Time
Friday, 02/26/21 at 12:00 PM - 1:00 PM (Central)
Title
Harnessing Student Solutions to Support Learning at Scale
Abstract
A challenge to meet the demand on higher education and professional development is to scale these educational opportunities while maintaining their quality. My work tackles this challenge by harnessing examples from existing resources to enable the creation of scalable and quality educational experiences.
In this talk, I will describe my work that contributes insights about developing effective learning at scale systems by leveraging the complementary strengths from peers, experts, and machine intelligence, differentiating it from existing systems that solely rely on machine or crowds of peers. Specifically, I’ll focus on a technique UpGrade, which uses student solution examples to semi-automatically generate multiple-choice questions for deliberate practice of higher order thinking in varying contexts. From experiments in authentic college classrooms, I show that UpGrade helps students gain conceptual understanding more efficiently and helps improve students' authentic task performance. Through an iterative design process with instructors, I demonstrate the generalizability of this approach and offer suggestions to improve the quality and efficiency of college instruction.
Bio
Xu Wang is an Assistant Professor in Computer Science and Engineering at the University of Michigan. Xu recently completed her Ph.D. in the Human-Computer Interaction Institute in the School of Computer Science at Carnegie Mellon University, advised by Dr. Ken Koedinger and Dr. Carolyn Rose. She conducts interdisciplinary research within the fields of Human-Computer Interaction, Cognitive Science, Artificial Intelligence and Education. Her work has been published at many top-tier conferences and journals in Human-Computer Interaction and Educational Technologies. Before coming to CMU, she received a Masters in Education from Harvard Graduate School of Education and a Bachelor’s in Science from Beijing Normal University. She has also worked in the User Interface Research Group at Autodesk Research. See more: https://web.eecs.umich.edu/~xwanghci/