The 9th International Symposium on
User Modeling and Language Learning
(UMLL 2025)

Symposium Topics

The rapid advancement of Generative Artificial Intelligence (GenAI) has created both opportunities and challenges across all levels of education. In schools, AI-enabled tools are widely used to complete homework and assignments, raising concerns about whether students are genuinely engaging in problem-solving and critical reasoning. In higher education, students increasingly rely on GenAI for drafting essays, creating study guides, and coding support. These practices can enhance efficiency but may also compromise academic integrity if used without critical consideration. For lifelong learners, GenAI provides accessible and personalized pathways that adapt to individual needs; however, questions remain about the reliability and quality of AI-generated outputs.

The potential of Generative Artificial Intelligence (GenAI) lies in its ability to augment human teaching and learning rather than replace it. AI-powered course assistants can reduce repetitive tasks, enabling instructors to devote more time to mentorship and deeper learning. Automated feedback systems can deliver timely, individualized, and scalable formative assessment. AI-integrated activities can transform pedagogy by engaging learners as active partners in collaboration with intelligent systems, thereby fostering creativity, critical thinking, and reflection. Nevertheless, adoption is often hindered by faculty hesitancy, inconsistent institutional policies, and technical limitations such as bias and hallucinations. Ethical concerns related to equity, privacy, transparency, and fairness further complicate the integration process.

Meanwhile, the expansion of MOOCs, Web 2.0 communities, social media, and mobile technologies has generated an unprecedented volume of multimodal learning resources, including videos, corpora, animations, and interactive materials. Learners now face the dual challenge of navigating vast resources and ensuring meaningful engagement. User modelling, which captures learner preferences, prior knowledge, goals, and contexts, has therefore become essential for effective personalization and resource organization.

Building on these directions, the Symposium provides a forum for researchers, educators, curriculum developers, and EdTech practitioners to discuss how AI for Education, especially user modelling and GenAI, can be responsibly integrated into MOOCs, blended learning, and language learning contexts. It affiliated to the International Symposium on Emerging Technologies for Education 2025 (SETE 2025), in conjunction with the International Conference on Web-based learning 2025 (ICWL 2025), to be held in Hong Kong, China.

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 modeling and personalization in MOOCs and blended learning
  • AI-powered course assistants and classroom support tools
  • Automated formative assessment and feedback generation
  • Cognitive and affective modeling for adaptive learning
  • Context-aware and ontology-based user modeling
  • Learning resource recommendation and search
  • Sentiment analysis, opinion mining, and learner motivation tracking
  • Generative AI in Computer-Assisted Language Learning (CALL) and Mobile-Assisted Language Learning (MALL)
  • Evaluation of AI and emerging technologies in language learning and teaching
  • Pedagogical and socio-educational implications of AI adoption
  • Fairness, equity, privacy, and transparency in educational AI
  • Data-driven learning (DDL) and corpora in language teaching
  • Emerging technologies for language learning and teaching
  • AI for multimodal and collaborative learning environments
  • 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