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Lee, Hyejeong; Closser, Florentina; Alghamdi, Khadijah; Ottenbreit-Leftwich, Anne; Brown, Matthew; Koressel, Jacob – TechTrends: Linking Research and Practice to Improve Learning, 2023
This study aims to examine the current experiences of high school students in computer science (CS) courses and the factors that motivated them to continue their future enrollment. The participants were 603 high school students in grades 9 through 12 in Indiana, all of whom enrolled in at least one CS course during the 2020-2021 academic year.…
Descriptors: Student Experience, Predictor Variables, Enrollment, Computer Science Education
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Jennifer M. Blaney; David F. Feldon; Annie M. Wofford; Kaylee Litson – Research in Higher Education, 2025
Community college transfer students represent a diverse and talented group to recruit to PhD and other graduate programs. Yet, little is known about practical strategies to support community college transfer students' access to graduate training. Focusing specifically on transfer students in computer science and guided by social cognitive career…
Descriptors: College Transfer Students, Community College Students, Graduate Study, Access to Education
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Melissa T. A. Simarmata; Gwo-Guang Lee; Hoky Ajicahyadi; Kung-Jeng Wang – Education and Information Technologies, 2024
Teaching computer programming language remotely presents particular difficulties due to its requirement for abstract and logical thinking. There is a dearth of research specifically examining the potential factors that determine student performance when distance self-learning is conducted for programming language education. This study aims to…
Descriptors: Distance Education, Independent Study, Computer Science Education, Programming
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Metin, Sermin; Basaran, Mehmet; Kalyenci, Damla – Pedagogical Research, 2023
The purpose of this research is to examine the coding skills of five-year-old children in terms of some variables. The research sample comprises 160 children aged five years studying in kindergarten affiliated with the Ministry of National Education in Gaziantep city center in the 2021-2022 academic year. As a data collection tool in the research,…
Descriptors: Programming, Kindergarten, Preschool Children, Foreign Countries
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Abraham E. Flanigan; Markeya S. Peteranetz; Duane F. Shell; Leen-Kiat Soh – ACM Transactions on Computing Education, 2023
Objectives: Although prior research has uncovered shifts in computer science (CS) students' implicit beliefs about the nature of their intelligence across time, little research has investigated the factors contributing to these changes. To address this gap, two studies were conducted in which the relationship between ineffective self-regulation of…
Descriptors: Computer Science Education, Self Concept, Intelligence, Self Management
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Ella Christiaans; So Yeon Lee; Kristy A. Robinson – Educational Psychology, 2024
Students want to learn computer science due to its usefulness for future careers, however they often meet challenges in introductory courses. In the increasingly digital world, it is important to understand some important psychological consequences of such challenges: perceived costs of pursuing computer science. This study thus investigated…
Descriptors: Undergraduate Students, Computer Science Education, Psychological Patterns, Student Attitudes
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Obeng, Asare Yaw – Cogent Education, 2023
The learning processes have been significantly impacted by technology. Numerous learners have adopted technology-based learning systems as the preferred form of learning. It is then necessary to identify the learning styles of learners to deliver appropriate resources, engage them, increase their motivation, and enhance their satisfaction and…
Descriptors: Predictor Variables, Cognitive Style, Electronic Learning, College Freshmen
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Ali Alshammari – Education and Information Technologies, 2024
In online education, it is widely recognized that interaction and engagement have an impact on students' academic performance. While previous research has extensively explored interactions between students, instructors, and content, there has been limited exploration of course design elements that promote the fourth type of interaction:…
Descriptors: Learning Analytics, Learning Management Systems, Academic Achievement, Correlation
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Jiali Zheng; Melissa Duffy; Ge Zhu – Discover Education, 2024
Students in technology majors such as Computer Science and Information Technology need to take a series of computer programming courses to graduate. Yet, not all students will persist in taking programming courses as required, and little is known about the factors influencing their enrollment intentions. Research is needed to better understand…
Descriptors: Computer Science Education, Programming, Predictor Variables, Enrollment
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Shah, Zohal; Chen, Chen; Sonnert, Gerhard; Sadler, Philip M. – AERA Online Paper Repository, 2023
Computer gameplay and social media are the two most common forms of entertainment in the digital age. Many scholars share the assumption that leisure-time digital consumption is associated with CS affinity, but there is a dearth of research evidence for this relationship. Female students generally spend less time on gaming and more time on social…
Descriptors: Computer Science, Vocational Interests, Computer Use, Gender Differences
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Lihui Sun; Danhua Zhou – Journal of Computer Assisted Learning, 2024
Background: Integrating programming in K-12 curriculum has become a global consensus. Teachers are central figures in programming instruction. But the majority of current research focuses on teachers' external teaching behaviours and less on teachers' attitudes towards programming. Objectives: The purpose of this study is to validate the K-12…
Descriptors: Foreign Countries, Elementary School Teachers, Secondary School Teachers, Teacher Attitudes
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Niklas Humble; Jonas Boustedt; Hanna Holmgren; Goran Milutinovic; Stefan Seipel; Ann-Sofie Östberg – Electronic Journal of e-Learning, 2024
Artificial Intelligence (AI) and related technologies have a long history of being used in education for motivating learners and enhancing learning. However, there have also been critiques for a too uncritical and naïve implementation of AI in education (AIED) and the potential misuse of the technology. With the release of the virtual assistant…
Descriptors: Cheating, Artificial Intelligence, Technology Uses in Education, Computer Science Education
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George, Kari L.; Sax, Linda J.; Wofford, Annie M.; Sundar, Sarayu – Research in Higher Education, 2022
Computing career opportunities are increasing across all sectors of the U.S. economy, yet there remains a serious shortage of college graduates to fill these jobs. This problem has fueled a nationwide effort to expand and diversify the computing career pipeline. Guided by social cognitive career theory (SCCT), this study used logistic regression…
Descriptors: College Environment, Career Choice, College Students, School Role
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Umar Bin Qushem; Solomon Sunday Oyelere; Gökhan Akçapinar; Rogers Kaliisa; Mikko-Jussi Laakso – Technology, Knowledge and Learning, 2024
Predicting academic performance for students majoring in computer science has long been a significant field of research in computing education. Previous studies described that accurate prediction of students' early-stage performance could identify low-performing students and take corrective action to improve performance. Besides, adopting machine…
Descriptors: Predictor Variables, Learning Analytics, At Risk Students, Computer Science
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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
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