Siqing Weir received both bachelor’s and master’s degrees in electrical and Computer Engineering from Purdue University. He is currently pursuing a Ph.D. degree in Engineering Education at Purdue University. After years of experience of serving a peer teacher and a graduate teaching assistant in first-year-engineering courses, he is a research assistant at CATME research group studying the existence, causes and interventions on international engineering teamwork behaviors, the integration and implementation of team-based assignments and projects into STEM course designs and using mixed-method, especially natural language processing to student written research data, such as peer-to-peer comments. Siqing also works as the technical support manager at CATME research group.
Rui Wang is an undergraduate student at School of Electrical and Computer Engineering at Purdue University. His research interests include interpretable machine learning, robust computer vision and natural language processing.
Matthew W. Ohland is Associate Head and the Dale and Suzi Gallagher of Professor of Engineering Education at Purdue University. He has degrees from Swarthmore College, Rensselaer Polytechnic Institute, and the University of Florida. His research on the longitudinal study of engineering students, team assignment, peer evaluation, and active and collaborative teaching methods has been supported by the National Science Foundation and the Sloan Foundation and his team received for the best paper published in the Journal of Engineering Education in 2008, 2011, and 2019 and from the IEEE Transactions on Education in 2011 and 2015. Dr. Ohland is an ABET Program Evaluator for ASEE. He was the 2002–2006 President of Tau Beta Pi and is a Fellow of the ASEE, IEEE, and AAAS.
Dr. Gaurav Nanda is an Assistant Professor of Practice in the School of Engineering Technology at Purdue University. He completed his Ph.D. in Industrial Engineering from Purdue University and Masters and Bachelors from Indian Institute of Technology Kharagpur, India.
His research interests include application of text mining and machine learning methods to analyze real-world data. Currently, he is studying learner experiences in online courses by applying text mining approaches on user generated data such as discussion forums and open-ended feedback.
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