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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
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
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
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
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)
Peidi Gu; Zui Cheng; Cheng Miaoting; John Poggio; Yan Dong – Journal of Computer Assisted Learning, 2025
Background: Today, the importance of STEM (Science, Technology, Engineering and Mathematics) education and training is widely recognised and accepted. Computer programming courses have become essential in higher education to nurture students' programming, analysis and computational skills, which are vital for success in all STEM fields and areas.…
Descriptors: Active Learning, Student Projects, Individualized Instruction, Student Motivation
Rafael Mellado; Claudio Cubillos – Journal of Computer Assisted Learning, 2024
Background: Effective learning in computer programming courses has been a constant challenge for university teachers and has become a relevant competence for current professionals. The literature on gamification in learning presents mixed results, mainly due to problems in instructional design and inconsistency in gamification. Studies with…
Descriptors: Engineering Education, College Students, Computer Software, Technical Occupations
Qin, Chao; Liu, Yanjia; Zhang, Hemei – Journal of Computer Assisted Learning, 2023
Background: Being easy to learn and fun, block-based programming tools are widely used to teach students introductory programming. Scratch and LEGO robots are two popular block-based programming tools. However, the objects they manipulate are completely different. Scratch manipulates graphical virtual sprites, whereas LEGO robots manipulate…
Descriptors: Foreign Countries, Undergraduate Students, Learner Engagement, Robotics
Yusuf, Abdullahi; Noor, Norah Md – Journal of Computer Assisted Learning, 2023
Background: Several attitude scales have been developed to measure students' attitudes toward computer programming, including the prominent one developed by Cetin and Ozden. The development of these scales stemmed from the elusive nature of attitude and the lack of specific constructs to measure attitude. These instruments measure students'…
Descriptors: Programming, Computer Science Education, Attitude Measures, Student Attitudes
Wang, Yi-Hsuan – Journal of Computer Assisted Learning, 2021
The study designed WebQuest activities and explored the learning performance of learners to understand the suitability of using WebQuest in a college programming course. The study modified the processes of WebQuest based on social constructivism and scaffolding learning, and included programming tasks such as debugging practice to encourage…
Descriptors: Learning Activities, Programming, Academic Achievement, Educational Technology
Mangaroska, Katerina; Sharma, Kshitij; Gaševic, Dragan; Giannakos, Michail – Journal of Computer Assisted Learning, 2022
Background: Problem-solving is a multidimensional and dynamic process that requires and interlinks cognitive, metacognitive, and affective dimensions of learning. However, current approaches practiced in computing education research (CER) are not sufficient to capture information beyond the basic programming process data (i.e., IDE-log data).…
Descriptors: Cognitive Processes, Psychological Patterns, Problem Solving, Programming
Wu, Bian; Hu, Yiling; Ruis, A. R.; Wang, Minhong – Journal of Computer Assisted Learning, 2019
Computational thinking (CT), the ability to devise computational solutions for real-life problems, has received growing attention from both educators and researchers. To better improve university students' CT competence, collaborative programming is regarded as an effective learning approach. However, how novice programmers develop CT competence…
Descriptors: Thinking Skills, Problem Solving, Teaching Methods, College Students
Lee, V. C. S.; Yu, Y. T.; Tang, C. M.; Wong, T. L.; Poon, C. K. – Journal of Computer Assisted Learning, 2018
Many students need assistance in debugging to achieve progress when they learn to write computer programs. Face-to-face interactions with individual students to give feedback on their programs, although definitely effective in facilitating their learning, are becoming difficult to achieve with ever-growing class sizes. This paper proposes a novel…
Descriptors: Computer Science Education, Programming, Computer Software, Feedback (Response)
Sitthiworachart, J.; Joy, M. – Journal of Computer Assisted Learning, 2008
Active learning is considered by many academics as an important and effective learning strategy. Assessment is integrated in learning as a tool for learning, but traditional assessment methods often encourage surface learning (passive learning) rather than deep learning (active learning). Peer assessment is a method of motivating students,…
Descriptors: Peer Evaluation, Learning Strategies, Active Learning, Programming