Mia Taylor began her freshman year at Virginia Tech as a five-year accelerated bachelor of science/master of science program in computer science. She will graduate this semester (FALL 2022) and has already accepted a position of research engineer on the machine learning team at Graf Research in Blacksburg.
Her research at the Sanghani Center has focused on how students use the interactive dimensionality reduction application Andromeda. “I want to understand how students — when given complex data analysis tools — learn from the experience of conducting exploratory data analysis,” said Taylor, who is advised by Chris North.
Taylor’s collaborative full paper, “Andromeda in the Classroom: Collaborative Data Analysis for 8th Grade Engineering Design,” was published by the 2022 American Society for Engineering Education (ASEE) Annual Conference and Exposition in June.
For this study, the classroom teacher uploaded data describing projects to Andromeda with each point in the visualization representing a student’s design. With Andromeda controlled by the teacher, students used it to visualize, analyze, and compare their designs in extended conversation with each other and the teacher and collectively explore their design-related data.
““Despite not having the mathematical background to understand dimensionality reduction, the students in our study learned about relations between variables and felt that Andromeda helped them compare their designs in a friendly, but competitive manner,” Taylor said.
In the study, she said, the team also suggested ways of improving Andromeda’s utility as a public, educational resource and provided an example of class activity aligned with Virginia’s proposed Standards of Learning in data science.
Taylor was introduced to research in visualization while doing an undergraduate capstone project in human-computer interaction.
“The Sanghani Center conducts interesting research within data science and machine learning,” said Taylor, “and as a master’s degree student, it has afforded me useful connections across the field which will continue to be valuable as I will be remaining in the Blacksburg area as a machine learning engineer after graduation.”