COMPUTATIONAL SOCIAL SCIENCE RESEARCH COLLOQUIUM /COLLOQUIUM IN COMPUTATIONAL AND DATA SCIENCES – Understanding Behavior in Interactive Environments: Deriving Meaningful Insights from Data – Michael Eagle
Computational Social Science Research Colloquium /Colloquium in Computational and Data Sciences
Michael Eagle, Asst. Professor
Department of Computational and Data Sciences
George Mason University
Understanding Behavior in Interactive Environments: Deriving Meaningful Insights from Data
Friday, September 21, 3:00 p.m.
Center for Social Complexity, 3rd Floor Research Hall
All are welcome to attend.
Abstract: Advanced learning technologies are transforming education as we know it. These systems provide a wealth of data about student behavior. However, extracting meaning from such datasets is a challenge for researchers; and often impossible for the instructors. Understanding learner behavior is critical to finding, extracting, and acting on insight found in educational data. It is equally important to have strong evaluative methodologies to explore the effectiveness of new interventions, and pinpoint when, where, and precisely what students are learning.
This talk covers the ways I have combined human modeling, qualitative, quantitative (statistical and machine learning) methods enable researchers to make sense of behavior and to produce data-driven personalization. I will have a focus on modeling of humans in interactive problem-solving environments, such as intelligent tutoring systems, online courses, and educational video games. Combining results from experimental design, machine learning, and cognitive models results in large improvements to existing learning systems, as well as powerful insights for instructors and researchers on how students behave and learn in interactive environments.