e-러닝에 참여한 성인학습자의 중도탈락 예측을 위한 베스트 모델 탐색 = A Best Logistic Regression Model for Predicting Dropout of Adult Learners from E-learning Courses

다국어 초록 (Multilingual Abstract)

The purpose of this study was to determine which specific set of variables can best predict the dropout of adult learners from e-learning courses in the workplace. Based on Keller’s(1987) ARCS model, a self-completion forced choice survey instrument scale was developed to obtain information about learners’ motivation to participate in e-learning in the workplace. The sample used for this study was a non-random convenience sample of employees in a South Korea company. Two hundred fifty-nine usable surveys were returned, yielding a final response rate of 12.26 percent. A logistic regression model was proposed to accomplish the purpose of the study. The primary results were: (1) The overall assessment of the proposed logistic regression model consisting of eight individual background variables and four motivational variables revealed that the model had a moderate association between the predictor variables and Dropout. (2) A logistic regression model consisting of Number of e-learning courses completed, Gender, Learning hours for the course per week, Hours worked per week, and Attention was chosen as the best model in terms of efficient predictability of dropout of adult learners.

국문 초록 (Abstract)

이 연구의 목적은 어떤 조합의 변인들이 e-러닝에 참여한 성인학습자들의 중도탈락을 가장 잘 예측하는지를 밝히는데 있다. 이 연구를 위해서 Keller(1987)의 동기설계모델의 네 가지 핵심조건인 참신성, 관련성, 자신감, 만족감 등에 근거해 설문도구를 개발하였다. 표집은 20 시간짜리 업무 관련 e-러닝 코스에 자발적 혹은 의무적으로 등록한 총 259명의 회사원들이다. 수집된 자료는 통계 프로그램인 SPSS와 SAS를 이용해 분석되었다. 분석 결과는 다음과 같다. (1) 개인 배경 변인들(수강한 e-러닝 코스의 수, 나이, 성별, 교육 수준, 결혼 여부, 의무적/자발적 참여 여부, 주당 근무 시수, 주당 e-러닝 코스에 투자한 시간)과 동기 변인들(참신성, 관련성, 자신감, 만족감)로 구성된 로지스틱 회귀분석 모델에 대한 전반적인 평가는 이 모델이 e-러닝에 참여한 성인학습자의 중도탈락을 어느 정도 잘 설명하고 있음을 보여 주었다. (2) 효율성의 측면에서 성별, 수강한 e-러닝 코스의 수, 참신성, 주당 근무 시수, 주당 e-러닝 코스에 투자한 시간 등의 다섯 변인들로 구성된 로지스틱 회귀분석 모델이 e-러닝에 참여한 성인학습자들의 중도탈락을 예측하는데 최고의 베스트 모델로 선정되었다.

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