Physics and Additional Mathematics Achievement towards Physics Achievement
Bibliographic record
Abstract
The purpose of this research is to identify the difference in students’ attitude towards Physics and Additional Mathematics achievement based on gender and relationship between attitudinal variables towards Physics and Additional Mathematics achievement with achievement in Physics. This research focused on six variables, which is attitude towards Physics, career related to Physics, importance of Physics, difficulty of understanding Physics, Physics teachers and Physics equipment usage. The respondents consist of 203 Grade 10 students in science stream who are taking Physics as an elective subject. This research was done in secondary schools in the district of Kota Bharu, Kelantan. A questionnaire was used to gather the data regarding six aspects (24 items). The items from Prokop, Tuncer, and Chuda (2007) were translated and used to determine the students’ attitude towards Physics. The findings showed a significant difference in students’ interest towards Physics, career related to Physics, importance of Physics, difficulty of understanding Physics, Physics teachers and Physics equipment usage whereby the male students are higher compared to female students. Meanwhile there was no difference between students’ attitude towards the importance of Physics and achievement in Additional Mathematics. There is a strong relationship between Additional Mathematics achievement and Physics achievement followed by interest towards Physics and difficulty of understanding Physics. Meanwhile the relationship between students’ attitude towards career related to Physics, importance of Physics, Physics teacher and Physics equipment usage is not significant towards Physics achievement. Physics teachers should give more emphasis in not only the learning of Physics but more importantly on students’ attitude towards the learning of Physics.
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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 | 0.001 | 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) | 0.005 | 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".