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Tongxi Liu – Journal of Educational Computing Research, 2024
Addressing cognitive disparities has become a paramount concern in computational thinking (CT) education. The intricate and nuanced relationships between CT and cognitive variations emphasize the needs to accommodate diverse cognitive profiles when fostering CT skills, recognizing that these cognitive functions can manifest as either strengths or…
Descriptors: Executive Function, Computation, Thinking Skills, Data Science
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)
Jo Boaler; Kira Conte; Ken Cor; Jack A. Dieckmann; Tanya LaMar; Jesse Ramirez; Megan Selbach-Allen – Journal of Statistics and Data Science Education, 2025
This article reports on a multi-method study of a high school course in data science, finding that students who take data science take more mathematics courses than those who do not, there are more under-represented students in data science than is typical for other advanced mathematics courses; that the students who take data science are more…
Descriptors: Mathematics Instruction, Opportunities, High School Students, Data Science
Editorial Projects in Education, 2024
Problem-based learning ignites hands-on exploration, ignites curiosity, and sparks lifelong problem-solvers. This Spotlight will help readers learn how virtual reality can be used for unique problem-solving and engagement; explore how students are publishing their research in peer-reviewed journals; uncover how after-school programs are helping…
Descriptors: Problem Based Learning, Computer Simulation, Problem Solving, Participative Decision Making
Ian Thacker; Rebecca Schroeder; Sara Shields-Menard; Nickolas Goforth – International Journal of Science and Mathematics Education, 2025
To create opportunities for meaningful applications of data science for diverse students, we developed and implemented an online learning module focused on engaging students at a Hispanic Serving Institution (HSI) in an analysis of authentic soil data. Development of the module occurred over three design iterations involving interviews with 10…
Descriptors: Hispanic American Students, Minority Serving Institutions, Data Science, Undergraduate Students
Marianthi Grizioti; Chronis Kynigos – Informatics in Education, 2024
Even though working with data is as important as coding for understanding and dealing with complex problems across multiple fields, it has received very little attention in the context of Computational Thinking. This paper discusses an approach for bridging the gap between Computational Thinking with Data Science by employing and studying…
Descriptors: Computation, Thinking Skills, Data Science, Classification
Okhee Lee; Scott Grapin – Journal of Research in Science Teaching, 2025
We propose a conceptual framework for STEM education that is centered around justice for minoritized groups. Justice-centered STEM education engages all students in multiple STEM subjects, including data science and computer science, to explain and design solutions to societal challenges disproportionately impacting minoritized groups. We…
Descriptors: Social Justice, STEM Education, Bilingual Students, Multilingualism
Shesen Guo; Ganzhou Zhang – Education and Information Technologies, 2024
This study looked at titles of research papers on educational technology that were published between 1927 and 2023 using computational text analysis. To map research trends, metrics for technology terminology use, network complexity, and knowledge updating rates were used. The findings showed that, despite some fluctuations, titles have become…
Descriptors: Educational Research, Educational Technology, Journal Articles, Content Analysis
Ibrahim Oluwajoba Adisa; Danielle Herro; Oluwadara Abimbade; Golnaz Arastoopour Irgens – Information and Learning Sciences, 2024
Purpose: This study is part of a participatory design research project and aims to develop and study pedagogical frameworks and tools for integrating computational thinking (CT) concepts and data science practices into elementary school classrooms. Design/methodology/approach: This paper describes a pedagogical approach that uses a data science…
Descriptors: Learner Engagement, Elementary School Students, Data Science, Computation