Print Email Facebook Twitter A Guidline for Creating Assessments in Machine Learning Education Title A Guidline for Creating Assessments in Machine Learning Education Author Çakıcı, Kerem (TU Delft Electrical Engineering, Mathematics and Computer Science) Contributor Migut, M.A. (mentor) Specht, M.M. (mentor) Özkan, B. (graduation committee) Degree granting institution Delft University of Technology Programme Computer Science and Engineering Project CSE3000 Research Project Date 2022-06-22 Abstract Even though machine learning field is growing rapidly, research on education of machine learning is scarce. In this paper a research about creating assessments in the machine learning’s context is presented. The aim of the research is to answer how to design assessments that reliably show progress on a module in machine learning. Learning outcomes and Bloom’s taxonomy are used to make the research reproducible, and draw conclusions. One of the main conclusions drawn in this paper is that verbs that are used in learning outcomes can also be used to find the appropriate question type (e.g. open ended, multiple-choice) to assess that learning outcome. Additionally, this paper concludes there is no strict procedure of creating assessment questions. Therefore, a guideline is created by the researcher and presented in the paper. Lastly, four questions are created using this guideline and evaluated with interviews with three machine learning professors. Subject Machine LearningAssessmentLearning outcomesBloom's taxonomyEducation To reference this document use: http://resolver.tudelft.nl/uuid:26e3f1df-fb9d-4f68-a563-51e9a653c8b5 Part of collection Student theses Document type bachelor thesis Rights © 2022 Kerem Çakıcı Files PDF final_paper_kerem_cakici.pdf 633.52 KB Close viewer /islandora/object/uuid:26e3f1df-fb9d-4f68-a563-51e9a653c8b5/datastream/OBJ/view