텍스트 마이닝과 설문조사 기반 법학적성시험 개선방안 탐색

초록

This study explored the major issues surrounding the Legal Education Eligibility Test (LEET), the entrance examination for law schools in Korea, and proposed directions for its improvement. Therefore previous studies were reviewed, and keyword analysis and Latent Dirichlet Allocation (LDA) topic modeling were conducted on news articles related to the LEET. Based on the identified issues, a nationwide survey of law school students was conducted to examine the LEET from the perspectives of test design and administration, its role as an aptitude test, and consequential validity. The results indicated several areas for improvement. First, issues related to test design and administration included imbalances in test difficulty and testing time, the current score weighting system, limited use of the Writing section, and once-a-year testing schedule. Second, respondents perceived that the LEET did not adequately assess the competencies required for succeedingl in law school, suggesting the need to redesign the assessment framework and item formats based on empirical evidence. Third, many respondents reported relying on private tutoring to prepare for the LEET, highlighting the need for stronger educational support systems. This study provides empirical evidence for improving the LEET by integrating text mining with a nationwide survey and offers practical implications for enhancing its design, administration, aptitude-testing function, and consequential validity.

키워드