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Motivating Students With Different Needs to Learn Chinese in a Mixed-Background Classroom by Robot-Assisted Learning

Ka Yan Fung, Kwong-Chiu Fung, Tze Leung Rick Lui, Kuen Fung Sin, Huamin Qu, Shenghui Song

Year
2025
Citations
5

Abstract

Mastering the visually complex characters of the Chinese language poses significant challenges for students. The situation is even worse in Hong Kong, where students with different backgrounds, including students with/without dyslexia and non-Chinese speaking (NCS) students, are placed in the same class. Interactive design has been proven effective in enhancing students' learning performance and engagement. However, developing a learning tool for students with diverse backgrounds is challenging. This study proposes a robot-assisted Chinese learning system (<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RACLS</i>) for those with diverse backgrounds and investigates its impact on learning motivation by a comparison study. In particular, 39 students participate in a five-day robot-led training program, while another 39 students received traditional teacher-led training. The comparison results show that <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RACLS</i> can enhance the emotional engagement of students with dyslexia and strengthen the behavioral engagement of students without dyslexia. Interestingly, the learning motivation of NCS students in the experimental and control groups is enhanced similarly.

Keywords

Computer scienceRobotHuman–computer interactionMathematics educationMultimediaArtificial intelligencePsychology

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