Ning Fang PhD

Publications | Journal Articles

Academic Journal

• Mayer, M., Fang, N., (2016). Factors affecting persistence of undergraduate engineering students: A quantitative research study using institutional data. International Journal of Engineering Education. Vol. 32(5A), pp. 1879-1887
• Fang, N., Guo, Y., (2016). Interactive computer simulation and animation for improving student learning of particle kinetics. Journal of Computer Assisted Learning. Vol. 32(5), pp. 443-455.
• Fang, N., Srinivasa, P., Edwards, N., (2016). Neural network modeling and prediction of surface roughness in machining aluminum alloys. Journal of Computer and Communications, Vol. 4, pp. 1-9.
• D’Mello, G., Srinivasa, P., Puneet, N., Fang, N., (2016). Surface roughness evaluation using cutting vibrations in high speed turning of Ti-6Al-4V - An experimental approach. International Journal of Machining and Machinability of Materials. Vol. 18(3), pp. 288-312
• Fang, N., Lawanto, O., Goodridge, W.H, Villanueva, I., Becker, K., (2016). A Research Experiences for Undergraduates (REU) Site Program on Engineering Education Research. International Journal of Engineering Education. Vol. 32(5A), pp. 1836-1846
• Ha, O., Fang, N., (2016). Spatial ability in learning engineering mechanics: critical review. Journal of Professional Issues in Engineering Education and Practice. Vol. 142(2), pp. 04015014-1 to 04015014-11
• Liu, G., Fang, N., (2016). Student misconceptions about force and acceleration in physics and engineering mechanics education. International Journal of Engineering Education. Vol. 32(1A), pp. 19-29.
• Fang, N., (2014). Difficult concepts in engineering dynamics: Students’ perceptions and educational implications. International Journal of Engineering Education. Vol. 30(5), pp. 1110-1119.
• Santoso, H.B, Lawanto, O., Becker, K., Fang, N., Reeve, E.M, (2014). High and Low Computer Self-Efficacy Groups and Their Learning Behavior from Self-Regulated Learning Perspective While Engaged in Interactive Learning Modules. Journal of Pre-College Engineering Education Research (J-PEER), 4:2, 11-28. doi: http://dx.doi.org/10.7771/2157-9288.1093
• Fang, N., Srinivasa, P., Edwards, N., (2014). A method of using Hoelder exponents to monitor tool-edge wear in high speed finish machining. International Journal of Advanced Manufacturing Technology. Vol. 72, pp. 1593-1601.
• Fang, N., Zhao, X., (2014). A cross-cultural comparison of learning style preferences between American and Chinese undergraduate engineering students. International Journal of Engineering Education. Vol. 30(1), pp. 179-188.
• Fang, N., (2014). Correlation between students’ motivated strategies for learning and academic achievement in an engineering dynamics course. Global Journal of Engineering Education. Vol. 16(1), pp. 6-12.
• Fang, N., Srinivasa, P., Edwards, N., (2013). A comparative study of high-speed machining of Ti-6Al-4V and Inconel 718, Part I: Effect of dynamic tool edge wear on the cutting forces. International Journal of Advanced Manufacturing Technology, 2013, Vol. 68(5), pp. 1839-1849.
• Fang, N., Srinivasa, P., Edwards, N., (2013). A comparative study of high-speed machining of Ti-6Al-4V and Inconel 718, Part II: Effect of dynamic tool edge wear on the cutting vibrations. International Journal of Advanced Manufacturing Technology, 2013, Vol. 68(5), pp. 1417-1428
• Fang, N., Guo, Y., (2013). A web-based interactive intelligent tutoring system for enhancing student learning in a foundational engineering dynamics course. International Journal of Engineering Education. 2013, Vol. 29(6), pp. 1503-1513.
• Fang, N., (2013). Increasing high school students’ interest in STEM education through collaborative brainstorming with Yo-Yos. Journal of STEM Education: Innovations and Research. 2013, Vol. 14(4), pp. 34-40.
• Huang, S., Fang, N., (2013). Predicting student academic performance in an engineering dynamics course: A comparison of four types of predictive mathematical models. Computers and Education, 2013, Vol. 61, pp. 133-145.
• Fang, N., Nielson, K., Kawamura, S., (2013). Using Computer Simulations with a Real-World Engineering Example to Improve Student Learning of High School Physics: A Case Study of K-12 Engineering Education. International Journal of Engineering Education, 2013, Vol. 29(1), pp. 170-180.
• Fang, N., (2012). Using tablet PCs to quickly assess students’ problem-solving performances in an engineering dynamics classroom. World Transactions on Engineering and Technology Education, Vol. 10(4), pp. 247-252.
• Fang, N., (2012). A student-centered active learning approach to teaching grant proposal writing in a Ph.D. in engineering education program. International Journal of Engineering Education, Vol. 28(5), pp. 1168-1176.
• Fang, N., (2012). Using computer simulation and animation to improve student learning of engineering dynamics. Procedia-Social and Behavioral Sciences Journal,Vol. 56(8), pp. 504-512.
• Fang, N., (2012). Students’ perceptions of dynamics concept pairs and correlation with their problem-solving performance. Journal of Science Education and Technology, Vol. 21(5), pp. 571-580
• Fang, N., Srinivasa, P., Edwards, N., (2012). Tool-edge wear and wavelet packet transform analysis in high-speed machining of Inconel 718. Strojniški vestnik - Journal of Mechanical Engineering, Vol. 58 (3), pp. 191-202
• Fang, N., Srinivasa, P., Edwards, N., (2012). Wavelet-Based Denoising of Vibration Signals for Tool-Edge Wear Detection in High Speed Machining of Inconel 718. Advanced Materials Research, Vol. 415-417, pp.1512-1515.
• Fang, N., (2012). Improving engineering students’ technical and professional skills through project-based active and collaborative learning. International Journal of Engineering Education, Vol. 28(1), pp. 26-36.
• Fang, N., (2011). Tree of Dynamics: A modified concept mapping approach to improving student conceptual understanding in engineering dynamics. International Journal of Engineering Education, Vol. 27(6), pp. 1352-1361.
• Fang, N., Srinivasa, P., Mosquea, S., (2011). A comparative study of sharp and round edge tools in orthogonal machining with built-up edge formation: cutting forces, cutting vibrations, and neural network modeling. International Journal of Advanced Manufacturing Technology, Vol. 53(9-12), pp. 899-910.
• Fang, N., Srinivasa, P., Mosquea, S., (2011). Effect of tool-edge wear on the cutting forces and vibrations in high-speed finish machining of Inconel 718: an experimental study and wavelet transform analysis. International Journal of Advanced Manufacturing Technology, 52:1-4, 65-77.
• Fang, N., (2011). A new methodology for assisting the development of instructional awareness in teaching a large engineering class with academically diverse students. International Journal of Engineering Education, 27:1, 167-177.
• Fang, N., Srinivasa, P.P, Mosquea, S., (2010). The effect of built-up edge on cutting vibrations in machining 2024-T351 aluminum alloy. International Journal of Advanced Manufacturing Technology, 49, 63-71.
• Fang, N., Srinivasa, P.P, Edwards, N., (2010). Prediction of built-up edge formation in machining with round edge and sharp tools using a neural network approach. International Journal of Computer-Integrated Manufacturing, 23:11, 1002-1014.
• Huang, S., Fang, N., (2010). Prediction of student academic performance in an engineering dynamics course: development and validation of multivariate regression models. International Journal of Engineering Education, 26:4, 1008-1017.
• Fang, N., Lu, J., (2010). A decision tree approach to predictive modeling of student performance in engineering dynamics. International Journal of Engineering Education, 26:1, 87-95.

An asterisk (*) at the end of a publication indicates that it has not been peer-reviewed.

Publications | Other

Other

An asterisk (*) at the end of a publication indicates that it has not been peer-reviewed.