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Ihrmark, Daniel; Tyrkkö, Jukka – Education for Information, 2023
The combination of the quantitative turn in linguistics and the emergence of text analytics has created a demand for new methodological skills among linguists and data scientists. This paper introduces KNIME as a low-code programming platform for linguists interested in learning text analytic methods, while highlighting the considerations…
Descriptors: Linguistics, Data Science, Programming, Data Analysis
Bende, Imre – Acta Didactica Napocensia, 2022
Understanding data structures is fundamental for mastering algorithms. In order to solve problems and tasks, students must be able to choose the most appropriate data structure in which the data is stored and that helps in the process of the solution. Of course, there is no single correct solution, but in many cases, it is an important step to…
Descriptors: Programming, Computer Science Education, Data, Visual Aids
Enze Chen; Mark Asta – Journal of Chemical Education, 2022
With the growing desire to incorporate data science and informatics into STEM curricula, there is an opportunity to integrate research-based software and tools (e.g., Python) within existing pedagogical methods to craft new, accessible learning experiences. We show how the open-source Jupyter Book software can achieve this goal by creating a…
Descriptors: Programming, Open Source Technology, STEM Education, Textbooks
Allison S. Theobold; Megan H. Wickstrom; Stacey A. Hancock – Journal of Statistics and Data Science Education, 2024
Despite the elevated importance of Data Science in Statistics, there exists limited research investigating how students learn the computing concepts and skills necessary for carrying out data science tasks. Computer Science educators have investigated how students debug their own code and how students reason through foreign code. While these…
Descriptors: Computer Science Education, Coding, Data Science, Statistics Education
Alderson, David L. – INFORMS Transactions on Education, 2022
This article describes the motivation and design for introductory coursework in computation aimed at midcareer professionals who desire to work in data science and analytics but who have little or no background in programming. In particular, we describe how we use modern interactive computing platforms to accelerate the learning of our students…
Descriptors: Curriculum Design, Introductory Courses, Computation, Data Science
Dogucu, Mine; Çetinkaya-Rundel, Mine – Journal of Statistics and Data Science Education, 2022
It is recommended that teacher-scholars of data science adopt reproducible workflows in their research as scholars and teach reproducible workflows to their students. In this article, we propose a third dimension to reproducibility practices and recommend that regardless of whether they teach reproducibility in their courses or not, data science…
Descriptors: Statistics Education, Data Science, Teaching Methods, Instructional Materials