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Effects of Block-Based Visual Programming on K-12 Students' Learning Outcomes
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Qing Yu; Kun Yu; Baomin Li – Journal of Educational Computing Research, 2025
Computer programming is regarded as an important skill for the future. However, many K-12 students face challenges and difficulties in learning traditional text-based programming. Block-based visual programming (BVP) can reduce the difficulty of learning programming and is seen as a potential programming education tool. Nevertheless, the effects…
Descriptors: Programming, Computer Science Education, Visual Aids, Outcomes of Education
Integrating Project-Based Learning with Self-Regulated Learning to Enhance Programming Learning Motivation
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Peidi Gu; Zui Cheng; Cheng Miaoting; John Poggio; Yan Dong – Journal of Computer Assisted Learning, 2025
Background: Today, the importance of STEM (Science, Technology, Engineering and Mathematics) education and training is widely recognised and accepted. Computer programming courses have become essential in higher education to nurture students' programming, analysis and computational skills, which are vital for success in all STEM fields and areas.…
Descriptors: Active Learning, Student Projects, Individualized Instruction, Student Motivation
Using Hackathons to Enhance University-Level Water Curriculum for Students in Minority Communities
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Wendy Haw; Adam Crawford – Journal of Learning Development in Higher Education, 2025
This article illustrates the potential for hackathons to serve as an innovative educational tool in addressing the underrepresentation of minority communities in science, technology, engineering, and mathematics (STEM) fields. Using Merced, California--a region recognised for its agricultural economy, socioeconomic disparities, and diverse…
Descriptors: Programming, Computer Science Education, Disproportionate Representation, STEM Education
The Project-Based Learning Model via Generative Artificial Intelligence to Promote Programming Skills for Vocational Students
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Sukan Saeliang; Pinanta Chatwattana – International Education Studies, 2025
The project-based learning model via generative artificial intelligence, or PjBL model via Gen-AI, is a research tool that was initiated based on the concept of project-based learning management focusing mainly on self-directed learning, in which learners are able to learn and practice through the projects they are interested in as to their…
Descriptors: Active Learning, Student Projects, Artificial Intelligence, Man Machine Systems
The Effectiveness of Project-Based Learning in Development of C# Programming Language Skills among Education Technology Students
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Arwa Ahmed Qasem – Discover Education, 2025
Contemporary education calls for innovative strategies to move away from traditional teacher-centered methods to methods that engage students and enhance learning outcomes. This shift toward student-centered learning is crucial for achieving educational goals and making the next generation more adaptable to the modern era. This paper examines the…
Descriptors: Active Learning, Student Projects, Program Effectiveness, Programming Languages
Getting Unstuck Together: Creating Personally Authentic Programming Projects in a 4th Grade Classroom
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Paulina Haduong; Karen Brennan – Computer Science Education, 2025
Background and Context: Learning to create self-directed and personally authentic programming projects involves encountering challenges and learning to get unstuck. Objective: This article investigates how one U.S. fourth-grade classroom engaged in practices which emphasized community supports, in the context of the classroom's implementation and…
Descriptors: Grade 4, Computer Science Education, Instructional Design, Programming
Fostering the Development of Earth Data Science Skills in a Diverse Community of Online Learners: A Case Study of the Earth Data Science Corps
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Nathan A. Quarderer; Leah Wasser; Anne U. Gold; Patricia Montaño; Lauren Herwehe; Katherine Halama; Emily Biggane; Jessica Logan; David Parr; Sylvia Brady; James Sanovia; Charles Jason Tinant; Elisha Yellow Thunder; Justina White Eyes; LaShell Poor Bear/Bagola; Madison Phelps; Trey Orion Phelps; Brett Alberts; Michela Johnson; Nathan Korinek; William Travis; Naomi Jacquez; Kaiea Rohlehr; Emily Ward; Elsa Culler; R. Chelsea Nagy; Jennifer Balch – Journal of Statistics and Data Science Education, 2025
Today's data-driven world requires earth and environmental scientists to have skills at the intersection of domain and data science. These skills are imperative to harness information contained in a growing volume of complex data to solve the world's most pressing environmental challenges. Despite the importance of these skills, Earth and…
Descriptors: Electronic Learning, Earth Science, Environmental Education, Science Education