Reviving Computer Science Education through Adaptive, Interest-Based Learning

Computing Education has become a widely popular research field at top universities with much attention aimed at improving and expanding K-12 computer science education. Though numerous efforts are being made by institutions, industries, and the community, many challenges still prevent widespread K-12 CS education. Our research aims to alleviate these challenges with a new adaptive learning system to teach introductory programming in a unique and interesting way. Adaptive learning strategies normally adapt based on a student's previous knowledge, pace, or learning style. Our research takes a new approach to adapt the content, practice problems, and examples based on a student's interests. Interest-based learning has been shown to improve intrinsic motivation, leading to better learning and achievements. This paper outlines how SAIL - a System for Adaptive Interest-based Learning - could impact introductory CS education and alleviate many of its challenges.