ZHOU Wei, Beijing Jiaotong University, China (wzhou@bjtu.edu.cn)
CHEN Yulin, National Penghu University of Science and Technology, Taiwan region (yulinchen@gmail.com)
QIANG Yan, School of Software, North University of China, China (27420265@qq.com)
Artificial intelligence has not only changed the forms and content of education but also put forward new requirements for the development, integration, and distribution of educational resources. Universities, primary and secondary schools, enterprises, scientific research institutions, and social venues all played crucial roles in science popularization education. How can we efficiently build science popularization educational resources and effectively carry out science popularization activities in the age of artificial intelligence? This special session aims to bring together various parties to explore the paths and strategies for constructing science popularization educational resources in the age of artificial intelligence, providing theoretical support and practical guidance for building a more inclusive social education system.
Topics include but are not limited to:
● Application of artificial intelligence in the development of science popularization educational
resources;
● Construction of information technology and programming resources for young people;
● Sustainable development of science popularization activities, such as organizing volunteers,
planning personalized activities;
● Successful cases and practical experience.
Prof. ZHOU Wei is Senior Researcher of Computer Science and Technology at Beijing Jiaotong University, China. She received the Ph.D. degree from Nagoya University (Japan).
With main research interests in Data Science, AI, System Engineer, Education Technology, Information Services, she has published many papers of international conference and journals, and served on some editorial boards.
See more: http://faculty.bjtu.edu.cn/8405/
CHEN Yulin, Ph.D., is an associate professor in the Department of Marketing and Logistics Management at National Penghu University of Science and Technology. She received the Ph.D. degree from Nagoya University (Japan). She delivers advanced instruction in Internet Marketing, Big Data Analytics, Social Media Analysis, and Quantitative Research Methods.
Dr. CHEN's academic inquiry is centered on the intersection of social media mining, large-scale data analytics, AI-enhanced multimodal content interpretation, and latent topic modeling.
Prof. QIANG Yan, Dean of the School of Software, North University of China, PhD in Engineering, Professor, Doctoral Supervisor. He is a famous teacher in Shanxi Province, an expert in engineering education certification of the Ministry of Education, a standing member of the Virtual Reality and Visualization Committee of the China Computer Society, and an executive member of the Education Committee. In recent years, he has published more than 80 SCI papers, including one highly cited paper in the top 1% of ESI global top.
Prof. Qiang is mainly engaged in the research of computer application technologies such as medical image processing and artificial intelligence algorithms, focusing on the cross-disciplinary research of medicine and engineering.
See more: https://ss.nuc.edu.cn/info/1022/4136.htm
QU Dapeng, Liaoning University, China (dapengqu@lnu.edu.cn)
HE Qiang, Northeastern University, China (heqiang@bmie.neu.edu.cn)
The rapid advancement of artificial intelligence (AI) is revoluting education, various innovative AI-driven methodologies, tools, and platforms are reshaping how computer practice is taught and learned. AI is integrated into curriculum design, personalized learning experiences, automated assessment systems, and the ethical considerations of AI in education etc. By bringing together educators, researchers, and industry experts, this session is intended to provide a forum to share insights, challenges, and future directions in AI-enabled computer practice teaching.
Topics include but are not limited to:
● AI-Driven Learning Paths in Computer Science Education;
● Automated Assessment and Feedback Systems in Programming Courses;
● Ethical Implications of AI in Educational Settings;
● AI-Enhanced Virtual Labs for Computer Practice;
● Integrating AI into Curriculum Design.
QU Dapeng, PhD, Associate Professor, Master's Supervisor, Senior Member of CCF, Executive Committee Member of Computer Education Committee, and Internet Committee in CCF. Director of the Science and Innovation Center, Faculty of Information, Liaoning University, Outstanding Party Affairs Worker of Liaoning Province, and Outstanding Young Faculty Member in Liaoning University.
HE Qiang received the Ph.D. degree in computer application technology from the Northeastern University, Shenyang, China in 2020. He also worked with School of Computer Science and Technology, Nanyang Technical University, Singapore as a visiting PhD researcher from 2018 to 2019. He is currently Professor at the College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China. His research interests include cloud computing, edge computing, machine learning, social network analytic, health care, etc. He has published more than 90 journal articles and conference papers, including IEEE/ACM Transactions on Networking、IEEE Transactions on Knowledge and Data Engineering、IEEE Transactions on Mobile Computing、IEEE Transactions on Neural Networks and Learning Systems、NeurIPS、AAAI.
LUO Juan, Hunan University, China (juanluo@hnu.edu.cn)
ZHAO Huan, Hunan University, China (hzhao@hnu.edu.cn)
CAI Yuhui, Hunan University, China (rj_cyh@hnu.edu.cn)
The widespread application of artificial intelligence (AI) technology is accelerating the transformation of the educational ecosystem, driving innovation in curriculum systems, interdisciplinary integration, and the modernization of teaching and management models. To address this trend, this session focuses on core issues such as the design of AI general education systems, multidisciplinary collaborative innovation, and AI-empowered teaching, aiming to explore new educational paradigms tailored to the intelligent era.
Topics include but are not limited to:
● Design and Exploration of AI General Education Curriculum Systems:
Development of AI literacy frameworks and curriculum reforms for students across diverse academic disciplines;
● Interdisciplinary Integration and Research in AI:
Curriculum reforms for cultivating cross-disciplinary talent through AI applications in fields such as humanities, social sciences, and
engineering;
● Practical Teaching Research in AI:
Innovations in teaching models, laboratory platform design, case study development, student competency training, and evaluation of
educational outcomes in AI practice;
● AI-Empowered Teaching:
Research on AI-driven personalized learning, intelligent tutoring systems, automated assessment, and educational big data analytics.
This session seeks to establish a collaborative forum for AI education research, promote the translation of theoretical advancements
into practical teaching, and provide systematic solutions for educators worldwide.
Juan Luo, Ph.D., is a professor, doctoral supervisor, and associate dean at the College of Computer Science and Electronic Engineering. She earned her bachelor's degree from the National University of Defense Technology and her master's degree and Ph.D. from Wuhan University. Previously, she worked at Fiberhome Networks, a company affiliated with the Wuhan Academy of Posts and Technology, and was a visiting scholar at the University of California, Irvine. She has been recognized as a New Century Outstanding Talent by the Ministry of Education and was granted the Hunan Province Outstanding Youth Fund.
Her current research focuses on IoT, cloud computing, and artificial intelligence.
See more: http://csee.hnu.edu.cn/people/luojuan
ZHAO Huan, Ph.D., Professor, doctor supervisor, associate dean, College of Computer science and Electronic Engineering. She is visiting scholar at the University of California, San Diego, the member of the Computer Basic Teaching Steering Committee of the Ministry of Education, and the member of the Steering Committee of the Education and Training of Industrial and Information Talents. She won the second prize of National Teaching Achievement Award, the Outstanding prize of BAOGANG distinction teacher and Huo Yingdong Education Foundation Education and Teaching Award.
Her research interests include embedded computer systems and speech information processing.
See more: http://csee.hnu.edu.cn/people/zhaohuan
CAI Yuhui is an associate professor at the College of Computer Science and Electronic Engineering in Hunan University whose research interests include computer networks, image processing, and artificial intelligence. He won the second prize of the Chinese University Science and Technology Award. And he was employed by the Ministry of Education of PRC in 2023 as a member of the course construction team for Computer Science Undergraduate Education and Teaching pilot reform program.
See more: http://csee.hnu.edu.cn/people/caiyuhui
WU Yonghui, Fudan University, China (yhwu@fudan.edu.cn)
Now all professions reliant on tool-based skills, including programmers, are being replaced by AI technologies. First, the lecture analyzes programming education and programming contests, and proposes cultivating computational and mathematical thinking through solving problems by programming is the breakthrough point for the reform of computer education in the AI era.
Second, the lecture demonstrates cultivating computational and mathematical thinking:
● The book series “for collegiate programming contests and education”: programming knowledge system and programming strategies,
using programming contest problems and their analyses as experimental learning units;
● Curriculums for solving problems by programming: The guiding ideology is programming is a technology. Case teaching is as the
teaching mode. And virtual programming contests are informatization technologies;
● “1+M+N” programming training system cross regions: one programming curriculum series for solving problems by programming,
collaborating across regions with M universities, enabling N students to benefit from the learning experience. Finally, the
innovation and effects are introduced;
Dr. WU Yonghui, associate professor at Fudan University, visiting scholar at Stony Brook University, and adjunct professor at Quanzhou University of Information Engineering. He won three medals in ACM ICPC World Finals for Fudan University. His book series “Collegiate Programming Contests and Education” has been published in simplified and traditional Chinese and English: the former by respective publishers of mainland China and Taiwan, and the latter by CRC Press. Since 2013, he has been giving lectures not only in China, but also in other countries.