The goal of my research is to create computing systems that maximize student learning both online and in the classroom. Specifically, my dissertation explores the design, implementation, and evaluation of novel educational systems that increase motivation, provide personalized learning experiences, and support formative assessment. As part of this work, I have created an incentive structure that promotes the growth mindset in an educational game, developed a framework for automatically generating instructional scaffolding, and evaluated a system that visualizes student data in real-time to assist classroom teachers. In the development of these systems, I combine ideas from computer science, psychology, education, and the learning sciences to develop novel technical methods of integrating learning theory into computational tools. In addition to evaluating my work through classroom studies with students and teachers, I have also conducted large-scale online experiments with tens of thousands of students. My findings provide new insights into how students learn and how computing systems can support the learning process. The ultimate goal of my research is to build personalized data-driven systems that transform how we teach, assess, communicate, and collaborate in learning environments.
Nell is a PhD candidate in Computer Science and Engineering at the University of Washington, advised by Zoran Popovic in the Center for Game Science. She received a B.A. in Computer Science and Spanish at Colby College in 2007, and an M.S. in Computer Science from the University of Washington in 2012. Her research lies at the intersection of human-computer interaction and educational technology with a focus on creating novel learning systems to support motivation, personalization, and formative assessment. Nell has won several awards and scholarships, including the Google Anita Borg Scholarship and the Microsoft Research Graduate Women’s Scholarship.
You can read more about her work and keep up to date at her CSE site.