Mathbrix LLC

Sbir Phase Ii: Building Mathematical Thinking and Problem-solving Skills Together Through Play -the Broader Impact/commercial Potential of This Small Business Innovation Research (SBIR) Phase Ii Project Will Be to Address Major Deficits in Mathematical Achievement Among Children Living in the United States, and to Develop New Modes and Approaches to Learning With Mobile Technology. a Growing Body of Research Shows That the Human Brain Is Most Receptive to Learning Math Concepts in the Pre-school Years and That Children Who Do Not Receive Appropriate Instruction at This Early Age Often Fail to Achieve in Mathematics Later in Life. This Is of Particular Concern Because Mathematical Ability Is Highly Correlated Academic Success and Future Jobs Increasingly Require Strong Math and Problem-solving Skills, Resulting in Significant Implications for the Competitiveness of Tomorrow?s Workforce. This Phase Ii Project Will Develop a Next Generation Education Technology That Guides Families and Children Through a Series of Learning Activities, Performed Mostly Off-screen, But Which Are Guided an Artificial Intelligence (ai)-powered Mobile Learning Application. This Technology Supports New Approaches to Learning and Has Applications in the Commercial Sector as Products Using Natural Language Processing (NPL) Continue to Proliferate. This Small Business Innovation Research (SBIR) Phase Ii Project Involves the Development of New Learning Technologies That Can Encourage Parent Child Interaction and Aim to Increase Parent Engagement in Learning Experiences With Their Children (ages 3-8). a Cloud-connected Mobile Applications Will Provide Regular Opportunities for Parent and Child to Build Early Math and Problem-solving Skills in Age-appropriate, Meaningful Contexts. Machine Learning Algorithms Deliver Activities That Match Developmental Milestones, Learning Objectives, and Family Interest. Animated Characters Guide Users Through Activities Both on and Off Computer and Prompt Meaningful Conversations by Asking Both Parent and Child Open-ended Questions. Ai Technology Analyzes Recorded Feedback to Obtain the Degree of Engagement by Considering Nuances Such as Voice Tone, Phrasing, and Number of Conversational Turns. 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.