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Brennan Bean – Journal on Empowering Teaching Excellence, 2023
Modern technology threatens traditional modes of classroom assessment by providing students with automated ways to write essays and take exams. At the same time, modern technology continues to expand the accessibility of computational tools that promise to increase the potential scope and quality of class projects. This paper presents a case study…
Descriptors: Introductory Courses, Data Science, Student Projects, Programming
Noll, Jennifer; Tackett, Maria – Teaching Statistics: An International Journal for Teachers, 2023
As the field of data science evolves with advancing technology and methods for working with data, so do the opportunities for re-conceptualizing how we teach undergraduate statistics and data science courses for majors and non-majors alike. In this paper, we focus on three crucial components for this re-conceptualization: Developing research…
Descriptors: Undergraduate Students, Statistics Education, Data Science, Teaching Methods
Mike, Koby; Hazzan, Orit – IEEE Transactions on Education, 2023
Contribution: This article presents evidence that electrical engineering, computer science, and data science students, participating in introduction to machine learning (ML) courses, fail to interpret the performance of ML algorithms correctly, since they fail to consider the application domain. This phenomenon is referred to as the domain neglect…
Descriptors: Engineering Education, Computer Science Education, Data Science, Introductory Courses
Jose L. Salas; Xinran Wang; Mary C. Tucker; Ji Y. Son – Online Learning, 2024
Students believe mathematics is best learned by memorization; however, endorsing memorization as a study strategy is associated with a decrease in learning (Schoenfeld, 1989). When the world changed with the onset of the COVID-19 global pandemic, instruction transitioned to fully remote instruction where many assignments and examinations became…
Descriptors: Distance Education, Memorization, Pandemics, COVID-19