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Atiq, Zahra; Loui, Michael C. – ACM Transactions on Computing Education, 2022
In introductory computer programming courses, students experience a range of emotions. Students often experience anxiety and frustration when they encounter difficulties in writing programs. Continued frustration can discourage students from pursuing engineering and computing careers. Although prior research has shown how emotions affect students'…
Descriptors: Psychological Patterns, College Freshmen, Engineering Education, Programming
Hu, Yue; Su, Chien-Yuan; Fu, Anna – Education and Information Technologies, 2022
In recent years, increased attention has been given to programming instruction for primary and secondary students. Several game-based programming learning platforms, such as Code.org, Lightbot, and Run Marco, have been created to offer enticing, enjoyable, and visualizable programming learning conditions that facilitate student interest and…
Descriptors: Game Based Learning, Programming, Computer Science Education, Student Attitudes
Mary Conyers Tucker – ProQuest LLC, 2022
Learning to program is increasingly important. Yet, it is becoming clear that most students struggle when learning to program (McCracken et al., 2001). This is leading to a divide where some people can program but many others can't. Prior research has traced poor student outcomes to their early experiences learning programming. Still, little is…
Descriptors: Teaching Methods, Programming, Computer Science Education, Student Motivation
Vandenberg, Jessica; Tsan, Jennifer; Boulden, Danielle; Zakaria, Zarifa; Lynch, Collin; Boyer, Kristy Elizabeth; Wiebe, Eric – ACM Transactions on Computing Education, 2020
The language and concepts used by curriculum designers are not always interpreted by children as designers intended. This can be problematic when researchers use self-reported survey instruments in concert with curricula, which often rely on the implicit belief that students' understanding aligns with their own. We report on our refinement of a…
Descriptors: Elementary School Students, Knowledge Level, Computer Science, Student Attitudes
Gökoglu, Seyfullah; Kilic, Servet – E-Learning and Digital Media, 2023
This study investigates pre-service computer science (CS) teachers' perspectives on the factors affecting their programming abilities, concerns about their future professional lives, and pedagogical suggestions for effective programming teaching. The participants of the study were twenty-eight pre-service CS teachers studying at eighteen different…
Descriptors: Programming, Computer Science Education, Preservice Teachers, Teaching Methods
Amoudi, Ghada; Tbaishat, Dina – Education and Information Technologies, 2023
Social network analysis involves delicate and sophisticated mathematical concepts which are abstract and challenging to acquire by traditional methods. Many studies show that female students perform poorly in computer science-related courses compared to male students. To address these issues, this research investigates the impact of employing a…
Descriptors: Computer Science, Graduate Students, Outcomes of Education, Educational Technology
Ying-Chieh Liu; Hung-Yi Chen – IEEE Transactions on Education, 2025
Contribution: Expand the scope of factors influencing self-efficacy and highlight the importance of teaching quality, peer support, perceived course value, the moderating effects of self-regulation, and adversity quotient (AQ). Background: Self-efficacy has been regarded as an important factor in students' learning performance. However, little…
Descriptors: Foreign Countries, College Students, College Faculty, Programming
Haoming Wang; Chengliang Wang; Zhan Chen; Fa Liu; Chunjia Bao; Xianlong Xu – Education and Information Technologies, 2025
With the rapid development of artificial intelligence technology in the field of education, AI-Agents have shown tremendous potential in collaborative learning. However, traditional Computer-Supported Collaborative Learning (CSCL) methods still have limitations in addressing the unique demands of programming education. This study proposes an…
Descriptors: Artificial Intelligence, Cooperative Learning, Programming, Computer Science Education
Peña, Joslenne; Hanrahan, Benjamin V.; Rosson, Mary Beth; Cole, Carmen – ACM Transactions on Computing Education, 2021
Many initiatives have focused on attracting girls and young women (K-12 or college) to computer science education. However, professional women who never learned to program have been largely ignored, despite the fact that such individuals may have many opportunities to benefit from enhanced skills and attitudes about computer programming. To…
Descriptors: Computer Science Education, Professional Education, Females, Programming
Bowman, Nicholas A.; Jarratt, Lindsay; Culver, K. C.; Segre, Alberto M. – ACM Transactions on Computing Education, 2021
Active and collaborative learning has shown considerable promise for improving student outcomes and reducing group disparities. As one common form of collaborative learning, pair programming is an adapted work practice implemented widely in higher education computing programs. In the classroom setting, it typically involves two computer science…
Descriptors: Programming, Cooperative Learning, Student Attitudes, Academic Achievement
Charito G. Ong; Josan C. Fermano; Albert Christopher P. Daniot II – International Association for Development of the Information Society, 2022
This study reports an impact assessment of the basic Arduino programming training conducted among select Junior High School Students in a National High School in Cagayan De Oro City. The Focus Group Discussion sessions and survey questionnaires via goggle form complemented the content of the impact study table. The researchers aimed to determine…
Descriptors: Computer Software, Programming, Computer Science Education, Junior High School Students
Gang Zhao; Lijun Yang; Biling Hu; Jing Wang – Journal of Educational Computing Research, 2025
Human-computer collaboration is an effective way to learn programming courses. However, most existing human-computer collaborative programming learning is supported by traditional computers with a relatively low level of personalized interaction, which greatly limits the efficiency of students' efficiency of programming learning and development of…
Descriptors: Artificial Intelligence, Man Machine Systems, Programming, Learning Strategies
Liu, Jun; Li, Qingyue; Sun, Xue; Zhu, Ziqi; Xu, Yanhua – Asia Pacific Journal of Education, 2023
Programming self-efficacy plays an important role in promoting interest in programming education among teenagers. Therefore, the purpose of this study was to examine to what extent family socioeconomic status, programming learning, programming teaching, and gender influence programming self-efficacy. A total of 851 upper-secondary-school students…
Descriptors: Programming, Computer Science Education, Self Efficacy, Foreign Countries
Kuo, Yu-Chen; Chang, Yen-Cheng – Education and Information Technologies, 2023
In recent years, flipped classroom has become a popular teaching method. Compared with the traditional teaching method, the flipped classroom gives learners and teachers more opportunities to discuss. However, the flipped classroom has also encountered some difficulties. If we do not consider the different learning conditions of each learner when…
Descriptors: Flipped Classroom, Barriers, Multimedia Instruction, Educational Technology
David Roldan-Alvarez; Francisco J. Mesa – IEEE Transactions on Education, 2024
Artificial intelligence (AI) in programming teaching is something that still has to be explored, since in this area assessment tools that allow grading the students work are the most common ones, but there are not many tools aimed toward providing feedback to the students in the process of creating their program. In this work a small sized…
Descriptors: Intelligent Tutoring Systems, Grading, Artificial Intelligence, Feedback (Response)

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