Attrition rates are a serious problem in U.S. education in both STEM and non-STEM fields and in traditional classroom and Massive Open Online Course (MOOC) settings. By detecting confusion and disengagement automatically and in the moment it occurs, the proposed technology enables instructors to respond immediately, spending more time on material when more help is needed. By preventing students from becoming discouraged and disenchanted, attrition rates may be reduced for STEM majors. Reducing the attrition rate by 7% would create half a million more STEM professionals.

This project addresses the growing e-learning phenomenon as well as traditional learning models. It proposes to use what has been discovered about brain signal technologies to improve learner engagement. Decades of research in neuro-signal processing produced methods for measuring a host of cognitive and affective metrics - attention, cognitive load, and engagement are a few. Building on this work, this team developed SynMetric that utilizes methods for detecting important metrics relevant to e-learning using portable inexpensive brain signal sensors - detecting text difficulty, reading comprehension, student confusion while watching course material, and user frustration while using a spoken dialog interface. SynMetric applies brain signal technologies proven in neuromarketing/neurocinema to help instructors better engage students. With SynMetric, instructors receive real-time information on the engagement and confusion level of students without any conscious effort from the student. This process is automatic so students simply listen to a lecture and minute-by-minute feedback is derived from their brain signals and transferred to an instructor dashboard without any conscious effort from the student. Additionally, this technology may inexpensively provide neurologically based measurements of engagement, expanding the traditional neuromarketing/neurocinema market to many other previously untapped markets e.g. small advertising studios, small film studios, independent branding managers, and small firms building their own branding.

Agency
National Science Foundation (NSF)
Institute
Division of Industrial Innovation and Partnerships (IIP)
Type
Standard Grant (Standard)
Application #
1439998
Program Officer
Rathindra DasGupta
Project Start
Project End
Budget Start
2014-06-01
Budget End
2015-11-30
Support Year
Fiscal Year
2014
Total Cost
$50,000
Indirect Cost
Name
Carnegie-Mellon University
Department
Type
DUNS #
City
Pittsburgh
State
PA
Country
United States
Zip Code
15213