Yang (Arvin) Shi (Instructor) is an Assistant Professor of Computer Science 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 served as a program committee (PC) member in conferences across EdTech (EDM, LAK, SIGCSE, ICER) and AI (KDD, AAAI, NeurIPS) disciplines, and co-organized the Educational Data Mining in Computer Science Education (CSEDM) workshop since 2020.
Catherine A. Manly (Instructor) Catherine A. Manly is Assistant Professor of Higher Education–Data Analytics for Fairleigh Dickinson University’s online Ed.D. program. Her research addresses how flexibility of educational design and delivery can address under-acknowledged needs of students traditionally underserved by higher education. She brings a social justice lens to quantitative investigation of transformational innovation, with particular interest in the changes possible because of online and educational technologies. She is a three-time participant of the Learning Analytics in STEM Education Research (LASER) Institute at North Carolina State University. She is currently serving the first year of a two-year elected term on the Executive Committee of the Society for Learning Analytics Research (SoLAR).
Rachel A. Ayieko (Instructor) is an Associate professor in Mathematics Education. She has done extensive work in large scale data analysis especially in comparative international studies. Her research focus has been on factors that influence students learning of mathematics and supporting pre-service teachers to learn to teach mathematics. She is now transitioning to using R to analyze large data sets and is currently working on learning analytics using the TIMSS -2023 database.
Elizabeth B. Cloude (Instructor) is an Assistant Professor in Educational Psychology and Educational Technology at Michigan State University. Her research centers on measuring and modeling self-regulated learning processes during learning activities using multimodal learning analytics (eye movements, speech, facial expressions, and behaviors) and advanced learning technologies, (intelligent tutoring systems, game-based learning environments, etc.). Over the past decade, she has published extensively in leading journals such as IEEE Transactions on Affective Computing, Journal of Learning Analytics, and the International Journal of Artificial Intelligence in Education. She has organized workshops, contributed to professional development initiatives on data analytics in education, and served on program committees for conferences, including Games and Learning Alliance and Learning Analytics and Knowledge.
Hye Rin Lee (Instructor) is a Postdoctoral Research and Teaching Associate at the Owens Institute for Behavioral Research at the University of Georgia. Her research examines self-regulated learning processes, with a focus on motivation and metacognition, both independently and jointly. Situated primarily within STEM contexts, her work spans three interconnected lines of research: (a) designing interventions to promote motivation and metacognition; (b) examining how motivation, metacognition, or both relate to academic outcomes over time; and (c) developing innovative approaches that advance understanding of motivation and metacognition by challenging traditional assessment paradigms. Through this work, she aims to foster more inclusive and equitable learning environments in which all students can thrive and excel in STEM. Learn more about her at https://hyerinl.wordpress.com.
So Yeon Lee (Instructor) is an Assistant Professor in Educational Psychology and Research at the University of Alabama at Birmingham. Her research focuses on understanding students’ motivation and identity development, as well as exploring the social contexts that shape changes in motivation and the development of beliefs. She also teaches quantitative methods (e.g., intermediate and advanced statistical methods) at her current institution. Through her participation in the Learning Analytics in STEM Education Research (LASER) Institute at North Carolina State University, she has been developing materials for graduate students related to learning analytics and data mining.
Son T. H. Pham (Instructor) As the Research and Operation Director at Nha Viet Institute Boston, Dr. Pham bridges the gap between high-level AI research and the practical demands of operational scaling. His work focuses on synthesizing postfoundational theory with AI literacy, institutional effectiveness, and change management. An active contributor to the global research community, he has published through the American Educational Research Association (AERA) and served on the organizing committees for the International AIED conferences in Japan (2023) and Brazil (2024), connecting with leading experts worldwide. By leveraging data analytics and accreditation standards, he guides organizations through systemic transformations, ensuring that both educators and the future workforce are ready to thrive in an AI-driven global economy and supply chain.
Francesca A. Williamson (Instructor)
Tiffany Wright (Instructor) is an education professional with experience in administration, teaching, and research capacities. She has helped develop the professional, academic and financial capabilities of diverse student groups. Her experience with advising in financial and academic matters has proven her ability to provide resources while encouraging learning development on various platforms.
She completed a PhD in Education with an emphasis in Global Leadership and Change. As a mixed methods researcher, her research interests include cultural capital, STEM education for female learners, technological equity, and educational policy. She has taught coursework in research methods, scientific writing, and human development at the graduate level.
Jennifer K. Houchins (Contributor) is a Senior Research Associate at WestEd with over 18 years experience as an educator and developer of educational technology. Her work advances data-driven approaches to understanding how students learn computational thinking and programming concepts. Dr. Houchins has contributed to numerous NSF-funded projects examining the integration of computational thinking into K-12 curricula. Her scholarship employs sophisticated data mining and learning analytics methodologies to uncover patterns in student learning and inform instructional design, including developing assessments for middle school computer science and investigating programming knowledge transfer across languages. She provides leadership for large-scale research projects, mentoring junior researchers in mixed-methods approaches using R, and has been instrumental in examining how different pedagogical approaches—from game-based learning to narrative-centered platforms—support computational skill development.
Shaun B. Kellogg (Contributor) has over 20 years of experience in education as both a public school teacher and educational researcher. Since 2011, Dr. Kellogg has led comprehensive evaluations, applied research, and technical training programs funded by local, state, and national organizations including NSF, U.S. Department of Education, the North Carolina Department of Public Instruction (NCDPI), and the Gates Foundation. Prior to joining NCDPI to lead the new Office of Research and Promising Practices, he served as a Sr. Director of Research and Evaluation at the Friday Institute for Educational Innovation at NC State University, where he led the Learning Analytics in STEM Education Research (LASER) Institute. His work aims to empower educators, administrators, and policymakers through collaborative, data-intensive improvement research. Leveraging methods drawn from learning analytics and data science, he works closely with educators and policymakers to facilitate evidence-based decision-making and drive effective and innovative educational change.
Jeanne M. McClure (Contributor) is an Applied AI researcher and educator with seven years of experience in classical and modern AI and 15 years in curriculum development and learning sciences. Her research examined cognitive engagement in AI and data science education, with particular attention to participation and persistence across learner populations. As founder of Ars Innovate, she leads AI enablement and adoption for educators, business leaders, and SMEs through audit and evaluation frameworks, strategic consulting, and agentic technology solutions. Over the last two years, she has delivered 15+ workshops serving over 1,200 instructors and researchers interested in teaching and learning with data science and AI methodologies, across universities, industry sectors, and national science and engineering conferences. She served four years as one of the lead facilitators and project manager of the Learning Analytics in STEM Education Research (LASER) Institute at NC State University and completed a Postdoctoral Fellowship at NC State's Data Science and AI Academy.