This work explores the multidimensional impacts of an Artificial Intelligence (AI) environment on Taekwondo training for middle school students. It establishes an intelligent training system and personalized training programs and compares the training outcomes of an experimental group (trained in an AI environment) with a control group (trained in a traditional environment). All participants are from the same middle school and undergo baseline assessments before the study to ensure data reliability and consistency. The results indicate that psychological state significantly and positively impacts students’ motivation levels (supporting Hypothesis 1), meaning that a good psychological state can markedly enhance middle school students’ training motivation. Additionally, motivation levels have a notable positive effect on the performance of technical movements (supporting Hypothesis 2). This illustrates that higher motivation levels can effectively improve the quality of technical movements, highlighting the importance of motivation in training outcomes. Furthermore, self-efficacy also has a significant positive influence on technical movement scores (supporting Hypothesis 3), indicating that the higher the students’ confidence in their abilities is, the better their technical performance is. The impact of training records on technical movement scores is likewise significant (supporting Hypothesis 4), where more training time and higher engagement can effectively enhance technical scores, emphasizing the importance of behavioral involvement. Finally, motivation levels also have a significant positive effect on self-efficacy (supporting Hypothesis 5), with high motivation levels contributing to an increase in students’ self-efficacy.
Yuan et al. (Mon,) studied this question.