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Heidi Taveter; Marina Lepp – Informatics in Education, 2025
Learning programming has become increasingly popular, with learners from diverse backgrounds and experiences requiring different support. Programming-process analysis helps to identify solver types and needs for assistance. The study examined students' behavior patterns in programming among beginners and non-beginners to identify solver types,…
Descriptors: Behavior Patterns, Novices, Expertise, Programming
Dan Sun; Fan Xu – Journal of Educational Computing Research, 2025
Real-time collaborative programming (RCP), which allows multiple programmers to work concurrently on the same codebase with changes instantly visible to all participants, has garnered considerable popularity in higher education. Despite this trend, little work has rigorously examined how undergraduates engage in collaborative programming when…
Descriptors: Cooperative Learning, Programming, Computer Science Education, Undergraduate Students
Irem Nur Çelik; Kati Bati – Informatics in Education, 2025
In this study, we aimed to investigate the impact of cooperative learning on the computational thinking skills and academic performances of middle school students in the computational problem-solving approach. We used the pretest-posttest control group design of the quasiexperimental method. In the research, computational problem-solving…
Descriptors: Cooperative Learning, Academic Achievement, Computation, Thinking Skills
Wenrui Huang; Dajanae Palmer; Ekaete Udoh; Yung Chun; Jason Jabbari – Annenberg Institute for School Reform at Brown University, 2025
The shortage of STEM workers, particularly in computer science, is compounded by the underrepresentation of women and certain minoritized racial/ethnic groups in these fields. Efforts to address worker shortages and broaden participation include improving traditional STEM education pathways and creating alternative pathways. While persistence has…
Descriptors: STEM Education, Programming, Internship Programs, Minority Group Students
Wen-shuang Fu; Jia-hua Zhang; Di Zhang; Tian-tian Li; Min Lan; Na-na Liu – Journal of Educational Computing Research, 2025
Cognitive ability is closely associated with the acquisition of programming skills, and enhancing learners' cognitive ability is a crucial factor in improving the efficacy of programming education. Adaptive feedback strategies can provide learners with personalized support based on their learning context, which helps to stimulate their interest…
Descriptors: Feedback (Response), Cognitive Ability, Programming, Computer Science Education
Experiencing Enjoyment in Visual Programming Tasks Promotes Self-Efficacy and Reduces the Gender Gap
Robbert Smit; Rahel Schmid; Nicolas Robin – British Journal of Educational Technology, 2025
Secondary school students (N = 269) participated in a daylong visual programming course held in a stimulating environment for start-up enterprises. The tasks were application-oriented and partly creative. For example, a wearable device with light-emitting diodes, (ie, LEDs) could be applied to a T-shirt and used for optical messages. Our research…
Descriptors: Self Efficacy, Gender Differences, Prediction, Student Attitudes
Xin Gong; Zhixia Li; Ailing Qiao – Education and Information Technologies, 2025
Feedback is crucial during programming problem solving, but context often lacks critical and difference. Generative artificial intelligence dialogic feedback (GenAIDF) has the potential to enhance learners' experience through dialogue, but its effectiveness remains sufficiently underexplored in empirical research. This study employed a rigorous…
Descriptors: Artificial Intelligence, Technology Uses in Education, Dialogs (Language), Feedback (Response)
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