A Case Study in Opportunities for Adaptive Experiments to Enable Rapid Continuous Improvement

Drawing inspiration from machine learning and experimentation in product development at leading technology companies, we explore how adaptive experimentation might help in continuous course improvement. In adaptive experiments, as different arms/conditions are deployed to students, data is analyzed and used to change the experience for future students. We discuss an example side-by-side comparison of traditional and adaptive experimentation of self-explanation prompts in online homework problems in a CS1 course. This provides the first step in exploring the future of how this approach can help bridge research and practice in continuous course improvement.