This SBIR Phase I project's broader/commercial impact of the proposed innovation is in the creation of a platform that can personalize the online learning experience using freely available online educational resources. The rising cost of education and professional development along with an increasing need for the same, create a need for affordable but high quality educational resources. The proposed project will add value to the online educational resources that are freely available and allow users to accomplish their educational goals at low or no cost. School and college students will be able to accomplish test preparation and the study of STEM subjects via resources that are best fit for their grade, ability and learning style. Professionals will be able to access courses that help them enhance their existing skills and learn new ones. As users' goals, interests, interactions and learning styles are revealed; the software will be able to provide high quality recommendations and enhanced personalization. Barriers that currently exist for learners based on income and geography can be eliminated by this disruptive technology. A freemium/ premium subscription model will keep the company viable despite providing free resources to the majority of users.
The project aims to enhance the value of currently available free online education resources to make it a better fit for learners' interests, goals, and learning styles. High quality online educational content is being generated by an increasing number of agencies and a lot of this content is freely available throughout the web. However, what is lacking is the customization of this ever-growing content to meet an individual user's specific learning needs. There is a strong need in the market to leverage the world's online educational content and build a web-based product with the ability to aggregate educational content from a wide variety of sources and provide it to the user with a high degree of personalization. Incorporating user goals, interests, past behaviors of learning, and user interactions into the users profile are important for providing the user with highly specific recommendations and creating a personalized experience. The use of machine learning and big data analytics, as well as other state of the art techniques will be key components in building such a product.
