원문정보
A study on the Analysis and Forecast of Effect Factors in e-Learning Reuse Intention Using Rule Induction Techniques
초록
영어
Electronic learning(or e-learning) has created hype for companies, universities, and other educational institutions. It has led to the phenomenal growth in the use of web-based learning and experimentation with multimedia, video conferencing, and internet-based technologies. Many researchers are interested in the factors that affect to the performance of e-learning or e-learning services. In this sense, this study is aimed at proposing e-learning system reuse prediction models in which e-learner intention to reuse influence factors(i.e., system accessibility, system stability, information clarity, information validity, self-regulated efficacy, computer self-efficacy, perceived usefulness, perceived ease of use, flow, and parental expectation) affect e-learner intention to reuse positively. A web survey was conducted for the full members of the e-learning education institute A in Seoul, Republic of Korea, an exclusive e-learning company that provides real time video lectures via the desktop conferencing system. The web survey was conducted for 20 days from November 5, 2009, through the e-learning web site of the company A. In this study, three data mining techniques were used:the multivariate discriminant analysis, CART, and C5.0 algorithm. This study was conducted to provide the e-learning service providers, e-learning operators, and contents developers with marketing and management strategies for improving the e-learning service companies, based on the data mining analysis results.
목차
1. 서론
2. 이러닝 시스템 재이용의도 영향요인에 관한 연구
2.1 시스템 특성과 정보 특성
2.2 TAM과 플로우 이론
2.3 학습자 특성(자기효능감 이론)과 부모의 성취기대
3. 연구 방법
3.1 연구 변수의 조작적 정의
3.2 표본 선정 및 분석 방법
4. 분석 결과
4.1 표본의 기술적 특성
4.2 다변량 판별분석 모형구축 및 결과
4.3 규칙유도기법 모형구축 및 결과
4.4 기계학습기법간 이러닝 시스템 재이용의도 속성의 비교분석
5. 결론
참고문헌