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Learning Analytics Seminar Series

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About

Data about learning and learners are being generated today on an unprecedented scale. To that end, the Learning Analytics Seminar Series founded at Teachers College – Columbia University, aims to bring together leading industry researchers and practitioners around the issues and current trends of methodology and application of learning analytics. These talks aim to both inform our internal conversation and to generate a broader conversation around educational data mining and cognitive data science.

This is an ongoing series scheduled at the convenience of our invited speakers. Time and dates of talks are emailed to our member list, all talks are free and open to the public.

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Interested in becoming a speaker? Send a talk title, presentation abstract, and bio to joshua.coleman@tc.columbia.edu

Current Organizers

Joshua Coleman
Joshua Coleman is a Master of Science student in Learning Analytics at Teachers College, Columbia University, where his research interests focus on the importance of effective design in digital learning environments, data analytics for formative evaluation of technologies; and the use of immersive, adaptive, and interactive technologies for instruction. Joshua received his Bachelor of Science degree in Social Science, two graduate certificates in Blended and Online Learning and Teaching and Online Instructional Development, respectively; and a Masters of Science in Instructional Systems and Learning Technologies from Florida State University. He currently consults on a project with Alliance for PROS, an organization formed by academic leaders and funded by the Bill and Melinda Gates Foundation, in order to examine the effects of courseware interventions in postsecondary readiness, outcomes & success.

Past Organizers (from most recent)

Chad Coleman
Chad ColemanChad Coleman received his Bachelor of Science degree in Social Science and a graduate certificate in Blended and Online Learning and Teaching at Florida State University. He continued his education at New York University (NYU) where he completed his Masters of Arts in Administration, Leadership & Technology with a focus in Digital Media and Design for Learning. Chad’s current research interests revolve around harnessing the power of educational Big Data mining, analytics, and applied machine learning in order to measure and predict learner knowledge growth and behavior outcomes. He recently graduated from Teachers College, Columbia University with a Masters of Science in Learning Analytics and remains a Ph.D. candidate in the Cognitive Studies in Education program.

Sunmin Lee
Sunmin LeeSunmin Lee is a Master of Science student in Learning Analytics at Teachers College, Columbia University, where her research focuses on data-driven decision making using large-scale and cross-national comparable data. As an educational data scientist, her interest lies in resolving data discrepancies in the organizational/governmental level by using both inferential statistics and innovative data mining applications. She is especially interested in improving national Educational Management Information System and adapting it into real-time monitoring system in order to impact on better policy planning for developing countries. Sunmin is currently working at the international organization, the United Nations International Children’s Emergency Fund (UNICEF) HQs in New York, the Division of Data, Research, and Policy and at the same time, the member of Dr. Alex Bowers’ research group. Prior to her joining in New York, she served as a statistician at United Nations Educational, Scientific, and Cultural Organization (UNESCO) HQs in Paris and at UNESCO Institute for Statistics in Bangkok. Sunmin holds Bachelor of Science in Statistics and Economics from Sookmyung Women’s University, Republic of Korea. She was awarded as a first college student Professional Intern Representing Korea at the United Nations from the Ministry of Gender Equality and Family, Republic of Korea.

Dr. Ryan Baker
Dr. Ryan BakerDr. Baker researches how students use and learn from educational games, intelligent tutors, and other kinds of educational software. Drawing on the fields of educational data mining, learning analytics, and human–computer interaction, he develops methods for mining the data that come out of the interactions between students and educational software. He then uses this information to improve our understanding of how students respond to educational software, and how these responses influence their learning. Dr. Baker is currently serving as Director of the Penn Center for Learning Analytics.