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Please use this identifier to cite or link to this item: http://hdl.handle.net/10791/271

Title: The objective ear: a tool for assessing music education progress
Authors: Burrows, Joel
Supervisor(s): Kumar, Vivekanandan (Faculty of Science, School of Computing and Information Science) and Dewan, Ali (Faculty of Science, School of Computing and Information Science)
Examining Committee: Kinshuk (University of North Texas)
Vallee, Mickey (Athabasca University)
Degree: Master of Science, Information Systems (MScIS)
Department: Faculty of Science and Technology
Keywords: Learning Analytics
Music Education
Issue Date: 28-Sep-2018
Abstract: The objective ear is an application that, given a pair of performances of a piece of music, judges the amount of progress made between the two performances. The application has two components: an evaluator and a classifier. The evaluator component analyzes each performance to generate a vector of metrics. These vectors are subtracted from each other to give a vector of differences. The difference vector is used as input to a decision tree, a machine learning classifier, which assigns a level of progress to the pair of performances. Testing of the classifier shows that the application provides accurate assessments and could be used in music education environments to aid students in assessing their progress, and to provide useful data on how music students progress.
Graduation Date:  6
URI: http://hdl.handle.net/10791/271
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