The Relationship between Students' Attitudes towards Mathematics and Academic Performance in the Subject
Bibliographic record
Abstract
Mathematics performance has been a persistent challenge in educational systems worldwide, including the Philippines. Students’ poor performance in mathematics often stems from a combination of cognitive and attitudinal factors, with negative attitudes such as anxiety, lack of confidence, and disinterest significantly hindering engagement and achievement. This study investigated the relationship between students’ attitudes toward mathematics and their academic performance in the subject. This study focused on Paradise Embac National High School students during the academic year 2024–2025. This research employed a descriptive-correlational design to examine the correlation between the attitudes of students toward mathematics and their performance. This design enabled both attitudinal data and academic records to be gathered to ascertain any possible correlations. The participants of this research were approximately 100 high school students who were selected via stratified random sampling to provide representation from various year levels and academic tracks. This research is anchored on the Expectancy Value Theory by Victor Vroom (1964), which explains how students' motivation influences academic performance in mathematics. Addressing the persistent challenge of low mathematics achievement in the Philippines, particularly in Davao City, this research examined how attitudinal factors, including interest, confidence, anxiety, and perceived usefulness, correlated with performance and were grounded in Victor Vroom’s Expectancy Value Theory. A descriptive-correlational design was employed, involving 100 high school students from Paradise Embac National High School. Data were collected using the Attitude Towards Mathematics Inventory (ATMI) and students’ final mathematics grades. Findings indicated moderate overall attitudes toward mathematics, with high perceived usefulness but low interest, confidence, and elevated anxiety. A significant positive correlation (R = 0.990, p=0.000) was found between attitudes and academic performance. These results highlight the need to cultivate positive attitudes and reduce anxiety to improve mathematics achievement, contributing to educational development in the region. In conclusion, it indicates a complex and multi-dimensional picture of students' mathematical attitudes and their related levels of achievement. Although students have a medium attitude towards mathematics overall, the results demonstrate an unambiguous imbalance between the components of the attitudinal process. Students have a high perception of the utility of mathematics, meaning that they intellectually realise its applicability in everyday life, professional future, and global society.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".