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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
Tanya Chichekian; Joel Trudeau; Tawfiq Jawhar; Dylan Corliss – Journal of Computer Assisted Learning, 2024
Background: Despite its obvious relevance to computer science, computational thinking (CT) is transdisciplinary with the potential of impacting one's analytical ability. Although countless efforts have been invested across K-12 education, there is a paucity of research at the postsecondary level about the extent to which CT can contribute to…
Descriptors: College Students, Computation, Thinking Skills, Transfer of Training
Shimaya, Jiro; Yoshikawa, Yuichiro; Ogawa, Kohei; Ishiguro, Hiroshi – Journal of Computer Assisted Learning, 2021
Encouraging students to actively ask questions during lectures is a formidable challenge that can be addressed through innovative use of information technology. We developed a robotic system that allows students in a lecture to collaboratively decide questions to be asked by a humanoid robot. To verify whether the system reduces hesitation to ask…
Descriptors: Robotics, Technology Integration, Questioning Techniques, Synchronous Communication
Zehang Xie; Xinzhu Wu; Yunxiang Xie – Journal of Computer Assisted Learning, 2024
Background: With the development of artificial intelligence (AI) technology, generative AI has been widely used in the field of education and represents a groundbreaking shift in overcoming the constraints of time and space within educational activities. However, previous literature has not paid enough attention to AI-involved teaching patterns,…
Descriptors: Longitudinal Studies, Undergraduate Students, Robotics, Technology Uses in Education
Iio, Takamasa; Maeda, Ryota; Ogawa, Kohei; Yoshikawa, Yuichiro; Ishiguro, Hiroshi; Suzuki, Kaori; Aoki, Tomohiro; Maesaki, Miharu; Hama, Mika – Journal of Computer Assisted Learning, 2019
This paper reports how robot-assisted language learning (RALL) impacts Japanese adults' English speaking skills. With existing research on RALL focusing on children, there is little evidence indicating RALL's effects on adults. We developed a RALL system comprising a robot, a tablet, and designed learning materials for speaking practice. To…
Descriptors: English (Second Language), Pretests Posttests, Asians, Accuracy