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 5th International Symposium on User Modeling and Language Learning is in conjunction with The 6th International Symposium on Emerging Technologies for Education (SETE2021) in Zhuhai, China during November 11-12, 2021. 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 SETE 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