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Peng Chen; Dong Yang; Jia Zhao; Shu Yang; Jari Lavonen – Journal of Computer Assisted Learning, 2025
Background: Computational thinking (CT) refers to the ability to represent problems, design solutions and migrate solutions computationally. While previous studies have shown that self-explanation can enhance students' learning, few empirical studies have examined the effects of using different self-explanation prompts to cultivate students' CT…
Descriptors: Computation, Thinking Skills, Programming, Learning Processes
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Umar Alkafaween; Ibrahim Albluwi; Paul Denny – Journal of Computer Assisted Learning, 2025
Background: Automatically graded programming assignments provide instant feedback to students and significantly reduce manual grading time for instructors. However, creating comprehensive suites of test cases for programming problems within automatic graders can be time-consuming and complex. The effort needed to define test suites may deter some…
Descriptors: Automation, Grading, Introductory Courses, Programming
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Charlotte Pierce; Clinton J. Woodward; Andrew Trevillian; Q. Tien Pham – ACM Transactions on Computing Education, 2025
Capstone courses, where students work on a large group project at the end of their degree, are common in computing. Many accreditation and industry bodies explicitly require or recommend them. Over the past two decades, capstone courses specifically focused on game development have become increasingly popular. Game development offers students the…
Descriptors: Foreign Countries, Computer Science Education, Programming, Design
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Ethan C. Campbell; Katy M. Christensen; Mikelle Nuwer; Amrita Ahuja; Owen Boram; Junzhe Liu; Reese Miller; Isabelle Osuna; Stephen C. Riser – Journal of Geoscience Education, 2025
Scientific programming has become increasingly essential for manipulating, visualizing, and interpreting the large volumes of data acquired in earth science research. Yet few discipline-specific instructional approaches have been documented and assessed for their effectiveness in equipping geoscience undergraduate students with coding skills. Here…
Descriptors: Earth Science, Undergraduate Students, Programming Languages, Computer Software
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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
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Zhizezhang Gao; Haochen Yan; Jiaqi Liu; Xiao Zhang; Yuxiang Lin; Yingzhi Zhang; Xia Sun; Jun Feng – International Journal of STEM Education, 2025
Background: With the increasing interdisciplinarity between computer science (CS) and other fields, a growing number of non-CS students are embracing programming. However, there is a gap in research concerning differences in programming learning between CS and non-CS students. Previous studies predominantly relied on outcome-based assessments,…
Descriptors: Computer Science Education, Mathematics Education, Novices, Programming
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Shih-Yu Li; Chun-Yu Ho; Shih-Ping Wu – Education and Information Technologies, 2025
This study originates from the observation during teaching and student interactions that students in industry-academic cooperative programs have very limited time to dedicate to coursework. The target group for this research consists of third-year students in the Mechanical Engineering industry-academia collaborative training program, and sessions…
Descriptors: Computer Science Education, Teaching Methods, Programming Languages, Teacher Student Relationship
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Yabing Jiang; Kazuo Nakatani – Journal of Information Systems Education, 2025
This research answers the call for Information Systems (IS) faculty to actively embrace rapidly advancing AI tools in teaching. We experimented with redesigning learning activities in two courses, requiring students to use GenAI, to aid student learning and teach responsible use of GenAI. The results show that students in the experimental group…
Descriptors: Teaching Methods, Technology Integration, Artificial Intelligence, Higher Education