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맞춤형 학습지원을 위한 다면적 학습역량 진단검사(MLCT)결과 분석:A대학교 학습자를 중심으로

Analysis of Multidimensional Learning Competency Test (MLCT) Results for Customized Learning Support: Focusing on Students of University A

  • 박지현 (우석대학교 인공지능융합교육전공)
  • Jihyun Park (Dept. of Artificial Intelligence Convergence Education, Woosuk Univ)
  • 투고 : 2024.08.09
  • 심사 : 2024.11.05
  • 발행 : 2024.11.30

초록

본 연구는 전북지역 A대학에서 자체 개발한 다면적학습역량(MLCT) 진단검사를 통해, 연구에 참여한 학습자들의 체계적인 맞춤형 학습지원을 위한 방안의 필요성을 제시하고 A대학 학생들의 특성에 따라 학생들의 학습역량을 정확히 진단하여 그에 따른 맞춤형 학습지원을 위한 기초자료 분석을 위한 연구이다. 773명의 연구참여자를 대상으로 MLCT의 구성요인 '동기','인지','행동','정서','환경'에 대하여 성별, 학년별, 단과 대학별 집단 간 분석을 실시하였다. 본 연구를 통하여, 학습자의 맞춤형 학습지원을 위한 다양한 학습역량 분석 도구 개발과 보급을 통해 학습자가 학교생활에 잘 적응하여 중도 탈락 없이 성공적인 학습활동이 이루어질 수 있도록 체계적인 학습자 진단과 맞춤형 학습지원 프로그램 개발이 필요하다.

This study was conducted to highlight the need for systematic and tailored learning support strategies for students at A University in the Jeonbuk region, based on the results of the university's self-developed Multi-Dimensional Learning Competency Test (MLCT). The research aimed to analyze foundational data to accurately diagnose students' learning competencies according to their characteristics and provide customized learning support. A total of 773 participants were involved in the study, which analyzed the MLCT components of 'Motivation,' 'Cognition,' 'Behavior,' 'Emotion,' and 'Environment' across different groups based on sex, grade level, and college affiliation. The findings underscore the necessity of developing and disseminating various learning competency analysis tools to ensure that students can adapt well to university life and engage in successful learning activities without dropping out. This calls for the development of systematic learner diagnosis methods and tailored learning support programs.

키워드

참고문헌

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