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Early Prediction of Students’ Performance via Machine Learning

Technology

The vast majority of U.S. undergraduate students are unable to graduate in four years. Those who graduate tend to lack diplomas in high demand majors: science, technology, engineering and math (STEM). America needs more science, engineering and technical graduates to enter the workforce, pay taxes, contribute to the economy, and repay their student loans. According to the US Department of Education, the four-year graduation rate for students attending public colleges and universities is 33.3%. The six-year rate is 57.6%. At private colleges and universities, the four-year graduation rate is 52.8%, and 65.4% earn a degree in six years. Students who graduate in four years rather than six save money on tuition, housing, administrative fees and student loans. To graduate in four years, students must take and pass at least 15 credits a semester. Multiple factors hinder students passing 15 credits per semester: financial stress, housing issues, food insecurity and poor course selection. Researchers have identified several evidence-based approaches to improving retention and graduation rates: optimized high school-to-college transition processes, student engagement and student achievement programs.
Rowan University investigators have developed a smartphone app that identifies high-risk undergraduate students early in a semester. After answering 5 multiple choice questions and a course-related, open-ended question after each class, the Rowan app provides instructors with a prediction of student engagement. Natural language processing tools can analyze student open-ended text.


Competitive Advantages
● Smartphone-based solution.
● 87% accurate in initial study for predicting student final grades.
● Useful for schools that lack a learning management system (LMS).


Opportunity
Rowan’s app addresses the student information services (SIS) segment of the LMS market, a $9.2 billion industry expected to earn $22.4 billion by 2023 at a CAGR of 19.6%. Rowan University seeks a partner to further develop and commercialize this technology through a license. The inventor is available to collaborate with interested companies.

Patent Information:
Category(s):
Engineering
Software
For Information, Contact:
Neal Lemon
Associate Vice President
Rowan University
lemonna@rowan.edu
Inventors:
Amir Miri Ramsheh
Seyyed Salili
Keywords:
App
Classroom
Data
Smartphone