Investigating Financial Literacy Knowledge, Attitude, and Practice of Malaysian Secondary School Students
Bibliographic record
Abstract
Youths are more likely to achieve financial independence and prevent intergenerational poverty with adequate knowledge about finance management. Adequate financial literacy is pertinent to enhance financial knowledge, behaviours, and overall well-being in managing finance from a young. This study aims to assess the financial knowledge, attitude, and practice among 150 high school urban students aged 13 to 17 years. The participants (N=150) completed an online survey questionnaire. The financial knowledge was assessed with 20 knowledge-based questions and 15 attitude and practice-based questions respectively using the Likert scale. Data was analysed using the chi-square test and median value. Results show a significant association between financial knowledge and financial literacy. The higher secondary students had higher scores in the three variables due to the exposure to financial literacy subjects, parental support, and peer influence in financial practices. Financial literacy was also associated with the age of the study population. The study shows that there is a need to implement a formalised curriculum to increase financial literacy among secondary students to have a more robust and positive implication on the students’ financial practices for the future. The study is significant in creating awareness and empowering the students with the necessary financial literacy skills.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".