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Ting-Ting Wu; Hsin-Yu Lee; Pei-Hua Chen; Wei-Sheng Wang; Yueh-Min Huang – Journal of Computer Assisted Learning, 2025
Background: Conventional reflective learning methodologies in programming education often lack structured guidance and individualised feedback, limiting their pedagogical effectiveness. Whilst computational thinking (CT) offers a systematic problem-solving framework with decomposition, pattern recognition, abstraction, and algorithm design, its…
Descriptors: Computation, Thinking Skills, Educational Diagnosis, Diagnostic Tests
Sayginer, Senol; Tüzün, Hakan – Journal of Computer Assisted Learning, 2023
Background: Studies on the effectiveness of block-based environments continue to produce inconsistent results. A strong reason for this is that most studies compare environments that are not equivalent to each other or to the level of learners. Moreover, studies that present evidence of the effectiveness of block-based environments by comparing…
Descriptors: Programming, Academic Achievement, Logical Thinking, Thinking Skills
Kevin Sigayret; Nathalie Blanc; André Tricot – Journal of Computer Assisted Learning, 2025
Background: Teaching programming and computational thinking is becoming a major issue in many education systems. Numerous approaches are possible, but very few studies compare these different ways of implementing programming and computational thinking learning. Objectives: We compared three ways of teaching programming and computational thinking…
Descriptors: Educational Technology, Technology Uses in Education, Robotics, Computation
Sáez-López, José Manuel; González-Calero, José Antonio; Cózar-Gutierrez, Ramón; Olmo-Muñoz, Javier – Journal of Computer Assisted Learning, 2023
Background: The present study analyses the design of programming literacy in the sixth grade of Primary Education, starting from the use of simple activities with visual block-based programming, through "Scratch," and progressively linking difficulty to the use of the "Unity" engine, and the "C#" language, with simple…
Descriptors: Elementary Education, Programming, Grade 6, Programming Languages
Dan Sun; Fan Ouyang; Yan Li; Chengcong Zhu; Yang Zhou – Journal of Computer Assisted Learning, 2024
Background: With the development of computational literacy, there has been a surge in both research and practice application of text-based and block-based modalities within the field of computer programming education. Despite this trend, little work has actually examined how learners engaging in programming process when utilizing these two major…
Descriptors: Computer Science Education, Programming, Computer Literacy, Comparative Analysis
Sun, Lihui; Zhou, Danhua – Journal of Computer Assisted Learning, 2023
Background: As one of the mainstream forms of programming education, educational robotics (ER) have been a crucial way to develop K-12 students' programming ability. Objectives: The purpose of this study is to clarify the content of programming ability, to verify the effectiveness of ER as a teaching method to improve students' programming…
Descriptors: Elementary School Students, Secondary School Students, Robotics, Programming
Peng Chen; Dong Yang; Jia Zhao; Shu Yang; Jari Lavonen – Journal of Computer Assisted Learning, 2025
Background: Computational thinking (CT) refers to the ability to represent problems, design solutions and migrate solutions computationally. While previous studies have shown that self-explanation can enhance students' learning, few empirical studies have examined the effects of using different self-explanation prompts to cultivate students' CT…
Descriptors: Computation, Thinking Skills, Programming, Learning Processes
Shang Shanshan; Geng Sen – Journal of Computer Assisted Learning, 2024
Background: Artificial intelligence-generated content (AIGC) has stepped into the spotlight with the emergence of ChatGPT, making effective use of AIGC for education a hot topic. Objectives: This study seeks to explore the effectiveness of integrating AIGC into programming learning through debugging. First, the study presents three levels of AIGC…
Descriptors: Artificial Intelligence, Educational Technology, Technology Integration, Programming
Ankora, Carlos; Bolatimi, Stephen Oladagba; Bensah, Lily; Mahama, Francois; Kuadey, Noble Arden; Adu, Adolph Sedem Yaw; Adjei, Laurene – Journal of Computer Assisted Learning, 2023
Background: The degree to which Computer Science (CS) and Information Communication Technology (ICT) students are motivated to learn greatly impacts their study habits, academic achievement in school and ultimately their job prospects. In recent times, skills in programming languages have become vital in searching for employment. Objective: This…
Descriptors: College Students, Student Motivation, Course Selection (Students), Programming Languages
Xin Gong; Weiqi Xu; Ailing Qiao; Zhixia Li – Journal of Computer Assisted Learning, 2025
Background: Robot programming can simultaneously cultivate learners' computational thinking (CT) and spatial thinking (ST). However, there is a noticeable gap in research focusing on the micro-level development patterns of learners' CT and ST and their interconnections. Objectives: This study aims to uncover the intricate development patterns and…
Descriptors: Mental Computation, Thinking Skills, Skill Development, Robotics
Yingbin Zhang; Yafei Ye; Luc Paquette; Yibo Wang; Xiaoyong Hu – Journal of Computer Assisted Learning, 2024
Background: Learning analytics (LA) research often aggregates learning process data to extract measurements indicating constructs of interest. However, the warranty that such aggregation will produce reliable measurements has not been explicitly examined. The reliability evidence of aggregate measurements has rarely been reported, leaving an…
Descriptors: Learning Analytics, Learning Processes, Test Reliability, Psychometrics
Žanko, Žana; Mladenovic, Monika; Krpan, Divna – Journal of Computer Assisted Learning, 2022
Background and Context: Most studies about programming misconceptions are conducted at the undergraduate and graduate levels. Since the age level for starting learning programming is getting lower, there is a need for determining programming misconceptions for younger learners. Objective: Our goal is to determine programming misconceptions and…
Descriptors: Programming, Misconceptions, Grade 5, Elementary School Students
Dominic Lohr; Hieke Keuning; Natalie Kiesler – Journal of Computer Assisted Learning, 2025
Background: Feedback as one of the most influential factors for learning has been subject to a great body of research. It plays a key role in the development of educational technology systems and is traditionally rooted in deterministic feedback defined by experts and their experience. However, with the rise of generative AI and especially large…
Descriptors: College Students, Programming, Artificial Intelligence, Feedback (Response)
Temesgen Samuel; Hsiu-Ling Chen; Abebayehu Yohannes – Journal of Computer Assisted Learning, 2025
Background: As highly interactive hands-on learning tools, robots can inspire new generations of mathematics students. However, to date, no comprehensive systematic reviews have been conducted on robot-assisted mathematics education from K-12 through higher education. Hence, it is important to explore the research evidence of robot-assisted…
Descriptors: Mathematics Instruction, Robotics, Technology Uses in Education, Elementary Secondary Education
Yanjia Liu; Chao Qin; Hao He – Journal of Computer Assisted Learning, 2024
Background: The world is moving towards digitalization and intelligence. Programming has become an essential development competency. Even though many countries are currently making great efforts to expand programming education, the programming education in these countries shows an imbalance in geographical and gender dimensions. We found that few…
Descriptors: Programming, Females, Womens Education, Rural Areas

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