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To improve students' sports skills performance, it is important to engage them in reflective practice. However, in physical classes, a teacher generally needs to face a number of students, and hence it is almost impossible to provide detailed guidance or feedback to individual students. Scholars have been trying to use Artificial Intelligence (AI) technologies to provide personalized support to individual students in diverse courses; however, in terms of promoting physical skills, there is a lack of sufficient research or practices. The present study aimed to develop a yoga automatic assessment and feedback system using AI technology to provide personalized feedback to engage individual students in reflective practice. To examine the learning effectiveness of the developed system, a total of 96 students were assigned to be the experimental group and adopted the yoga automatic assessment and feedback system for learning, while a total of 91 students were in the control group and adopted the general online learning system. The results showed that adopting the yoga automatic assessment and feedback system for learning could significantly increase students' yoga skills performance. In addition, it had positive effects on students' skills learning, which was conducive to "promoting reflection," "enhancing learning motivation," and "obtaining feedback."

Traditional waste incineration generates a large amount of exhaust gas, resulting in adverse environmental impacts. Therefore, we developed an organic and intelligent photochemical processing system that utilizes high-energy lasers for incineration, thereby reducing the production of exhaust gas. A large-scale laser machine was set up, incorporating low-cost 2D Light Detection and Ranging (LiDAR) technology for system sensing, which performs angle range and threshold filtering, as well as multispectral laser allocation, integrated with the laser ablation machine system. After testing, the error was <5 mm (<8%), achieving precise object scanning and ranging and solving the problem of manual laser positioning. Experimental results showed that CO2 lasers can effectively process organic materials and medical waste of different sizes. This innovative research will have profound implications for the future development of environmental protection and incineration technologies. In the future, it has widespread application prospects in areas such as pet waste disposal and medical waste treatment. [ABSTRACT FROM AUTHOR]

Affect can significantly influence education/learning. Thus, understanding a learner's affect throughout the learning process is crucial for understanding motivation. In conventional education/learning research, learner motivation can be known through postevent self-reported questionnaires. With the advance of affective computing technology, researchers are able to objectively identify and measure a learner's affective status during the entire learning process in a real-time manner, and then they are able to understand the interrelationship between emotion, motivation and learning performance. There are over 100 papers in the ScienceDirect database with the keywords 'affective computing in education' or 'affective computing in learning,' which reveals that this emerging technology has been applied to education/learning. This study intends to categorize and summarize those measurements so as to realize their applicability, feasibility and trends. Finally, some challenges and suggestions are then raised for helping educational researchers when applying affective computing technology. [ABSTRACT FROM AUTHOR]