An Empirical Study on the Determinants of Insurance Literacy among Korean College Students
Bibliographic record
Abstract
Abstract As consumers increasingly assume greater responsibility and risk in choosing diverse and complex insurance products, the importance of insurance literacy is growing. While existing research has focused on the relationship between financial competency and financial knowledge, attitudes, behavior, and financial consumer protection, research on the impact and structure of financial education precursors to financial literacy is scarce, particularly in the area of insurance. This study developed and analyzed a survey of approximately 900 undergraduate students majoring in insurance studies at universities in Korea to examine the factors that determine the relative effectiveness of risk management and insurance education. The study examined relationships between faculty and students, and between the environment and faculty, and analyzed the influence of teaching behaviors on subcategories of educational effectiveness including students’ attitude, knowledge, and behavior. Results confirmed that student characteristics, faculty characteristics, and characteristics of the educational environment impact the effectiveness of risk management and insurance education. Specific findings demonstrate the importance of teaching behaviors and educational environments that promote students’ efficacy and motivation as key factors in enhancing educational effectiveness in risk management and insurance.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".