Abstract: As more students recognize the opportunities that computing provides, undergraduate computing learners are increasingly diverse. Yet, methods to teach computing remain largely the same. I aim to understand the challenges and values of particular student groups and create new computing education interfaces that better align with students’ goals, interests, and prior experience.
In this talk, I will demonstrate how innovative models of interaction with computing education that constrain unnecessary complexity can support student motivation and success. First, I will talk about my research understanding why students reject code tracing, an ubiquitous introductory programming learning activity. I found that for all novices, high cognitive load can be a barrier, and for non-majors in particular, how tracing supports their goals is unclear. Second, I will introduce purpose-first programming, a new instructional approach designed for learners who care more about code’s applications than how code works. By reimagining programming instruction to focus on domain-specific code patterns, I was able to motivate learners with low self-efficacy for programming. Third, I will describe my work with a highly guided transfer pathway program that tripled the number of Latinx graduates in computer science at CSU Monterey Bay. By implementing a cohort model and centralizing student support, over 70% of program participants graduated in three years.
I will conclude with future directions for my research. In addition to understanding learners and developing novel learning interfaces, my vision is to support transitions between highly-constrained and traditional learning methods, scale purpose-first programming with platforms that assist in code pattern identification and curriculum design, and identify best practices for transfer students in computer science.
Bio: Dr. Kathryn Cunningham is a Postdoctoral Scholar and CIFellow at Northwestern University, supervised by Dr. Eleanor O’Rourke. Her research uses approaches from human-computer interaction in the context of computing education to diversify and improve the way we teach at the undergraduate level. She has won several awards and fellowships, including the NSF Graduate Research Fellowship and two Best Paper Awards at SIGCSE. She received her PhD from the University of Michigan in Information, advised by Dr. Mark Guzdial and Dr. Barbara Ericson, her MS from Georgia Tech in Computer Science (Human-centered Computing), and her BS from the University of Arizona in Computer Science and Molecular and Cellular Biology. Before her PhD, Kathryn was the Computer Science Education Coordinator for the CSin3 program at CSU Monterey Bay.