Paper Info
Title
Personalized word learning for university students: a profile-based method for e-learning systems
Abstract
It is widely acknowledged that the acquisition of vocabulary is the foundation of learning English. With the rapid development of information technologies in recent years, e-learning systems have been widely adopted for English as a Second Language (ESL) Learning. However, a limitation of conventional word learning systems is that the prior vocabulary knowledge of learners is not well captured. Understanding the prior knowledge of learners plays a key role in providing personalized learning, which many studies suggest is a successful learning paradigm for vocabulary acquisition, one that aims to optimize instructional approaches and paces by catering to individual learning needs. A powerful learner profile model which can represent learner’s prior knowledge is therefore important for word learning systems to better facilitate personalized learning. In this article, we investigated various methods to establish learner profiles and attempted to determine the optimal method. To verify the effectiveness of personalized word learning supported by the proposed model, ESL students from several universities participated in this study. The empirical results showed that the proposed learner profile model can better facilitate vocabulary acquisition compared with other baseline methods.
Year
DOI
Venue
2019
10.1007/s12528-019-09215-0
Journal of Computing in Higher Education
Keywords
Field
DocType
Word learning, Personalized learning, E-learning, Learner modeling
E learning,Information technology,Computer science,Knowledge management,Personalized learning,Teaching method,Mathematics education,Word learning,Vocabulary,Vocabulary development,Individual learning
Journal
Volume
Issue
ISSN
31
2
1042-1726
Citations 
PageRank 
References 
0
0.34
0
Authors
5
Name
Order
Citations
PageRank
Haoran Xie145071.21
Di Zou23812.11
Ruofei Zhang300.34
Minhong Wang453147.90
R. Kwan521.06