Bridging the Knowledge Gap: Identifying Essential Machine Learning Concepts for Effective Progression in Follow-Up Courses

This research paper aims to investigate the adequacy of concepts taught during an introductory machine learning course in preparing students for subsequent courses and their professional careers. The study adopts a comprehensive approach, including a literature review, interviews with teaching staff of follow-up courses, and a survey...

Visualizing Complexity: Kernel Density Estimation in University Education: Investigating Misconceptions, Challenges, and the Role of Prior Knowledge in Comprehending KDE

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...

Measuring students’ progress in Machine Learning: A case study of Decision Trees and Random Forests

Machine Learning (ML) is a rapidly growing field, therefore ensuring that students deeply understand such concepts is of key importance in order to certify that they are prepared for the challenges and opportunities of the future workforce. Despite this, literature on teaching ML and assessing students' understanding with regard to this field is...

Discovering the misconceptions that influence learning of Machine Learning

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...

Competences in Machine Learning: The order of competences that students need to learn in ML

Machine learning is becoming more and more applied within business and academia alike. This has led researchers to look inwards and discuss whether the current way of teaching and learning machine learning is the right way. Within this train of thought, one must investigate the characteristics of teaching and learning. Namely, what are the...

Instructional Designs of Machine Learning: A research into the instructional designs used in introductory courses of machine learning in computer science bachelors

Instructional Design is a discipline and a science that has existed for decades. There has been research done into the most effective instructional designs for different study disciplines, the same cannot be said about machine learning. As ML is a relatively young discipline, no research has been done into instructional designs and teaching...

A Guidline for Creating Assessments in Machine Learning Education

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...

CITYSENT: Sentiment analysis of the Netherlands and Flanders

The department of Urbanism at the TU Delft, our clients, research the sentiment in different places, times, ages or genders and compare them to each other. This report describes the purpose, design, implementation and accuracy of a web tool created to get insights into the sentiment people have, de- ducted from social media. The aim of our...