HCII Seminar Series - Eleanor O'Rourke
Eleanor (Nell) O'Rourke
Assistant Professor in Computer Science and the Learning Sciences at Northwestern University
This will be a virtual presentation.
"Why Do Students Think They're Bad at Programming? Towards Intelligent Systems to Support Motivation and Learning in CS1"
In this talk, I will introduce a surprising motivational challenge in the domain of computer science education: students often think they're bad at programming, even when they are performing well. I will present a series of studies showing that students in introductory courses assess their own programming ability frequently, using criteria that are often misaligned with best practices (e.g. "I should be able to debug quickly based off a first glance"; "I shouldn't have to sit there and think"). Then, I will show how we can use these self-assessment criteria as a lens to better understand student experiences and the ways they approach learning. Finally, I will present research exploring the design of intelligent programming environments that can automatically detect potential self-assessment moments and provide feedback to help students re-frame these experiences. Through this body of work, I will demonstrate the value of conducting research that crosses the boundaries of human-computer interaction and the learning sciences to deeply understand learning contexts and inform the design of novel learning environments.
Eleanor O'Rourke is an Assistant Professor in Computer Science and the Learning Sciences at Northwestern University, where she co-directs the interdisciplinary Delta Lab. Her research explores the design of novel computational systems to support motivation and learning in STEM domains. Recent projects include studying student beliefs about programming ability in introductory computer science courses, designing game mechanics that encourage students to practice effective problem-solving skills, and developing web inspection tools that allow novice developers to learn directly from authentic professional websites. Her interventions have been used by over 100,000 students online, adopted by companies, and integrated into classrooms. Her work has been recognized through an NSF CAREER Award, a Google Systems Research Award, and best paper awards and nominations at SIGCSE, UIST, and CHI.