Self-Efficacy, Adversity Quotient, and Students’ Achievement in Mathematics
Bibliographic record
Abstract
Indonesian students’ achievement in mathematics is generally still low compared with other countries. Many psychological factors, both internal and external, influence this poor performance. This study aimed to measure the effect of self-efficacy and the adversity quotient of Grade IX students regarding achievement in mathematics. Both of these internal variables have been selected because students’ success in mathematics is determined more by internal factors than by external factors. A survey method was used. The sample included 140 students and was drawn using a probability sampling technique. A self-efficacy scale and an adversity quotient scale were used to collect the data. Students’ mathematics achievement was determined based on school test results. The data were analyzed using multiple regressions. The findings reveal significant effects of self-efficacy and the adversity quotient but no significant effects of gender on students’ academic mathematics achievement. Therefore, an implication of the study is that we must investigate how to improve students’ self-efficacy and adversity quotient in mathematics. The results may be of interest to other developing countries, especially those in Southeast Asia that share similar concerns with Indonesia regarding students’ mathematics achievement.
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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 | 0.004 |
| 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 | 0.001 |
| 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".