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Direct linkDavid Shilane; Nicole Di Crecchio; Nicole L. Lorenzetti – Teaching Statistics: An International Journal for Teachers, 2024
Educational curricula in data analysis are increasingly fundamental to statistics, data science, and a wide range of disciplines. The educational literature comparing coding syntaxes for instruction in data analysis recommends utilizing a simple syntax for introductory coursework. However, there is limited prior work to assess the pedagogical…
Descriptors: Programming, Data Science, Programming Languages, Coding
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
Andrew A. Tawfik; Linda Payne; Andrew M. Olney – Technology, Knowledge and Learning, 2024
Theorists and educators increasingly highlight the importance of computational thinking in STEM education. While various scaffolding strategies describe how to best support this skillset (i.e., paired programming, worked examples), less research has focused on the design and development of these digital tools. One way to support computational…
Descriptors: Thinking Skills, Computation, STEM Education, Scaffolding (Teaching Technique)
