Multidisciplinary Projects Drive Student Engagement in Data Science
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Statistics and data science topics are often viewed with trepidation by students of non-mathematical disciplines. This talk presents vignettes of interdisciplinary projects with strong Data Science themes which have successfully drawn engagement from diverse student populations. Three of the projects focus on problems related to the analysis of remote sensing data collected to survey the health of the Hawaiian islands’ coral reefs. The other projects relate to the identification of endemic Hawaiian bird calls using modern neural network machine learning techniques. Bringing multidisciplinary teams to bear on problems of local relevance drives interest in the application of data science skills from student populations that do not typically enroll in math and computer science courses where these techniques are taught. The guided application of advanced techniques also demonstrates the importance of basic results and definitions from probability, statistics, and related technical fields.
Dr. Grady Weyenberg is Assistant Professor of Mathematics at the University of Hawaii at Hilo. He received his Ph.D. in Statistics from the University of Kentucky in 2015. His research interests include mathematical biology and ecology as well as the effective use of technology and data in education.
Assistant Professor, UH Hilo