Attitudes, Study Habits, and Academic Performance of Junior High School Students in Mathematics
Bibliographic record
Abstract
Mathematics as a discipline is considered as one of the most difficult subjects among Filipino learners. This study was conducted in a public national high school in the Mandaue City Division, Cebu, Philippines. The respondents were the 177 Grade 9 students enrolled in mathematics. These respondents were selected using probability random sampling. They were asked to answer a standardized survey questionnaire to assess their attitudes and study habits. The tool is consists of three parts. Part 1 gathers the socio-demographic profile of the respondents. Part 2 assesses the attitudes of the respondents towards mathematics, while Part 3 was used to assess the study habits of the respondents. Furthermore, their academic performance in mathematics was measured based on their first quarter grade, which was retrieved from the Registrar’s Office. The study revealed that those respondents had positive attitudes towards mathematics in terms of its value while they had a neutral attitude when it comes to their self-confidence, enjoyment, and motivation in mathematics. Also, the study shows that there was a negligible positive correlation between the attitudes and academic performance of the respondents in terms of their self-confidence, enjoyment, and motivation while there was a weak positive correlation between the value of math and their academic performance in math. It was concluded that students’ attitudes and their study habits are significant factors that affect their performance in mathematics. The researchers strongly recommend the utilization of the enhancement plan in the teaching of mathematics to junior high school students.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".