In the current big data era, we have witnessed the prosperity of emerging massive open online courses, user-generated data and ubiquitous techniques. These evolving technologies and applications have significantly changed the ways for people to learn new knowledge and access information. To find users’ desired data in an effective and efficient way, it is critical to understand/model users in applications involving in such a large volume of learning resources. For instance, word learning systems can be promoted significantly in terms of learning effectiveness if the preknowledge on vocabulary of learners can be predicted accurately. In this research, we focus on the issue of how to model a specific group of users, i.e., language learners, in the context of e-learning systems. Specifically, we try to predict the pre-knowledge on vocabulary of learners from their previous learning documents such as writing assignments and reading essays. The experimental study on real participants shows that the proposed predicting model is very effective and can be exploited for various applications in the future.
|Title of host publication||Current Developments in Web Based Learning - ICWL 2015 International Workshops, KMEL, IWUM, LA, Revised Selected Papers|
|Editors||Di ZOU, Zhiguo GONG, Dickson K.W. CHIU|
|Publisher||Springer-Verlag GmbH and Co. KG|
|Number of pages||7|
|Publication status||Published - 2016|
|Event||The 14th International Conference on Web-based Learning - Guangzhou, China|
Duration: 5 Nov 2015 → 8 Nov 2015
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Conference||The 14th International Conference on Web-based Learning|
|Abbreviated title||ICWL 2015|
|Period||5/11/15 → 8/11/15|
Bibliographical noteThe work described in this paper was fully supported by a grant from Research Grants Council of Hong Kong Special Administrative Region, China (UGC/FDS11/E06/14), a grant from the National Natural Science Foundation of China (Grant No. 61502545), a grant from the Soft Science Research Project of Guangdong Province (Grant No. 2014A030304013), and “the Fundamental Research Funds for the Central Universities” (Grant No. 46000-31610009).
- Learner profile
- Vocabulary pre-knowledge
- Word learning