*** Apologies if you have received this CFP multiple times ***
Call for Papers:
Expert Systems The Journal of Knowledge Engineering
Special Issue on: Recommender systems for and in social and online learning environments
Guest Editors:
Dr. Tiffany Y. Tang, Department of Computing Engineering, Konkuk University, South Korea (tiffany@xxxxxxxxx)
Dr. Ben K. Daniel, College of Arts and Sciences, University of Saskatchewan, Canada (ben.daniel@xxxxxxxx)
Dr. Cristobal Romero, Department of Computer Sciences and Numerical Analysis, University of Cordoba, Spain (cromero@xxxxxx)
With the rapid growth of digital learning contents and online learning communities, searching useful information and discovering knowledge from those community sites is an important issue for both educators and learners.
These digital learning contents may include articles, research papers, online learning resources, presentation slides, dataset, books, test banks/ solutions, discussions, and many others, which are often scattered across multiple (un)-related sites.
Due to huge volume of these resources and the data associated with it, online learners as well as instructors are likely facing challenges in finding relevant information in the right amount and in the right time. Recommender systems can help learners/instructors to discover and retrieve relevant and personalized learning contents.
More specifically, recommender systems in education and social contexts consider not only the learners/teachers preferences for certain material, but also how the material may help them to achieve their goals.
Further, social networks on the other hand, enable learners and instructors to filter information and further share their experiences through connecting with other learners and peers via Web 2.0/Web 3.0 technologies.
From an educator?s perspective, learner interactions with other experts/learners within social network learning environments, is likely to bring some important information for assessing the learner?s learning progress, and delivering better learning contents in the future.
Moreover, from the learners? perspective, obtaining (either through self-exploring or recommendations) related contents to their learning interests or learning goals is critical to enable them effectively engage in the learning process. Ultimately, overall understanding of the learning process in online learning environments is critical to maintaining learners/instructors? interests as well as delivering relevant content to students.
In this special issue, we solicit original research papers on employing intelligent techniques to uncover interesting, serendipitous information from the vast amount of data for learning content delivery, management and improvement.
The issue aims to exam the interrelated relationships among the learner, the learning environment(s) and their interactions.
Broadly, the learning environments of interest include web-based learning system and the latest social learning environments where social networks have been adopted to facilitate knowledge creation, assembling and sharing.
Topics of interest:
We are especially interested in two broad categories: recommender systems in education, and social network and education.
The topics of interest include but are not limited to:
1) Recommender systems in education:
- Innovative recommendation techniques
- Group recommendation in education
- The pre- and post-assessment of recommendations
- User interface of educational recommender system
- Visualizations of recommended items in practice
- Context- and location-aware recommender systems
- Data Mining in recommender systems
- Privacy-preserving recommendations
- Case studies of educational recommender system implementations
2) Social networks and educational analytics:
- Research methods and techniques for analysis of social learning networks
- Models, metrics, and methods for analysis of online/virtual communities
- Learners? behavioral analysis
- Visualization and learning analytics: learners, social and knowledge networks
- Information gathering and processing techniques
- The process of learning in virtual communities
- Learning analytics
- Visualization of learning interactions in online/virtual communities
- Models of information analytics and knowledge networks
- Social recommender systems
- Data mining in social networks
Timeline (Provisional)
Submission of title and abstract: 29 February, 2012 (to rs_es@xxxxxxxxx)
Notification of acceptance: 15 March, 2012
Manuscript submission deadline: 15 June, 2012 (to http://mc.manuscriptcentral.com/exsy)
First review result: 15 September, 2012
Revised manuscripts due: 15 October, 2012
Second round of review result: 31 October, 2012
Final manuscripts due: 15 November, 2012
Paper Submission
The Guide for authors and online submission is available at http://www.wiley.com/bw/journal.asp?ref=0266-4720.
To submit to the special issue, please set the first words of the tittle "Submitted to Recommender Systems in Social and Learning Environments special issue".
Expert Systems The Journal of Knowledge Engineering
http://www.wiley.com/bw/journal.asp?ref=0266-4720
Edited by: Jon G. Hall
ISI Journal Citation Reports© Ranking: 2010: Computer Science, Artificial Intelligence: 81 / 108; Computer Science, Theory & Methods: 67 / 97
Impact Factor: 0.717
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