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David 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
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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
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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)
Nischal Shrestha – ProQuest LLC, 2022
Data science programming presents many challenges for programmers entering the field. Roughly, data science programming can be broken up into several activities: data wrangling, analysis, modeling, or visualization. Data wrangling is an important first step that involves cleaning and shaping tabular data--or dataframes--into a form amenable for…
Descriptors: Data Science, Programming, Learning Strategies, Programming Languages
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Odden, Tor Ole B.; Silvia, Devin W.; Malthe-Sørenssen, Anders – Journal of Research in Science Teaching, 2023
This article reports on a study investigating how computational essays can be used to help students in higher education STEM take up disciplinary epistemic agency--cognitive control and responsibility over one's own learning within the scientific disciplines. Computational essays are a genre of scientific writing that combine live, executable…
Descriptors: Computation, Essays, Undergraduate Students, STEM Education
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Fergusson, Anna; Pfannkuch, Maxine – Mathematical Thinking and Learning: An International Journal, 2022
The advent of data science has led to statistics education researchers re-thinking and expanding their ideas about tools for teaching statistical modeling, such as the use of code-driven tools at the secondary school level. Methods for statistical inference, such as the randomization test, are typically taught within secondary school classrooms…
Descriptors: Foreign Countries, Data Science, Statistics Education, Mathematical Models
P. Janelle McFeetors – Sage Research Methods Cases, 2016
This case study describes an experience of using constructivist grounded theory to analyze data. The project investigated how high school students improved their approaches to learning mathematics. Over 4 months, students participated in processes which supported their learning while simultaneously generating data, including interactive writing,…
Descriptors: High School Students, Mathematics Education, Data Analysis, Data Interpretation