SBIR Phase II: Developing a Structured Student-guided Personalized Learning System for Mathematics

This SBIR Phase II project develops novel adaptive techniques for web-based learning materials, and creates Algebra and Statistics content using those techniques. College textbooks and homework are being replaced with web-based learning materials that are highly-interactive, involving animations, learning questions, and auto-generated auto-graded homework/quiz exercises. The project develops those exercises to adjust (adapt) to the learner's performance as well as to the learner's preferences, providing a novel structured form of adaptivity that maximizes learning efficiency while reducing student anxiety, in contrast to many other proposed adaptive techniques. The project creates new content for the topics of Algebra and for Statistics, two critical subjects with which many college students struggle. The result will be greater success (and less failure) in Algebra and Statistics courses by young college students, leading to more graduates in STEM (science, technology, engineering, and math) fields, which contribute greatly to the nation's productivity and competitiveness. The techniques can be applied to many other STEM and non-STEM subjects, and for learning beyond college courses too. This SBIR Phase II project develops novel adaptive techniques for web-based learning materials, called structured student-guided adaptive (SSGA) techniques. In contrast to some recent adaptive commercial products, SSGA preserves the ability of an instructor to maintain a structured path through the material, which is critical for keeping students in synch with lecture/discussion sessions, for enabling students to study with classmates, and more. Adaptivity comes in several forms, including auto-generating successively-harder problems based on correct completion of earlier problems, with explanations and source material carefully integrated to ensure students learn underlying concepts. Also, the adaptivity is in part guided by the student, who can choose to start with simpler or harder problems, or can auto-generate self-quizzes based on performance, selected material, and more. In contrast with other products, student-guided adaptivity gives students appropriate control over their learning, yielding a sense of empowerment and reducing anxiety that can inhibit learning. The project builds the authoring platform necessary to support SSGA material creation, building upon a previously-developed authoring framework for interactive web material. The project also creates new material for college algebra and statistics courses, whose high attrition rates can be reduced by replacing traditional textbooks/homework with SSGA material.