Publication Date
| In 2026 | 0 |
| Since 2025 | 18 |
Descriptor
Source
Author
| A. M. Phan | 1 |
| Ailing Qiao | 1 |
| Alper Bayazit | 1 |
| Anna Y. Q. Huang | 1 |
| Arwa Ahmed Qasem | 1 |
| Aykut Durak | 1 |
| C. L. Sandoval | 1 |
| C. Pilegard | 1 |
| C. Schurgers | 1 |
| Cheng-Yan Lin | 1 |
| Chenglu Li | 1 |
| More ▼ | |
Publication Type
| Reports - Research | 18 |
| Journal Articles | 17 |
| Tests/Questionnaires | 3 |
Education Level
| Higher Education | 6 |
| Postsecondary Education | 6 |
| Secondary Education | 5 |
| High Schools | 3 |
| Junior High Schools | 1 |
| Middle Schools | 1 |
Audience
Location
| China | 1 |
| Turkey (Istanbul) | 1 |
| Yemen | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
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
Anna Y. Q. Huang; Cheng-Yan Lin; Sheng-Yi Su; Stephen J. H. Yang – British Journal of Educational Technology, 2025
Programming education often imposes a high cognitive burden on novice programmers, requiring them to master syntax, logic, and problem-solving while simultaneously managing debugging tasks. Prior knowledge is a critical factor influencing programming learning performance. A lack of foundational knowledge limits students' self-regulated learning…
Descriptors: Artificial Intelligence, Technology Uses in Education, Coding, Programming
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
Rajagopal Sankaranarayanan; Mohan Yang; Kyungbin Kwon – Journal of Computing in Higher Education, 2025
The purpose of this study is to explore the influence of the microlearning instructional approach in an online introductory database programming classroom. The ultimate goal of this study is to inform educators and instructional designers on the design and development of microlearning content that maximizes student learning. Grounded within the…
Descriptors: Teaching Methods, Introductory Courses, Databases, Programming
Zifeng Liu; Wanli Xing; Xinyue Jiao; Chenglu Li; Wangda Zhu – Education and Information Technologies, 2025
The ability of large language models (LLMs) to generate code has raised concerns in computer science education, as students may use tools like ChatGPT for programming assignments. While much research has focused on higher education, especially for languages like Java and Python, little attention has been given to K-12 settings, particularly for…
Descriptors: High School Students, Coding, Artificial Intelligence, Electronic Learning
Erkan Er; Gökhan Akçapinar; Alper Bayazit; Omid Noroozi; Seyyed Kazem Banihashem – British Journal of Educational Technology, 2025
Despite the growing research interest in the use of large language models for feedback provision, it still remains unknown how students perceive and use AI-generated feedback compared to instructor feedback in authentic settings. To address this gap, this study compared instructor and AI-generated feedback in a Java programming course through an…
Descriptors: Student Evaluation, Student Attitudes, Feedback (Response), Artificial Intelligence
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
Manuel T. Rein; Jeroen K. Vermunt; Kim De Roover; Leonie V. D. E. Vogelsmeier – Structural Equation Modeling: A Multidisciplinary Journal, 2025
Researchers often study dynamic processes of latent variables in everyday life, such as the interplay of positive and negative affect over time. An intuitive approach is to first estimate the measurement model of the latent variables, then compute factor scores, and finally use these factor scores as observed scores in vector autoregressive…
Descriptors: Measurement Techniques, Factor Analysis, Scores, Validity
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
Aykut Durak; Vahide Bulut – Technology, Knowledge and Learning, 2025
The study uses the partial least squares-structural equation modeling (PLS-SEM) algorithm to predict the factors affecting the programming performance (PPE) (low, high) of the students receiving computer programming education. The participants of the study consist of 763 students who received programming education. In the analysis of the data, the…
Descriptors: Prediction, Low Achievement, High Achievement, Academic Achievement
Pere J. Ferrando; David Navarro-González; Fabia Morales-Vives – Educational and Psychological Measurement, 2025
The problem of local item dependencies (LIDs) is very common in personality and attitude measures, particularly in those that measure narrow-bandwidth dimensions. At the structural level, these dependencies can be modeled by using extended factor analytic (FA) solutions that include correlated residuals. However, the effects that LIDs have on the…
Descriptors: Scores, Accuracy, Evaluation Methods, Factor Analysis
Sohail Ahmed Soomro; Vijayakumar Nanjappan; Hernan Casakin; Georgi V. Georgiev – International Journal of Technology and Design Education, 2025
This paper explores the impact of a digital fabrication course on the development of digital fabrication skills and creativity. The course focused on open-ended prototyping and aimed to investigate its effects on students' motivation, enjoyment, and confidence. Students' creativity levels were measured using a creativity test at the beginning and…
Descriptors: Computer Peripherals, Construction (Process), Design, Skill Development
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)
Previous Page | Next Page »
Pages: 1 | 2
Peer reviewed
Direct link
