SBIR Phase I: Developing a personality and usage-based user model for an advanced personalized learning system for pre-collegiate and remedial mathematics

This SBIR Phase 1 project proposes to demonstrate the feasibility of an advanced personalized learning system for pre-collegiate and remedial Algebra, with future extension to other scientific and mathematical disciplines. The project aims to model learning as a complex dynamics system, and to develop a user-model that incorporates student profile data with a detailed and large set of markers on usage and performance collected from an analytics engine. These markers can be derived from a student's learning and social activities, such as her interaction with various types of learning resources, participation on question and answer forums and so on. This model then guides a recommender system to select appropriate resources from a learning catalog based on the student's unique learning path. Whereas, the project uses open source recommender algorithms, the intellectual merit lies in developing a user model, identifying the specific markers that impact learning, automatically reconfiguring the learning material, and in demonstrating its viability for algebra learners. This model will be built leveraging some of the latest infrastructures in education technology including an authoring and delivery framework, a learning catalog of 10 million curated learning resources, and the latest advances in data-analytics and information filtering systems. The broader/commercial impact lies in using the proposed technology to replace textbooks and other less-advanced learning systems, not only in mathematics, but also in other STEM disciplines, making it easier, faster and more affordable for students to learn. To an extent, it will level the playing field by providing equal access to a personalized 1-on-1 type of experience, even for those students who don't have the opportunity to get high quality instruction and mentorship today. It will significantly impact students who today struggle with mathematics and STEM subjects, by providing alternate and more relevant ways for them to visualize and learn. Additionally, Zyante's technology and expanded services will enable colleges/universities to offer high-quality online courses and successfully handle larger enrollments. All this will ultimately improve national outcomes and provide a better-trained workforce in disciplines needed to drive the economic success of the US. For these reasons, it is important that the proposed technology be readily commercialized.