UMLL21: The 5th International Symposium on User Modeling and Language Learning Zhuhai, China, November 11-12, 2021 |
Conference website | http://sete-umll.org/2021/ |
Submission link | https://easychair.org/conferences/?conf=umll2021 |
Submission deadline | August 12, 2021 |
Notification of acceptance | August 27, 2021 |
Camera-ready submission | September 6, 2021 |
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 (UMLL21) is in conjunction with The 6th International Symposium on Emerging Technologies for Education (SETE21) 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.
Submission Guidelines
Submissions must not exceed 10 pages in LNCS (Lecture Notes in Computer Science) format. We encourage authors to cite related work comprehensively, and when citing conference papers please also consider citing their extended journal versions if applicable.
All submissions must be in PDF format. Authors should avoid the use of non-English fonts to avoid problems with printing and viewing the submissions. All accepted papers MUST follow strictly the instructions for LNCS Authors. Springer's LNCS site offers style files and information.
- Long Papers: 8 - 10 pages
- Short Papers: 4 - 6 pages
Submissions must not have been published previously and must not be under review for publication while being considered for UMLL. This applies also to papers with significantly overlapping contributions. Authors are advised to interpret these limitations strictly and to contact the PC chairs in case of doubt.
UMLL submissions are reviewed following the single-blind review process, meaning, you do not need to hide authors' names and affiliations.
Each accepted paper must be accompanied by at least one full registration regardless of the status of the registering author, and an author must present the paper at the conference. Otherwise, the paper will be removed from the proceedings and LNCS digital library.
Submission system on EasyChair.
List of Topics
- 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
Committees
Symposium Chairs
- Gary Cheng, The Education University of Hong Kong, Hong Kong
- Di Zou, The Education University of Hong Kong, Hong Kong
- Wei Chen, Chinese Academy of Agricultural Sciences, China
Steering Committee Chairs
- Haoran Xie, Lingnan University, Hong Kong
- Yi Cai, South China University of Technology, China
Contact
All questions about submissions should be emailed to Prof Xie (hrxie2@gmail.com).