Exploring Contextual Factors Affecting Student Performance in Mathematics: A Sequential Explanatory Research
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study aimed to explore and characterize the contextual factors that affect academic performance in learning mathematics among high school students. The study employed an explanatory sequential mixed method research design, and primary data were collected with the aid of the adopted questionnaire for quantitative data, and the interview was done for qualitative data. The study used descriptive and inferential statistical methods in analyzing and interpreting the gathered data. In addition, qualitative data were analyzed through a thematic analysis approach. Results showed that the performance of students in mathematics is influenced by different factors such as students' attitudes towards mathematics, self-efficacy, parental support, and the learning environment. In addition, a thematized interview with the students supports the quantitative analysis that their performance in mathematics was governed by the said factors. Conclusively, students must be supported in their learning by providing doable tasks and exciting problems in mathematics to boost their attitude and self-efficacy. Parents are also advised to give them the appropriate support to motivate them in their studies. Moreover, teachers must integrate welfare and positive attitudes towards students to have a conducive learning experience.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it