Special Session 11

Learning Sciences and Intelligent Education: Cognitive Engagement, Learning Analytics, and Pedagogical Innovation

Description
Learning sciences and intelligent education are increasingly shaping the future of teaching, learning, assessment, and educational innovation. As artificial intelligence, learning analytics, adaptive technologies, and intelligent learning environments become more deeply integrated into educational practice, there is a growing need to understand not only how these technologies support instruction, but also how they influence learners’ cognition, motivation, engagement, self-regulation, and knowledge construction. This special session focuses on the dynamic relationship between learning sciences and intelligent education, with particular attention to how evidence from cognitive, psychological, technological, and pedagogical research can inform the design of more effective, cognitively responsive, and pedagogically meaningful learning environments.
This session welcomes theoretical, empirical, and practice-oriented studies that examine intelligent education from interdisciplinary perspectives. Topics may include AI-supported learning, learning analytics, cognitive engagement, adaptive learning systems, self-regulated learning, smart classrooms, teacher-AI collaboration, digital pedagogy, and the ethical and responsible use of intelligent technologies in education. By bringing together scholars, educators, and practitioners, this session aims to promote deeper dialogue on how learning sciences can guide intelligent education toward meaningful learning, pedagogical innovation, educational equity, and sustainable educational transformation.

Session organizer
Prof. Hang Hu, Southwest University, China

The topics of interest include, but are not limited to:
▪ Artificial intelligence and generative AI in teaching and learning
▪ Learning sciences approaches to intelligent education
▪ Cognitive engagement, metacognition, and knowledge construction in digital learning environments
▪ Learning analytics, educational data mining, and evidence-informed teaching
▪ Adaptive learning systems and personalized learning pathways
▪ Self-regulated learning, learner agency, and motivation in intelligent learning environments
▪ Teacher-AI collaboration, digital pedagogy, and instructional innovation
▪ Ethical, inclusive, and responsible use of intelligent technologies in education

Submission method
Submit your Full Paper (no less than 5 pages with two colums) or your paper abstract-without publication (200-400 words) via Online Submission System, then choose Special Session 11 (Learning Sciences and Intelligent Education: Cognitive Engagement, Learning Analytics, and Pedagogical Innovation)
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Introduction of session organizer

Prof. Hang Hu
Southwest University, China

CHu Hang is a Professor and Doctoral Supervisor (including postdoctoral supervision). He serves as the Director of the Institute of Big Science Education; Director of the Research Office for Technological Civilization and Digital Humanities and Director of the Chongqing Key Laboratory for Strategic Development of Civilizational Mutual Learning at the China-Greece Center for Mutual Learning of Civilizations (a joint institute for regional and country studies under the Ministry of Education and a key research base for philosophy and social sciences in Chongqing); Director of the "Big Science Education" Virtual Teaching and Research Office (part of the Ministry of Education’s "Collaborative Quality Enhancement" initiative led by Southwest University); Rotating Executive Editor-in-Chief of the journal *Greek Studies*; Convener of the National (Big Science) Discipline Education Alliance; and a "Top 1% Highly Cited Scholar" on CNKI.
He holds positions as an expert for the Ministry of Education’s National Education Examinations Authority; Vice Chair of the Information Technology Education Committee under the Chinese Society of Education; Vice Chair of the Experimental Teaching Equipment Branch of the China Educational Equipment Industry Association; Executive Council Member of the Information Technology Education Committee under the China Association for Educational Technology; Council Member of the Learning Sciences Branch of the China Association of Higher Education; Member of the Group Standard Expert Committee of the China Educational Equipment Industry Association; and expert in basic education quality monitoring and social science popularization for Chongqing Municipality.
He has presided over more than 20 projects at the national, provincial/ministerial, and university levels. He has published over 80 papers in journals indexed by SCI, SSCI, and CSSCI, and authored or translated 14 books (including textbooks). His research output, *Empirical Study on Technology-Facilitated Deep Learning in Primary School Mathematics*, won the National Award for Outstanding Achievements in Empirical Educational Research. He serves on the editorial boards and as an external reviewer for several high-level journals. His "Deep Learning and Intelligent Education" experimental school network spans kindergartens, primary and secondary schools, vocational education (secondary and higher levels), and higher education. His projects cover areas such as reform of assessment mechanisms for high school and college entrance exams; early identification and cultivation of top-tier innovative talent; regional smart education development; intelligent "Grand Ideological and Political Education" (Big Ideological-Political Education); comprehensive educational reform for the New International Land-Sea Trade Corridor; comprehensive educational reform for the Yangtze River Economic Belt and the Chengdu-Chongqing Economic Circle; and mutual learning regarding technological civilization between China, Greece, and the Mediterranean region.
Key research areas include: deep learning and its educational applications; science, technology, and intelligent education; intelligent computing and digital humanities; and the history and philosophy of science and technology.