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Abdous, M'hammed; He, Wu; Yen, Cherng-Jyh – Educational Technology & Society, 2012
As higher education diversifies its delivery modes, our ability to use the predictive and analytical power of educational data mining (EDM) to understand students' learning experiences is a critical step forward. The adoption of EDM by higher education as an analytical and decision making tool is offering new opportunities to exploit the untapped…
Descriptors: Electronic Learning, Online Courses, Video Technology, Synchronous Communication
Cocea, M.; Weibelzahl, S. – IEEE Transactions on Learning Technologies, 2011
Learning environments aim to deliver efficacious instruction, but rarely take into consideration the motivational factors involved in the learning process. However, motivational aspects like engagement play an important role in effective learning-engaged learners gain more. E-Learning systems could be improved by tracking students' disengagement…
Descriptors: Prediction, Electronic Learning, Online Courses, Delivery Systems
Smith, Vernon C.; Lange, Adam; Huston, Daniel R. – Journal of Asynchronous Learning Networks, 2012
Community colleges continue to experience growth in online courses. This growth reflects the need to increase the numbers of students who complete certificates or degrees. Retaining online students, not to mention assuring their success, is a challenge that must be addressed through practical institutional responses. By leveraging existing student…
Descriptors: Academic Achievement, At Risk Students, Prediction, Community Colleges
Hung, Jui-Long; Hsu, Yu-Chang; Rice, Kerry – Educational Technology & Society, 2012
This study investigated an innovative approach of program evaluation through analyses of student learning logs, demographic data, and end-of-course evaluation surveys in an online K-12 supplemental program. The results support the development of a program evaluation model for decision making on teaching and learning at the K-12 level. A case study…
Descriptors: Web Based Instruction, Databases, Virtual Classrooms, Decision Support Systems
Huang, Chenn-Jung; Chu, San-Shine; Guan, Chih-Tai – Computers & Education, 2007
In recent years, designing useful learning diagnosis systems has become a hot research topic in the literature. In order to help teachers easily analyze students' profiles in intelligent tutoring system, it is essential that students' portfolios can be transformed into some useful information to reflect the extent of students' participation in the…
Descriptors: Portfolios (Background Materials), Prediction, Online Courses, Intelligent Tutoring Systems

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