With the rapid development of Massive Open Online Courses (MOOCs), Web 2.0 online communities, social media, and mobile technologies in the big data era, there is a fast growth of learning resources such as online learning communities, open course videos, and other learning materials (e.g., Web pages, animations and documents). Confronting such a large volume of data, learners need an effective and efficient way to information organization. To achieve this goal, a powerful and versatile user model, which may contain various types of user information such as learning preferences, plans, pre-knowledge levels and contexts, is essential and critical. Such a user model can be exploited and applied in various Web-based learning applications like personalized learning paths discovery, learning resource recommendations, course opinions and sentiment analysis.
The first International Symposium on User Modeling and Language Learning is in conjunction with the 2nd International Symposium on Emerging Technologies for Education (http://2017.isete.net/) in Cape Town, South Africa during September 20–22, 2017. The aim of this symposium is to provide a forum for MOOC developers, e-learning developers, computational linguists, language educators, curriculum planners, material writers, and academia and industrial practitioners from disciplines of computer science, information systems and education to discuss recent advances in user modeling from perspectives of language learning. Authors of either theoretical or practical articles on user modeling and language learning, MOOCs or blended learning are encouraged to attend this symposium, explore potential education-oriented strategies, and create opportunities for future research collaborations.
We appreciate the interest and support of all attendees. Special thanks go to the ICWL organizers and Program Committee members. We are grateful to their hard work and the contributions of all the authors.
Topics of interest include, but are not limited to the exploitation of user modeling and language learning, the identification of semantics underlying large volume of user data for user modeling and efficient algorithms for e-learning data management, and the applications of user modeling and language learning in research fields related to (but not limited to):
User and learning resource modeling
User profiling and personalization
Learning resources recommendation and search
Ontology mining and modeling for learning users
Context modeling for users
Sentiment mining for user review
Cognitive-based user modeling
Learning style and methodology modeling
Learning assessments modeling
Computer-assisted language learning (CALL)
Mobile-assisted language learning (MALL)
Computer-based language assessment
Emerging technologies for language learning and teaching
Evaluation of existing technologies for language learning and teaching
Theoretical foundations of technology enhanced language learning (TELL)
Technical applications of TELL
Development of TELL
Assessment of TELL
Blended learning and TELL
Online teaching tools and platforms
Socio-educational perspectives and implications of TELL
TELL in multimodal environments
Data-driven learning (DDL) and TELL
Direct and indirect application of DDL in TELL
Corpora in language teaching