MétaCan
Menu
Back to cohort
Record W4390928757 · doi:10.5539/ibr.v17n1p19

Investigating Financial Literacy Knowledge, Attitude, and Practice of Malaysian Secondary School Students

2024· article· en· W4390928757 on OpenAlexvenueno aff
Davamalar Arivalagan, Pavithran Ilangko

Bibliographic record

VenueInternational Business Research · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Literacy, Pension, Retirement Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsFinancial literacyLikert scaleFinanceCurriculumPsychologyMedical educationTest (biology)PopulationBusinessPedagogyMedicineSociologyDemographyDevelopmental psychology

Abstract

fetched live from OpenAlex

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.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.218
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0020.004
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.043
GPT teacher head0.400
Teacher spread0.356 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueInternational Business ResearchSame topicFinancial Literacy, Pension, Retirement AnalysisFrench-language works237,207