Print Email Facebook Twitter Visualizing Complexity: Kernel Density Estimation in University Education Title Visualizing Complexity: Kernel Density Estimation in University Education: Investigating Misconceptions, Challenges, and the Role of Prior Knowledge in Comprehending KDE Author Popica, Tudor (TU Delft Electrical Engineering, Mathematics and Computer Science) Contributor Migut, M.A. (mentor) Lofi, C. (graduation committee) Degree granting institution Delft University of Technology Programme Computer Science and Engineering Project CSE3000 Research Project Date 2023-06-27 Abstract This research investigates the improvement of Kernel Density Estimation (KDE) comprehension in a university context via visualization-enhanced teaching. The study tackles KDE misconceptions, the efficacy of visual aids, and the role of previous mathematical and machine learning knowledge. Using a mix of literature review, survey, and experimental study, findings show that visualization techniques notably enhance KDE understanding and application, validating our hypothesis. This work underlines the importance of evidence-based teaching in machine learning education. Subject Kernel Density EstimationKDEteaching strategiesvisualization techniquesmisconceptionsuniversity educationmachine learningnon-parametric methodcomputer science educationeducational techniques To reference this document use: http://resolver.tudelft.nl/uuid:54ff3f18-f00f-4772-a691-5f5578ce3483 Part of collection Student theses Document type bachelor thesis Rights © 2023 Tudor Popica Files PDF Tudor_Popica_Final_Paper.pdf 435.62 KB Close viewer /islandora/object/uuid:54ff3f18-f00f-4772-a691-5f5578ce3483/datastream/OBJ/view