Topic outline

  • Introduction

    The 7th CyberPsychology and Behavioral Seminar is hosted by the Chinese Psychological Society, Youth Psychology, and Behavior Lab of Education Ministry and the School of Psychology of Central China Normal University. The seminar aims at providing a platform for researchers from psychology, educational technology or information science backgrounds to share their ideas and resources and help improve related research and implication. The focus of this year is "models and analysis of self-improving adaptive instructional systems.

    • Over ten experts will give keynote speeches on most advanced adaptive instructional systems (AIS)
    • One panel discussions about AIS * Lessons learned  * Stat of the Art, * Future outlook * Benefit and potential issues, * Ethics in AI in Education.
    • Two Workshops: 1) Generalized Intelligent Framework for Tutoring (GIFT), 2) Conversation-Based Intelligent Tutoring Systems.

  • Schedule

    Link to the schedule

    File: 1
  • Art Graesser

    Dr. Art Graesser is a professor in the Department of Psychology and the Institute of Intelligent Systems at the University of Memphis and is an Honorary Research Fellow in the Department of Education at the University of Oxford. He received his Ph.D. in psychology from the University of California at San Diego. 

    Art's primary research interests are in cognitive science, discourse processing, and the learning sciences. More specific interests include knowledge representation, question asking and answering, tutoring, text comprehension, inference generation, conversation, reading, problem solving, memory, emotions, computational linguistics, artificial intelligence, human-computer interaction, and learning technologies with animated conversational agents. He has published over 600 articles in journals, books, and conference proceedings. 

    Art has been Principal Investigator or co-PI on 70 grants or contracts -- approximately $45 million of external funding for the University of Memphis. This funding has primarily come from National Science Foundation, Institute of Education Sciences, National Institutes of Health, Office of Naval Research, Army Research Laboratory, and Advanced Distributed Learning.    

    Art served as editor of the journal Discourse Processes (1996–2005) and Journal of Educational Psychology (2009-2014) and as president of the Empirical Studies of Literature, Art, and Media (1989-1992), the Society for Text and Discourse (2007-2010), the International Society for Artificial Intelligence in Education (2007-2009), and the Federation of Associations in Behavioral & Brain Sciences (2012-13).  He has participated on four OECD expert panels on problem solving: ,he 2011 Programme for the International Assessment of Adult Competencies (PIAAC) on Problem Solving in Technology Rich Environments, the 2012 Programme for International Student Assessment (PISA) on Complex Problem Solving, PISA 2015 Collaborative Problem Solving (chair), and PIAAC Complex Problem Solving 2021. He has been a member of four expert panels of the National Academy of Sciences, Engineering, and Medicine, including the recent panel on the second edition of How People Learn.  

    Dr. Graesser and his colleagues have designed, developed, and tested software that integrates psychological sciences with learning, language, and discourse technologies.  These include AutoTutor, DeepTutor, ElectronixTutor, MetaTutor, GuruTutor, HURA Advisor, SEEK Web Tutor, Operation ARIES!, iSTART, Writing-Pal, iDRIVE, the Personal Assistant for Life Long Learning (PAL3), AutoCommunicator, Point & Query, Question Understanding Aid (QUAID), QUEST, & Coh-Metrix.

    In 2010, Dr. Graesser received the Distinguished Scientific Contribution Award (Society for Text and Discourse) and in 2011 he received the Distinguished Contributions of Applications of Psychology to Education and Training Award (American Psychological Association).  On February 28, 2012, Dr. Graesser received the first Presidential Award for Lifetime Achievement in Research from the University of Memphis. This award is the University’s highest level of research recognition given to its faculty. It was established as part of the University’s Centennial fundraising campaign in order to recognize the vital role and impact of research at the University of Memphis.  In 2018 he received the Harold W. McGraw, Jr. Prize in Education.   

  • Steve Ritter

    Steven Ritter, Founder and Chief Scientist at Carnegie Learning, has been developing and evaluating educational systems for over 20 years. He earned his Ph.D. in Cognitive Psychology at Carnegie Mellon University and was instrumental in the development and evaluation of Cognitive Tutors for mathematics. Through leadership of the research department, Dr. Ritter has led many improvements to the use of adaptive learning systems and math education in real-world settings. He is the author of numerous papers on the design, architecture and evaluation of Intelligent Tutoring Systems. He is lead author of an evaluation judged by the US Department of Education’s What Works Clearinghouse as fully meeting their standards and is lead author of a "Best Paper" at the International Conference on Educational Data Mining.

  • Noboru Matsuda

    I am an associate professor of computer science and a director of the Innovative Educational Compting Laboratory at North Carolina State University. I am also an affiliate of the Center for Educational Informatics.

    My primary research focus is on the technology innovation and integration to advance the sciences of learning.

    I am interested in the innovation and application of Artificial Intelligence technologies for students to learn, teachers to teach, and researchers to understand how people learn (and, more importantly, fail to learn!). I am therefore an engineer of transformative technologies and a practitioner to improve education.

    I am also interested in studying the transformative theory of learning and teaching that brings us with the significant knowledge on how people learn and how people should be taught. I am therefore a learning scientist working on the empirical data collected from field studies conducted with the learning technologies that I invent.

  • Dragan Gasevic

    Dragan Gasevic is Professor of Learning Analytics in the Faculty of Information Technology at Monash University since Feb 2018. Previously, he was a Professor and Sir Tim O'Shea Chair in Learning Analytics and Informatics in the Moray House School of Education and the School of Informatics at the University of Edinburgh from Feb 2015 to Feb 2018. He also was the Canada Research Chair in Semantic and Learning Technologies and a Professor in the School of Computing and Information Systems at Athabasca University from Jan 2007 to Feb 2015. He is a co-founder and served the President (2015-2017) of the Society for Learning Analytics Research. He holds several honorary appointements including an Honorary Professor in the Moray House School of Education and the School of Informatics at the University of Edinburgh, an Adjunct Professor in the School of Interactive Arts and Technology at Simon Fraser University, Adjunct Professor in the School of Education at the University of South Australia, a Research Scientist in the LINK Research Lab at the University of Texas, Arlington, Adjunct Professor in the Centre for Distance Education at Athabasca University, and a Distinguished Professor in the Institute for Research in Open and Innovative Education at the Open University of Hong Kong. A computer scientist by training and skills, Dragan considers himself a learning analyst developing computational methods that can shape next-generation learning technologies and advance our understanding of information seeking, sense-making, and self-regulated and social learning. Funded by granting agencies and industry in Australia, Canada, Europe, and USA, Dragan is a recipient of several best paper awards at the major international conferences in learning and software technology. The award-winning work of his team on the LOCO-Analytics software is considered one of the pioneering contributions in the growing area of learning analytics. Recently, he has founded ProSolo Technologies Inc that develops a software solution for tracking, evaluating, and recognizing competences gained through self-directed learning and social interactions. Committed to the development of international research community, Dragan had a pleasure to serve as a founding program co-chair of the International Conference on Learning Analytics & Knowledge in 2011 and 2012 and the general chair in 2016 as well as a founding program co-chair of the Learning Analytics Summer Institute in 2013 and 2014. He also served as a founding editor of the Journal of Learning Analytics (2012-2017) and is a (co-)author of numerous research papers and books and a frequent keynote speaker.

  • Gautam Biswas

    Gautam Biswas is a Professor of Computer Science, Computer Engineering, and Engineering Management in the EECS Department and a Senior Research Scientist at the Institute for Software Integrated Systems (ISIS) at Vanderbilt University. He has an undergraduate degree in Electrical Engineering from the Indian Institute of Technology (IIT) in Mumbai, India, and M.S. and Ph.D. degrees in Computer Science from Michigan State University in E. Lansing, MI.

    Prof. Biswas conducts research in Intelligent Systems with primary interests in hybrid modeling, simulation, and analysis of complex embedded systems, and their applications to diagnosis, prognosis, and fault-adaptive control. As part of this work, he has worked on fault-adaptive control of fuel transfer systems for aircraft, and Advanced Life Support systems for NASA. He has also initiated new projects in health management of complex systems, which includes online algorithms for distributed monitoring, diagnosis, and prognosis. More recently, he is working on data mining for diagnosis, and developing methods that combine model-based and data-driven approaches for diagnostic and prognostic reasoning. This work, in conjunction with Honeywell Technical Center and NASA Ames, includes developing sophisticated data mining algorithms for extracting causal relations amongst variables and parameters in a system. In other research projects, he is involved in developing simulation-based environments for learning and instruction. The most notable project in this area is the Teachable Agents project, where students learn science by building causal models of natural processes. He has also developed innovative educational data mining techniques for studying students’ learning behaviors and linking them to metacognitive strategies. His research has been supported by funding from NASA, NSF, DARPA, and the US Department of Education. His industrial collaborators include Airbus, Honeywell Technical Center, and Boeing Research and Development. He has published extensively, and has over 300 refereed publications.

    Dr. Biswas is an associate editor of the IEEE Transactions on Systems, Man, and Cybernetics, Prognostics and Health Management, and Educational Technology and Society journal. He has served on the Program Committee of a number of conferences, and most recently was Program co-chair for the 18th International Workshop on Principles of Diagnosis and Program co-chair for the 15th International Conference on Artificial Intelligence in Education. He is currently serving on the Executive committee of the Asia Pacific Society for Computers in Education and is the IEEE Computer Society representative to the Transactions on Learning Technologies steering committee. He is also serving as the Secretary/Treasurer for ACM Sigart. He is a senior member of the IEEE Computer Society, ACM, AAAI, and the Sigma Xi Research Society.

  • 胡祥恩(Xiangen Hu)

    Dr. Xiangen Hu is a professor in the Department of PsychologyDepartment of Electrical and Computer Engineering and Computer Science Department at The University of Memphis (UofM) and senior researcher at the Institute for Intelligent Systems (IIS) at the UofM and is professor and Dean of the School of Psychology at Central China Normal University (CCNU). Dr. Hu received his MS in applied mathematics from Huazhong University of Science and Technology, MA in social sciences and Ph.D. in Cognitive Sciences from the University of California, Irvine. Dr. Hu is the Director of Advanced Distributed Learning (ADL) Partnership Laboratory at the UofM, and is a senior researcher in the Chinese Ministry of Education’s Key Laboratory of Adolescent Cyberpsychology and Behavior.

    Dr. Hu's primary research areas include Mathematical Psychology, Research Design and Statistics, and Cognitive Psychology. More specific research interests include General Processing Tree (GPT) models, categorical data analysis, knowledge representation, computerized tutoring, and advanced distributed learning. Dr. Hu has received funding for the above research from the US National Science Foundation (NSF), US Institute of Education Sciences (IES), ADL of the US Department of Defense (DoD), US Army Medical Research Acquisition Activity (USAMRAA), US Army Research Laboratories (ARL), US Office of Naval Research (ONR), UofM, and CCNU.

  • Robby Robson

    Dr. Robson has had a diverse and successful career as a researcher, entrepreneur, and innovator in industry and academia. He has made significant contributions to mathematics, learning technology, education, and the development of interoperability standards. He is co- founder and CEO of Eduworks Corporation, a company that applies artificial intelligence, text mining, and other advanced technologies to improve human performance, and he serves on multiple boards and committees of the IEEE Standards Association and IEEE Computer Society. Robby has played leadership and governance roles in small businesses and professional societies and is currently leading the open source CASS project that is developing transformative infrastructure for competency-based education, training, and career management.

  • Robert Sottilare

    Dr. Robert Sottilare is the Science Director for Intelligent Training at Soar Technology, Inc. He came to SoarTech in 2018 after completing a 35-year federal career in both Army and Navy training science and technology organizations. At the US Army Research Laboratory, he led the adaptive training science and technology program where the focus of his research was automated authoring, instructional management, and analysis tools and methods for intelligent tutoring systems (ITSs) and standards for adaptive instructional systems. He is a co-creator of the Generalized Intelligent Framework for Tutoring (GIFT), an open source, AI-based adaptive instructional architecture.  GIFT has over 2000 users in 76 countries.

    Dr. Sottilare has long history as a leader, speaker, and supporter of learning and training sciences forums at the Defense & Homeland Security Simulation, HCII Augmented Cognition, and AI in Education conferences.  He is the founding chair of the HCII Adaptive Instructional Systems (AIS) Conference. He is a member of the AI in Education Society, the Florida AI Research Society, the IEEE Computer Society and Standards Association, the National Defense Industry Association (lifetime member), and the National Training Systems Association. He is currently the IEEE Project 2247 working group chair for the development of standards and recommended practices for AISs. He is a faculty scholar and adjunct professor at the University of Central Florida where he teaches a graduate level course in ITS design.

    Dr. Sottilare has also been a frequent lecturer at the United States Military Academy (USMA) where he taught a senior level colloquium on adaptive training and ITS design.  He has a long history of participation in international scientific fora including NATO and the Technical Cooperation Program. He has over 200 technical publications in the learning sciences field with over 1500 citations in the last 5 years. His doctorate is in Modeling & Simulation with a focus in Intelligent Systems from the University of Central Florida.

    Dr. Sottilare is a recipient of the US Army Meritorious Service Award (2018; 2nd highest civilian award), the US Army Achievement Medal for Civilian Service (2008; 5th highest civilian award), and two lifetime achievement awards in Modeling & Simulation: US Army RDECOM (2012; inaugural recipient) and National Training & Simulation Association (2015).

  • 唐杰(Jie Tang)

    I am a Full Professor and the Associate Chair of the Department of Computer Science and Technology of Tsinghua University. I obtained my Ph.D. in DCST of Tsinghua University in 2006. My research interests include artificial intelligencedata mining, social networks machine learning and knowledge graph, with an emphasis on designing new algorithms for mining social and knowledge networks.

    I have been visiting scholar at Cornell University (working with Prof. John Hopcroft and Jon Kleinberg), University of Southampton (working with Dame Wendy Hall), KU Leuven (working with Marie-Francine Moens), University of Illinois at Urbana-Champaign (short term, working with Jiawei Han), Chinese University of Hong Kong (working with Jeffrey Yu), and Hong Kong University of Science and Technology (working with Qiong Luo). During my graduate career, I have been an intern at NLC group of Microsoft Research Asia from 2004 to 2005. I also have attended the internship program of IBM China Research Lab in 2004.

    I have published more than 200 journal/conference papers and hold 20 patents. I served as PC Co-Chair of CIKM’16WSDM’15, Associate General Chair of KDD’18, and Acting Editor-in-Chief of ACM TKDD, Editors of IEEE TKDEIEEE TBD, and ACM TIST. I am leading the project for academic social network analysis and mining, which has attracted more than 10 million independent IP accesses from 220 countries/regions in the world. I was honored with the UK Royal Society-Newton Advanced Fellowship AwardCCF Young Scientist AwardNSFC for Distinguished Young Scholar, and KDD’18 Service Award.

    I am looking for highly-motivated students to work with me on the exciting area of social network, data mining, and machine learning. I also have a few open Postdoctoral Positions to investigate underlying theory and algorithms in data mining, social networks, machine learning, and knowledge graph.

  • 朱廷劭 (Tingshao Zhu)

    Tingshao Zhu is the scholar of the "Hundred Talents Program" of the University of Chinese Academy of Sciences. He received a Ph.D. from the Institute of Computing Technology of the University of Chinese Academy of Sciences in 1999 and the University of Alberta in Canada in 2005. Dr. Zhu’s research interests include machine learning and network behavior psychology. , He was the first person using a data mining technique to explore rules underneath the Chinese rhythm, the Chinese words and sentences. The machine learning method he proposed has been widely used to train the user's browsing behavior model. He has studied various internet user features including user personality, mental health, attitude towards society and provided intervention based on the prediction of user behavior. He has led major grants such as the National Natural Science Foundation of China, the Ministry of Science and Technology 973 and 863, the National Social Science Fund, and the Chinese Academy of Sciences Class A Pilot Project, and published more than 60 papers.

  • 周宗奎 (Zongkui Zhou)

    Zongkui Zhou a Professor of School of Psychology of the Central China Normal University, the director of the Key Laboratory of Adolescent Cyberpsychology and Behavior, Ministry of Education. He is also the executive director of the Chinese Psychological Association, the director of the Network Psychology Committee of the Chinese Psychological Association and the China Psychology Associate Director of the Society for Developmental Psychology. Dr. Zhou’s research interests are the developmental and educational psychology, cyberpsychology, and mental health education. His long-term research concerns include the social and personality development of children and adolescents, the growth and education of left-behind children in rural areas, the mental health education in primary and secondary schools, and the psychological and behavioral development of adolescents. He has led more than 10 projects including the National Natural Science Foundation of China, the major projects of the National Social Science Fund, and the international collaborative projects. He has been entitled leading talent of several national projects.

  • 刘三女牙(Sanya Liu)

    刘三女牙,博士,教授,博士生导师。 现任华中师范大学国家数字化学习工程技术研究中心、教育大数据应用技术国家工程实验室常务副主任,同时兼任教育部高等学校教学信息化与教学方法创新指导委员会教育技术专业教学指导分委员会委员、华中师范大学学术委员会委员、《大数据》杂志编辑委员会委员、全国信息技术标准化委员会教育技术分技术委员会委员等,2011年入选教育部“新世纪优秀人才”计划,2012 年入选湖北省”新世纪高层人才”计划,2016 年获湖北省“科技创新源泉工程”创新创业人才称号,2017 年获湖北省政府专项津贴,主要研究方向为教育技术、教育大数据、教育人工智能,承担包括国家科技支撑与重点研发计划、国家社科基金、国家自然科学基金、省级重大项目等项目 20 余项,发表学术论文 100 余篇,出版著作 10 部;获得国家授权专利 40 余项,荣获湖北省科技进步一等奖 2 项、二等奖 1 项、高等教育国家教学成果二等奖 1 项、湖北省高等学校教学成果一等奖 1项。

  • 张立山(Lishan Zhang)

    张立山博士是华中师范大学国家数字化学习工程技术研究中心副研究员,毕业于美国亚利桑那州立大学,一直从事人工智能教育应用,智能导学系统,学习分析等相关研究。担任包括Computers & Education, Interactive Learning Environments等多本国际期刊的同行评审。在2019年国际学习分析大会(LAK)上,主办了Innovative problem solving assessment with learning analytics的工作坊。为国家自然科学基金下教育信息科学与技术青年项目首批获资助者。

  • Frank Andrasik

    Frank Andrasik 教授是孟菲斯大学心理学系行为医学中心的杰出教授、主席和主任,同时担任《应用心理生理学 和生物反馈》、《行为治疗》等杂志的主编,在美国心理学协会(健康心理学和临床心理学学会)、心理科学协会和行为医学学会中担任研究员。先后获得西佛罗里达大学授予的“杰出的研究和 创造性活动奖”,AAPB(应用精神生理学和生物反馈协会)授予的优异奖和杰出科学家奖,以及西佛罗里达大学学术和创造性活动奖等。

    Andrasik 教授的研究工作集中在行为医学领域,主要是慢性疼痛、 头痛和应激障碍、基础和应用心理生理学以及军人多重创伤。Andrasik 教授发表了大约 270 篇文章和书本章节,并在美国、巴西、加拿大、 中国、丹麦、英国、芬兰、法国、德国等发表了多场演讲,同时也活跃在临床领域,被列入国家认证的心理健康服务者,担任多个机构的顾问。

  • 孙茂松(Maosong Sun)

    孙茂松教授是清华大学计算机科学与技术系系主任,教授,博士生导师。研究方向为自然语言理解、中文信息处理、Web 智能、社会计算和计算教育学等。孙茂松教授作为项目负责人,主持 973 二级课题、863 重大专项二级课题、国家自然科学基金重点项目、国家自然科学基金项目、863 项目、国际合作项目等约 20 项,主持信息处理用分词国际标准 2 项。在国际刊物、国际会议、国内核心刊物上共发表论文 130 余篇,获得国家发明专利 4 项。多次担任相关领域国际会议 和全国性学术会议大会主席或程序委员会主席。主要学术兼职为中国中文信息学会副理事长,国务院学位委员会第六届学科评议组计算机科学与技术组成员,国家自然科学基金委员会第十二届专家评审组成员,北京市语言文字工作委员会专家委员会副主任,中国计算机学会理事,全国术语标准化技术委员会委员,中关村开放实验室联盟副理事长,浙江省地税信息化建设专家顾问委员会委员,《中文信息学报》 (计算机类全国核心期刊)主编,Journal of Computer Science and Technology、《中国计算机学会通讯》、《计算机科学与探索》、《计 算机教育》、《语言文字应用》、《南开语言学刊》、《澳门语言学刊》等期刊编委,863 重点项目“中文为核心的多语言处理技术”总体专家组组长等。

  • 袁莉(Li Yuan)

    袁莉博士是英国教育技术和互操作性标准中心 Cetis 的高级研究员和学习技术顾问。目前,她正在通过 Jisc 智能校园 项目和学习分析项目,来智能地利用数据改善学生的体验,并提高大学的教与学水平。她一直在从事一些欧盟资助的大型项目,如“Rage”,“LACE”和“Tel-MAP”。 她感兴趣的主要领域是研究并理解教育领域的新兴技术和创新实践。她发表了一系列的简报文件、白皮书以及与政策、管理、技术或一线读者相关的报告( author/cetisli)。她的报告“MOOCs 与开放教育:对高等教育的影响”在国际上受到政府机构、教育组织和技术公司的好评。袁莉博士创建了一个以中国为基地的开放式在线学习平台 Wolne (,以便利英国的大学和学者通过在 线课程和数字技术与中国的大学生接触,并探索国际教育的新模式和新方法。

  • 刘凯(Kai Liu)

    刘凯博士,华中师范大学心理学院博士后,孟菲斯大学 FIT 智能研究院访问学者,渤海大学教育科学学院讲师,心理健康教育研究生导师。 具有计算机、心理学、教育学、管理学、医学等多学科知识背景,拥有丰富的软件开发和社会实践经验,具有较强的科研能力和项目管理水平, 关注国际前沿问题并主动寻找本土解决方案,当前主要研究方向为:通用人工智能、机器教育、 计算精神病学。除常规科研工作外,还是教育大科学前沿论坛(2016、2017、2018、2019)及中国通用人工智能协会(筹) 的召集人和组织者(该会议每周举办,具有较大的影响力)。

  • 燕翔(Xiang Yan)

    燕翔京师乐学副总裁、京师城投董事长。 燕翔先生带领京师乐学致力与大数据,教育技术服务偏远山区教育,其创办的京师城投在贵阳市注册成立不到两年时间,其研发的各类软件著作权系统达 20 余个。其中,“大数据+教育”精准扶贫项目入选教育部 2018 年度教育信息化教学应用实践共同体项目,获得教育部 2018 年教育管理信息化优秀案例。

  • 崔炜(Wei Cui)

    崔炜博士是乂学教育-松鼠 AI 联合创始人、首席科学家,被《麻省理工科技评论》 中国区“35 岁以下科技创新 35 人”,上 海市人工智能高级职称认定正高级工程师,AI 学术会议 ACM-CIKM-19本地主席。前 Realizeit 核心算法科学家,人工智能、 智适应学习和大数据专家,人工智能博士和博士后,师从全球遗传算法顶级专家,发表了 27 篇 AI 和大数据相关的国际学术论文,获得过 IEEE-CIFER 最佳学术论文奖, 在全球顶级学术会议发表过 40 多次国际学术演讲。

  • Workshops

    • 通用智能辅导框架 (GIFT) (10.11 14:00-17:30)

      主讲人:Robert Sottilare、胡祥恩
    • AutoTutor 工作坊(10.12 8:30-12:00)