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Direct linkQian Fu; Xinyi Zhou; Yafeng Zheng; Zhenyi Wang – Journal of Computer Assisted Learning, 2025
Background: Understanding algorithms is crucial for programming education, yet their abstract nature often challenges students. Algorithm visualisation (AV) has been proven effective in enhancing algorithmic thinking among university students. However, its efficacy for elementary school students and the optimal forms of AV tools remain unclear.…
Descriptors: Algorithms, Visualization, Elementary School Students, Learning Motivation
Katai, Zoltan; Osztian, Erika – Journal of Computer Assisted Learning, 2023
Background: This study is the first to address the topic of schematic versus realistic dynamic visualization with particular focus on the human movement effect (HME) when the content to be learned takes the form of a computer algorithm. An AlgoRythmics dance choreography illustration (HM-realistic) was compared with an abstract computer animation…
Descriptors: Computer Software, Algorithms, Visualization, Animation
Gulnur Tyulepberdinova; Madina Mansurova; Talshyn Sarsembayeva; Sulu Issabayeva; Darazha Issabayeva – Journal of Computer Assisted Learning, 2024
Background: This study aims to assess how well several machine learning (ML) algorithms predict the physical, social, and mental health condition of university students. Objectives: The physical health measurements used in the study include BMI (Body Mass Index), %BF (percentage of Body Fat), BSC (Blood Serum Cholesterol), SBP (Systolic Blood…
Descriptors: Artificial Intelligence, Algorithms, Predictor Variables, Physical Health
