College of Engineering

In addition to being a mechanical engineer, associate professor Ning Fang has devoted much of his research to finding the most effective method for teaching engineering courses. He also involves local high school teachers in his research in hopes of improving student learning in high school physics and mathematics courses.

An one-year project "Improving Student Learning in Engineering Dynamics Through an Online Intelligent Learning System" was recently granted $19,992 by USU's Research Catalyst Funds

in hopes of engineering computer software that will exist as an online tutor. Fang hypothesizes the extra assistance the software will provide for his Engineering Dynamics class students will improve students' problem-solving skills. Fang says this software can be the temporary replacement of a human tutor, and will walk students through selected homework problems in order to increase the understanding and comprehension of the course material.

Fang has been conducting research to improve engineering education methods that involve student surveys and analysis of student success rates. His study on "Impact of Classroom Response Systems" looks into the effectiveness of iClickers in the classroom. The iClickers allow professors to immediately assess how well the students are learning the information they are dealt; it also makes the lecture interactive and engaging. Fang found 79 percent of students considered it a helpful tool in understanding the course material, and 86 percent of students believed iClickers promote active learning. With classes that hold more than 100 students, Fang also found value in using iClickers to take attendance.

In order to perk the success rate of engineering students who take the Fundamentals of Engineering exam, Fang has been formulating a mathematical model that will hopefully improve passing rates. He titled this project "Predicting Students' Academic Performance in Engineering Dynamics." Currently, the national passing rate for this exam is approximately 50 percent. This mathematical model will also work to help Fang predict the success of the students in his Engineering Dynamics class, which is the last course USU students must take before entering their specific engineering field. His formula includes multivariate linear regression, neural networking and the use of a support vector machine, which recognizes patterns and analyzes data.

Fang is using his background in mechanical engineering to establish a way to predict how successful a certain product is at cutting soft and hard materials, such as aluminum and titanium. The National Science Foundation granted his project $155,798. Along with post-doctoral researcher P. Srinivasa and student researchers N. Edwards and K. Nielsen, he is conducting research on how to predict the forces and vibrations that will occur when cutting these materials. If there are a lot of vibrations detected, the cut made in the material is usually poor. Fang also reached out to high school physics teachers in local school districts and involved them in this project. He aims to combine his passion for improving engineering education with hands-on mechanical work.

Finally, Fang is working on a project that aims to improve students’ problem-solving skills in Engineering Dynamics by developing a new set of computer simulation and animation modules that integrate mathematical modeling with visualization. The National Science Foundation granted his project $600,000.  He is also assessing how simulation modules affect student learning outcomes that are associated with diverse learning style preference, gender, and ethnic/racial background. Currently, one PhD student Ms. Y. Guo is working under his supervision on this project.