Yariv Glazer
The Data Analysis & Visualization tool (DAVIS) project develops and tests the feasibility of a cloud-based interactive digital lab manual that integrates auto grading functionality. DAVIS consolidates 21st century technologies to provide students with a cutting-edge tool to improve their laboratory experience, and provide teaching staff with a system that minimizes the time requirements of lab report grading and promotes fairness in grading across lab sections. The project focuses on introductory chemistry courses at the college undergraduate level. It creates, studies and disseminates technology-based assessments, tools and learning materials to teach critical lab skills including acquisition, analysis, and reporting of data.
DAVIS algorithms incorporate big data and crowd sourcing principles to improve student learning and teaching practice. For example, the use of big data allows students to see the results of their work in comparison to their classmates through graphical visualizations of the data, and thereby enabling them to proactively correct their mistakes and improve their lab skills. The use of big data also allows teachers to see classroom trends, such as specific areas of student strengths and weaknesses, and thereby adjust their instruction to optimize student learning.