SBIR Phase I: An Instruction and Learning Analytics Platform to Improve Learning and Teaching in Science, Technology, Engineering, and Mathematics

Period of Performance: 01/01/2014 - 12/31/2014

$150K

Phase 1 SBIR

Recipient Firm

YourLabs, LLC
4159 E. Stone River Dr.
Tucson, AZ 85712
Principal Investigator, Firm POC

Abstract

This SBIR Phase I project proposes to develop a novel diagnostic algorithm and methodology for obtaining detailed learner feedback in multi-step problem solving questions. This feedback is fundamental to derive learning patterns, identify at-risk learners, assess knowledge mastery, and inform both students and teachers about what was learned, what needs to be learned, and where and how mistakes were made. It informs the teacher what the students know and don?t know. The wealth of data collected by the proposed prototype will promote peer standards of excellence and student self-regulated learning, inform teaching practice, revise curricula, and inform educational administrators. This project is responding to a need in the educational system for personalized learning experiences for every learner, evidence-centered learning, and data that will improve teaching efficiency and effectiveness. The diagnostic assessment of the product will help educators understand the extent to which learners have mastered critical Science, Technology, Engineering, and Mathematics skills to identify specific areas in which improvement is needed and in which areas learners have mastered. The broader/commercial impact of this proposal is the real-time student feedback and the subsequent analysis of that data to efficiently transform Science, Technology, Engineering, and Mathematics education. It provides a formative, low cost technology product that can help teachers personalize and revise curriculum in real-time and promote step-by-step problem solving skills required for 21st century careers. This will help the U.S compete effectively in the global market. The in-depth learner database informs school administrators and education policymakers on changes required to improve student performances and teaching practice, and compliance with recently adopted common core state standards. Data mining across multiple levels - from single problem to school to district to state and internationally - allows school administrators to compare performances within the U.S. and abroad. This project allows for the discovery of knowledge gaps while enhancing teaching, learning and training in all educational settings.