Fang Yang
Learning Path Construction Based on Association Link Network
Yang, Fang; Li, Frederick W.B.; Lau, Rynson W.H.
Authors
Contributors
Elvira Popescu
Editor
Dr Frederick Li frederick.li@durham.ac.uk
Editor
Ralf Klamma
Editor
Howard Leung
Editor
Marcus Specht
Editor
Abstract
Nowadays the Internet virtually serves as a library for people to quickly retrieve information (Web resources) on what they want to learn. Reusing Web resources to form learning resources offers a way for rapid construction of self-pace or even formal courses. This requires identifying suitable Web resources and organizing such resources into proper sequences for delivery. However, getting these done is challenging, as they need to determine a set of Web resources properties, including the relevance, importance and complexity of Web resources to students as well as the relationships among Web resources, which are not trivial to be done automatically. Particularly each student has different needs. To address the above problems, we present a learning path generation method based on the Association Link Network (ALN), which works out Web resources properties by exploiting the association among Web resources. Our experiments show that the proposed method can generate good quality learning paths and help improve student learning.
Citation
Yang, F., Li, F. W., & Lau, R. W. (2012). Learning Path Construction Based on Association Link Network. In E. Popescu, Q. Li, R. Klamma, H. Leung, & M. Specht (Eds.), Advances in web-based learning (ICWL 2012) : proceedings of 11th International Conference, Sinaia, Romania, September 2-4, 2012 (120-131). Springer Verlag. https://doi.org/10.1007/978-3-642-33642-3_13
Publication Date | Jan 1, 2012 |
---|---|
Deposit Date | Jul 6, 2016 |
Publicly Available Date | Jul 19, 2016 |
Publisher | Springer Verlag |
Pages | 120-131 |
Series Title | Lecture notes in computer science |
Book Title | Advances in web-based learning (ICWL 2012) : proceedings of 11th International Conference, Sinaia, Romania, September 2-4, 2012. |
ISBN | 9783642336416 978, 36423364238 |
DOI | https://doi.org/10.1007/978-3-642-33642-3_13 |
Public URL | https://durham-repository.worktribe.com/output/1642226 |
Additional Information | Series: Lecture Notes in Computer Science |
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Copyright Statement
The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-33642-3_13
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