I-Corps: A flexible learning and assessment tool based on a skill mastery approach

The broader impact/commercial potential of this I-Corps project will serve the national interest by improving the ability of universities to train a globally competitive STEM (Science, Technology, Engineering, and Mathematics) workforce. The core technology in this project provides students with the opportunity to practice questions in a personalized environment until mastery is achieved.

The technology also makes it easy for instructors to incorporate frequent and second chance testing while scaling to support more students. These pedagogical strategies have been shown to reduce the failure rates in STEM classes and could disproportionately benefit women, minorities, first-generation students, and students of low socio-economic status.

Helping these students can improve retention efforts, in general, and for diverse students, in particular. The commercial potential of this project includes capturing a significant fraction of the rapidly-growing university education technology market with potential markets worldwide as well as in non-university education sectors.

This I-Corps project aims to develop a Software as a Service (SaaS) online platform for creating and delivering learning experiences and assessments for students, with a focus on university-level STEM (Science, Technology, Engineering, and Mathematics) courses. The platform allows instructors to easily combine adaptive, rule-based and artificial intelligence (AI) algorithms to generate and grade different randomized versions of activities and assessments.

It includes novel AI auto-grading algorithms for complex question types including symbolic mathematics, interactive student drawing, live coding, and natural language input. The core algorithms advance the state of the art in three key ways: (1) The use of AI auto-grading can entirely eliminate the use of human graders in university courses, dramatically reducing staffing levels and costs, and enabling expansion to larger and more diverse student populations; (2) The platform deters cheating with a set of novel algorithms; and (3) The platform uses sophisticated grading algorithms that incentivize mastery learning and that lead to substantial improvements in learning outcomes.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.