Special Issue on: "User Modelling and Learning Analytics"


Guest Editors:
Prof. Fu Lee Wang, Caritas Institute of Higher Education, Hong Kong
Dr. Di Zou, The Hong Kong Polytechnic University, Hong Kong
Dr. Haoran Xie and Dr. Tak-Lam Wong, The Education University of Hong Kong, Hong Kong

With the rapid development of massive online open courses (MOOCs), web 2.0 online communities, social media and mobile technologies in the big data era, there is a fast proliferation of learning resources such as online learning communities, open course videos and learning materials and multimedia textbooks (e.g. webpages, animations and documents).

When faced with such a large volume of data, it is essential to have effective and efficient ways to organise information. To achieve this goal, we need not only versatile user models but also powerful learning analytic approaches. Such user models and learning analytic approaches can be exploited and applied in various web-based learning applications such as personalised learning path discovery, learning resource recommendations, course opinions and sentiment analysis.

This special issue aims to present the latest research and developments in user modelling and learning analytics. The issue will carry revised and substantially extended versions of selected papers presented at the 1st International Workshop on User Modeling for Web-based Learning , the 14th International Conference on Web-based Learning and the 1st International Technology Enhanced Language Learning Workshop, but we also strongly encourage researchers unable to participate in the conference to submit articles for this call.

Subject Coverage

Suitable topics include, but are not limited to, the following:

Learner and learning resource modelling
Learning style and preference identification
Learner profiling and personalisation
User log mining and analytics for e-learning
Learning context modelling for users
Cognitive-based learner modelling
Learning assessment modelling
Knowledge management and learning strategies
Knowledge construction in e-learning
Web-based learning and knowledge communities
Learning and knowledge portals
Making sense of learning analytics
Learning analytic systems
Case studies of learning analytic implementations
Evaluation and assessment
MOOCs and learning analytics

Notes for Prospective Authors

Submitted papers should not have been previously published nor be currently under consideration for publication elsewhere. (N.B. Conference papers may only be submitted if the paper has been completely re-written and if appropriate written permissions have been obtained from any copyright holders of the original paper).

All papers are refereed through a peer review process.

All papers must be submitted online. To submit a paper, please read our Submitting articles page.
If you have any queries concerning this special issue, please email the Guest Editors at pwang@cihe.edu.hk or hrxie2@gmail.com.

Important Dates

Submission of manuscripts: 31 July, 2016

Notification to authors: 31 August, 2016

Final versions due: 30 September, 2016