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Christina Glasauer; Martin K. Yeh; Lois Anne DeLong; Yu Yan; Yanyan Zhuang – Computer Science Education, 2025
Background and Context: Feedback on one's progress is essential to new programming language learners, particularly in out-of-classroom settings. Though many study materials offer assessment mechanisms, most do not examine the accuracy of the feedback they deliver, nor give evidence on its validity. Objective: We investigate the potential use of a…
Descriptors: Novices, Computer Science Education, Programming, Accuracy
Timothy Kluthe; Hannah Stabler; Amelia McNamara; Andreas Stefik – Computer Science Education, 2025
Background and Context: Data science and statistics are used across a broad spectrum of professions, experience levels and programming languages. The popular scientific computing languages, such as Matlab, Python and R, were organized without using empirical methods to show evidence for or against their design choices, resulting in them feeling…
Descriptors: Programming Languages, Data Science, Statistical Analysis, Vocabulary
Molly Domino; Bob Edmison; Stephen H. Edwards; Rifat Sabbir Mansur; Alexandra Thompson; Clifford A. Shaffer – Computer Science Education, 2025
Background and Context: Self-regulated learning (SRL) skills are critical aspect of learning to program and are predictive of academic success. Early college students often struggle to use these skills, but can improve when given targeted instruction. However, it is not yet clear what skills are best to prioritize. Objective: We seek to create a…
Descriptors: Metacognition, Programming, Computer Science Education, College Students
W. Monty Jones; Katherine Hansen; Douglas Lusa Krug; Michael L. Schad; Nakisha Whittington; Xun Liu – Computer Science Education, 2025
Background and Context: Efforts to engage adult learners in computer science in the United States have been largely unsuccessful. While research examining the use of music for teaching computer programming with K-12 learners is emerging, little research with adult learners exists. Objective: This study evaluates the effect of computer coding…
Descriptors: Musical Composition, Computer Software, Adult Students, Student Attitudes
Tianxiao Yang; Jongpil Cheon – Computer Science Education, 2025
Background and context: There were few studies indicating if students' computational thinking (CT) self-efficacy and their CT performance were aligned with each other. Objectives: The study was to investigate if there was a discrepancy between students' CT self-efficacy and their CT performance. Method: Involving 104 non-CS undergraduate students…
Descriptors: Self Efficacy, Computer Science Education, Prediction, Teacher Expectations of Students
Dandan Yang; Zhanxia Yang; Marina Umaschi Bers – Computer Science Education, 2025
Background and context: Despite the growing importance of computer science (CS) education, high-quality CS curricula for students in kindergarten to lower elementary grades are lacking. It is also unclear how students from underrepresented groups such as female students, students from low socioeconomic status, and students with disability respond…
Descriptors: Computer Science Education, Early Childhood Education, Program Effectiveness, Programming
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
M. V. Lubarda; A. M. Phan; C. Schurgers; N. Delson; M. Ghazinejad; S. Baghdadchi; M. Minnes; M. Kim; C. Pilegard; J. Relaford-Doyle; C. L. Sandoval; H. Qi – Computer Science Education, 2025
Background and context: Pair programming and oral exams were deployed in tandem in a remote undergraduate computer programming course to promote social interaction and enhance learning. Objectives: We investigate their impact on social interactions, sense of connection, academic performance, and academic integrity within a virtual learning…
Descriptors: Distance Education, Undergraduate Students, Integrity, Computer Science Education

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