Applying Cluster Analysis to Student Responses from Energy Surveys for Identification of Commonalities in their Understanding
Author: Arianna Giguere
Graduation Year: 2020
Thesis Advisor: Michael Wittman & John Thompson
Description of Publication: Energy is a complicated model that has been developed to describe matter to matter interactions. Since energy can be challenging to define, there are inconsistencies among even teachers and physicists in how they define the concept. It is no wonder that students themselves carry misconceptions and confusions. While it may be difficult to teach, an understanding of energy from a young age is essential for the future of technology, climate change, and scientific discoveries. Middle school students in Maine are required to learn about energy transformation, conservation, and forms, and from 2011-2018, researchers at the University of Maine administered multiple surveys to record some level of student thought processes. This project uses the technique of cluster analysis to analyze the previously collected survey data. The resulting clusters of statistical significance are interpreted to obtain insight on common student understanding of energy. This information can benefit both teachers and students because improvements cannot be made until a problem is identified.
Location of Publication:
URL to Thesis: https://digitalcommons.library.umaine.edu/honors/593/