Discovering the misconceptions that influence learning of Machine Learning

Bachelor thesis (2022)

Authors

I.C. Angelescu Electrical Engineering, Mathematics and Computer Science

Contributors

M.A. Migut Computer Science & Engineering-Teaching Team - EEMCS (supervisor 1)
M.M. Specht Web Information Systems - EEMCS (supervisor 1)
Burcu Kulahcioglu Ozkan Software Engineering - EEMCS (supervisor 2)
Faculty
Electrical Engineering, Mathematics and Computer Science
Copyright: © 2022 Iulia Angelescu
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Published Date

22-06-2022

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

The purpose of the study is to investigate and evaluate the most common misunderstandings that are associated with the subject of Machine Learning, and then to make a direct comparison between the findings of the study and the Machine Learning course that is currently being provided by the Delft University of Technology as part of their Bachelor's degree program. In order to do this, the study uses literature analysis, together with interviews conducted with teachers and students of the course in question. The paper analyses the origin of the misconceptions and proposes different methods that can be used in order to eradicate the found misconceptions and, at the same time, methods that could help teachers discover new misconceptions.