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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
Remsh Nasser Alqahtani; Ahmad Zaid Almassaad – Education and Information Technologies, 2025
The aim of research is to reveal the effect of a training program based on the TAWOCK model for teaching computational thinking skills on teaching self-efficacy among computer teachers. It used the quasi-experimental approach, with a pre-test and post-test design with a control group. An electronic training program based on the TAWOCK model was…
Descriptors: Models, Teaching Methods, Computation, Thinking Skills
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
Ioannis Vourletsis – Educational Technology Research and Development, 2025
Computational thinking (CT) skills have become increasingly important in modern education, as they equip students with critical problem-solving skills applicable across various domains. Given the growing emphasis on digital literacy, it is essential to investigate grade- and gender-level differences in CT skills among students to support targeted…
Descriptors: Gender Differences, Instructional Program Divisions, Elementary School Students, Scores
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
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
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
Michelle Hodara; Ming Yin – Education Northwest, 2025
Computational thinking encompasses proficiencies in computer science and general problem-solving and can support students' learning across subject areas and success in science, technology, engineering, and mathematics (STEM) education and career pathways. To support students' STEM outcomes, many school districts are offering computer science…
Descriptors: Computation, Thinking Skills, Outcomes of Education, STEM Education
Arwa Ahmed Qasem – Discover Education, 2025
Contemporary education calls for innovative strategies to move away from traditional teacher-centered methods to methods that engage students and enhance learning outcomes. This shift toward student-centered learning is crucial for achieving educational goals and making the next generation more adaptable to the modern era. This paper examines the…
Descriptors: Active Learning, Student Projects, Program Effectiveness, Programming Languages
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
Brian R. Belland; Anna Y. Zhang; Eunseo Lee; Emre Dinç; ChanMin Kim – Journal of Computing in Higher Education, 2025
Computer science can be included in Early Childhood Education (ECE) through the use of block-based coding and robots. But this requires adequate preparation of ECE teachers to work with coding and robots, and integrate such into high quality lesson plans. In this paper, we investigate predictors of lesson plan quality among preservice, early…
Descriptors: Robotics, Educational Quality, Lesson Plans, Early Childhood Education
M. V. Lubarda; A. M. Phan; C. Schurgers; N. Delson; M. Ghazinejad; S. Baghdadchi; M. Minnes; M. Kim; C. Pilegard; J. Relaford-Doyle; C. L. Sandoval; H. Qi – Computer Science Education, 2025
Background and context: Pair programming and oral exams were deployed in tandem in a remote undergraduate computer programming course to promote social interaction and enhance learning. Objectives: We investigate their impact on social interactions, sense of connection, academic performance, and academic integrity within a virtual learning…
Descriptors: Distance Education, Undergraduate Students, Integrity, Computer Science Education
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

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