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Qian 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
Kang, Tinghu; Tang, Tinghao; Zhang, Peizhi; Luo, Shu; Qi, Huanhuan – British Journal of Educational Psychology, 2023
Background: The ability to translate concrete manipulatives into abstract mathematical formulas can aid in the solving of mathematical word problems among students, and metacognitive prompts play a significant role in enhancing this process. Aims: Based on the concept of semantic congruence, we explored the effects of metacognitive prompts and…
Descriptors: Metacognition, Eye Movements, Cues, Elementary School Students
Miaomiao Liu; Yixun Li; Yongqiang Su; Hong Li – Scientific Studies of Reading, 2024
Purpose: This study sought to 1) identify linguistic features important for Chinese text complexity with a theory-based and systematic approach, and 2) address how feature sets and algorithms affect the performance of Chinese text complexity models. Method: Texts from Chinese language arts textbooks from Grades 1 to 6 (N = 1,478) in Mainland China…
Descriptors: Difficulty Level, Textbooks, Algorithms, Artificial Intelligence