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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
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Gabriela de Carvalho Barros Bezerra; Wilk Oliveira; Ana Cláudia Guimarães Santos; Juho Hamari – ACM Transactions on Computing Education, 2024
Despite recent high interest among researchers and practitioners in learning programming, even the most dedicated learners can struggle to find motivation for studying and practicing programming. Therefore, in recent years, several strategies (e.g., educational games, flipped classrooms, and visual programming languages) have been employed to…
Descriptors: Gamification, Programming, Computer Science Education, Workshops
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Miaoting Cheng; Xiaoyan Lai; Da Tao; Juntong Lai; Jun Yang – Education and Information Technologies, 2024
While numerous studies have highlighted the potential benefits of programming environment (PE) use for children's learning, the boundary conditions of children's PE acceptance within the programming education context are less clear. This study fills this gap in the literature by investigating the critical determinants of children's PE use…
Descriptors: Programming, Intention, Competition, Computation
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
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Dennis Tay – Journal of Statistics and Data Science Education, 2024
Data analytics and programming skills are increasingly important in the humanities, especially in disciplines like linguistics due to the rapid growth of natural language processing (NLP) technologies. However, attitudes and perceptions of students as novice learners, and the attendant pedagogical implications, remain underexplored. This article…
Descriptors: Data Analysis, Programming, Linguistics, Graduate Students
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Wei-Ying Li; Tzu-Chuen Lu – Informatics in Education, 2024
This study investigates the effect of programming courses on the computational thinking (CT) skills of elementary school students and the learning effectiveness of students from different backgrounds who are studying programming. We designed a OwlSpace programming course into an elementary school curriculum. Students in fourth and fifth grades…
Descriptors: Programming, Computation, Thinking Skills, Elementary School Students
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Hugo G. Lapierre; Patrick Charland; Pierre-Majorique Léger – Computer Science Education, 2024
Background and Context: Current programming learning research often compares novices and experienced programmers, leaving early learning stages and emotional and cognitive states under-explored. Objective: Our study investigates relationships between cognitive and emotional states and learning performance in early stage programming learners with…
Descriptors: Programming, Computer Science Education, Psychological Patterns, Cognitive Processes
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Siu-Cheung Kong; Wei Shen – Interactive Learning Environments, 2024
Logistic regression models have traditionally been used to identify the factors contributing to students' conceptual understanding. With the advancement of the machine learning-based research approach, there are reports that some machine learning algorithms outperform logistic regression models in terms of prediction. In this study, we collected…
Descriptors: Student Characteristics, Predictor Variables, Comprehension, Computation
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Zi Xiang Poh; Ean Teng Khor – International Journal on E-Learning, 2024
Machine learning and data mining techniques have been widely used in educational settings to identify the important features that tend to influence students' learning performance and predict their future performance. However, there is little to no research done in the context of Singapore's education. Hence, this study aims to fill the gap by…
Descriptors: Learning Analytics, Goodness of Fit, Academic Achievement, Online Courses
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Chenglong Wang – Turkish Online Journal of Educational Technology - TOJET, 2024
The rapid development of education informatization has accumulated a large amount of data for learning analytics, and adopting educational data mining to find new patterns of data, develop new algorithms and models, and apply known predictive models to the teaching system to improve learning is the challenge and vision of the education field in…
Descriptors: Decision Making, Prediction, Models, Intervention
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Ramon Mayor Martins; Christiane Gresse Von Wangenheim – Informatics in Education, 2024
Information technology (IT) is transforming the world. Therefore, exposing students to computing at an early age is important. And, although computing is being introduced into schools, students from a low socio-economic status background still do not have such an opportunity. Furthermore, existing computing programs may need to be adjusted in…
Descriptors: Information Technology, Socioeconomic Status, Social Class, Computer Literacy
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Ramadan Abdunabi; Ilham Hbaci; Teddy Nyambe – Information Systems Education Journal, 2024
Programming is a major subject in various Information Systems (IS) programs, with students often finding it a challenging skill to acquire. While there is extensive literature on factors helping students learn to program, most of which focuses on non-IS students. Due to the increasing demand for professionals with programming skills, there is a…
Descriptors: Influences, Programming, Self Efficacy, Computer Science Education
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Anette Bentz; Bernhard Standl – ACM Transactions on Computing Education, 2024
Digital literacy is considered to be crucial for social and professional participation. Hence, several projects have been launched in school, as well as extracurricular activities to promote digital literacy in middle school. They aim, among other things, to increase interest in the so-called STEM subjects (science, technology, engineering, and…
Descriptors: Digital Literacy, Computer Science Education, Extracurricular Activities, Middle School Students