Lo, C. - C., Chao, K. - M., Kung, H. - Y., Chen, C. - H., & Chang, M. (2015). Information Management and Applications of Intelligent Transportation System. Mathematical Problems in Engineering, .
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Anderson, T., Upton, L., Dron, J., Malone, J., & Poelhuber, B. (2015). Social Interaction in Self-paced Distance Education. Open Praxis; Vol 7, No 1 (2015), .
Abstract: In this paper we present a case study of a self-paced university course that was originally designed to support independent, self-paced study at distance. We developed a social media intervention, in design-based research terms, that allows these independent students to contribute archived content to enhance the course, to engage in discussions with other students and to share as little or as much personal information with each other as they wished. We describe the learning design for the intervention and present survey data of student and tutor perception of value and content analysis of the archived contributions. The results indicate that the intervention was positively received by tutors and by the majority (but not all) students and that the archive created by the students'Äô contributions was adding value to the course. We conclude that the intervention was a modest, yet manageable example of a learning enhancement to a traditional cognitive-behavioral, course that has positive impact and potential with little negative impact on workload.
Keywords: Social Networks; blogs; self-paced study; online education; web 2.0; enhanced learning
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Bernard, J., Chang, T. - W., Popescu, E., & Graf, S. (2015). Using Artificial Neural Networks to Identify Learning Styles. Lecture Notes in Computer Science. Springer International Publishing.
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Bernard, J., Chang, T. - W., Popescu, E., & Graf, S. (2015). Improving Learning Style Identification by Considering Different Weights of Behavior Patterns Using Particle Swarm Optimization. State-of-the-Art and Future Directions of Smart Learning. Springer Singapore.
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Graf, S., Lachance, P., & Mishra, B. (2015). Integrating Motivational Techniques into Learning Management Systems. State-of-the-Art and Future Directions of Smart Learning. Springer Singapore.
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