Exploring Additional Personalized Support While Attempting Exercise Problems in Online Learning Platforms

Abstract

In online asynchronous learning environments, students are assigned exercises, but it is not clear how to incorporate the kinds of actions an in-person tutor might take such as explaining, providing more practice, prompting for reflection, and motivating. We explore approaches to adding "Drop-Downs'' that appear after a student submits an answer and that contain additional information to support learning. We conducted randomized A/B experiments exploring the impact of these Drop-Downs on student learning in the online portion of a flipped CS1 course. The deployed Drop-Downs in this course provided explanations, reflective prompts, additional problems, and motivational messages. The results suggest that students benefit from various Drop-Downs in different contexts, indicating the possibility of personalizing content based on the student's state. We discuss the resulting design implications of Drop-Downs in online learning systems.