Yang (Arvin) Shi is an Assistant Professor at Utah State University. He has been working towards building data-driven methods for representing program code to enhance the ability of Intelligent Tutoring Systems and benefit student modeling processes for computing education. With a focus on DM/ML approaches applied to CS education, his research interests also include Programming Language Processing, Software Analysis, and Deep Learning. He has been serving as a (senior) program committee member in conferences across multiple disciplines, including EDM, LAK, AIED, KDD, AAAI, EAAI, SIGCSE, NEURIPS, and ITICSE.
Shan Zhang is a PhD Candidate in the educational technology program at the University of Florida. Before that, she gained her Ed.M. degree from Harvard University. Her research focuses on multi-model AI Literacy assessment, learning analytics, educational data mining, and AI in education. Shan's recent work explores integrating AI into K-12 education to support teaching and learning, using data-driven methods to analyze interaction from multiple data sources, collaborative learning processes, and affective states in STEM+C+AI contexts, and develop learner models.
Peter Brusilovsky is a Professor of Information Science and Intelligent Systems at the University of Pittsburgh, where he also directs the Personalized Adaptive Web Systems (PAWS) lab. He has been working in the field of adaptive educational systems, user modeling, and intelligent user interfaces for more than 30 years. He published numerous papers and edited several books on adaptive hypermedia and the adaptive Web. He is a founder of CS-SPLICE and has advanced research and infrastructure for CSEDM.
Thomas Price is an Associate Professor of Computer Science at North Carolina State University. His primary research goal is to develop learning environments that automatically support students through AI and data-driven help features. His work has focused on the domain of computing education, where he has developed techniques for automatically generating programming hints and feedback for students in real-time by leveraging student data. He has helped organized a number of efforts at the intersection of AIED, Data Mining and CS Education, including the CS-SPLICE working group on programming snapshot representation and prior CSEDM and CS-SPLICE workshops.
Bita Akram is an Assistant Professor with the Department of Computer Science at North Carolina State University. Her research lies at the intersection of artificial intelligence and advanced learning technologies with its application on improving access and quality of CS Education. She has been actively developing data-driven approaches for assessing students' CS competencies as demonstrated through their interactions with educational programming activities. She has served as the organizer and program committee for venues focused on educational data mining including EDM and CSEDM.
Juho Leinonen is an Assistant Professor and an Academy Research Fellow at Aalto University. His research focuses on creating better insight into students’ learning with fine-grained learning analytics; using educational technology and artificial intelligence for personalizing course content; and using learnersourcing to create ample learning opportunities for distinct student needs. He has served on the program committees of both computing education focused and educational data mining focused conferences.
Andrew (Shiting) Lan is an Associate Professor in the Manning College of Information and Computer Sciences, University of Massachusetts Amherst. His research focuses on the development of artificial intelligence (AI) and especially natural language processing (NLP) methods to enable scalable and effective personalized learning in education, covering areas such as learner modeling, personalization, content generation, and human-in-the-loop AI. He is a leader in developing generative models for student modeling.
Paulo Carvalho is an Assistant Professor in the Human-Computer Interaction Institute at Carnegie Mellon University. His research explores how AI can revolutionize learning by creating engaging, practice-first environments. He uses data analytics and computational modeling to understand student learning, motivation, and meta-cognition and develop precise models for better learning experiences. He's currently investigating how generative AI can power these practice-focused approaches, boosting engagement and freeing teachers to provide personalized support.
Ken Koedinger is a Professor of Human Computer Interaction and Psychology at Carnegie Mellon University. Dr. Koedinger has an M.S. in Computer Science, a Ph.D. in Cognitive Psychology, and experience teaching in an urban high school. His multidisciplinary background supports his research goals of understanding human learning and creating educational technologies that increase student achievement. His research has contributed new principles and techniques for the design of educational software and has produced basic cognitive science research results on the nature of student thinking and learning. Koedinger directs LearnLab, which started with 10 years of National Science Foundation funding and is now the scientific arm of CMU’s Simon Initiative. LearnLab builds on the past success of Cognitive Tutors, an approach to online personalized tutoring that is in use in thousands of schools and has been repeatedly demonstrated to increase student achievement, for example, doubling what algebra students learn in a school year. He was a co-founder of CarnegieLearning, Inc. that has brought Cognitive Tutor based courses to millions of students since it was formed in 1998, and leads LearnLab, now the scientific arm of CMU’s Simon Initiative. Dr. Koedinger has authored over 250 peer-reviewed publications and has been a project investigator on over 45 grants. In 2017, he received the Hillman Professorship of Computer Science and in 2018, he was recognized as a fellow of Cognitive Science.
Tiffany Barnes is a Distinguished Professor of Computer Science at NC State University. She received the B.S. and M.S. degrees in Computer Science and Mathematics, and the Ph.D. degree in Computer Science from N.C. State. A member of Phi Beta Kappa and the NC State Golden Chain Society, she has served ACM SIGCSE (Symposium Chair 2018, Program Chair 2017, Board 2011-2016), IEEE Special Technical Community on Broadening Participation (Chair, and founder of the RESPECT conference (2015-present)), the International Educational Data Mining Society (EDM chair 2016, board 2011-present), STARS Computing Corps (Co-Director 2006-present, Celebration Chair 2011, 2015), Foundations of Digital Games (Program Chair 2014), the International Society for AI in Education (Board 2016-Present), and IEEE Transactions on Learning Technologies (Assoc. Editor 2016-Present). Dr. Barnes received an NSF CAREER Award for her novel work in using data and educational data mining to add intelligence to STEM learning environments. Dr. Barnes is co-Director for the STARS Computing Corps, a consortium of universities that engage college students in outreach, research, and service to broaden participation in computing. Her research focuses on AI for education, educational data mining, serious games for education, health, and energy, computer science education, and broadening participation in computing education and research.
Arun Balajiee Lekshmi Narayanan | University of Pittsburgh, USA
Luc Paquette | University of Illinois at Urbana-Champaign, USA
Andrew Petersen | University of Toronto, Canada
Juan Pinto | University of Illinois at Urbana-Champaign, USA
Maria Mercedes T. Rodrigo | Ateneo de Manila University, Philippines
Cliff Shaffer | Virginia Tech, USA
Andy Smith | North Carolina State University, USA
Cansu Tatar | Northern Illinois University, USA
Khushboo Thaker | University of Pittsburgh, USA
Leo Ureel II | Michigan Technological University, USA
Zichao Wang | Adobe, USA
Yingbin Zhang | South China Normal University, China
Zhikai Gao | North Carolina State University, USA
Adam Gaweda | North Carolina State University, USA
Arto Hellas | Aalto University, Finland
Muntasir Hoq | North Carolina State University, USA
Nguyen-Thinh Le | Humboldt-Universität zu Berlin, Germany
Naiming Liu | Rice University, USA
Michael Liut | University of Toronto, Canada
Lauri Malmi | Aalto University, Finland