Acute Teaching Method of College Physical Skills Based on Mobile Intelligent Terminal

Abstract

Mobile technology can make lessons of physical skills for the students to prepare them more vibrant. Its multicultural, consolidated, and communicative characteristics contribute to the improving teaching performance, excitement of learners, reformation of learning, and a basic idea of teaching mode. The challenge facing college physical education professionals is emotionally labile students, repetition of their education, and the lack of appropriate technology, resources, school violence, and behavioral issues. Because of the high levels of bullying experienced by students with learning and attention difficulties, misbehavior and absence are more likely to occur. The school environment and negative emotions can both aggravate academic difficulties. The proposed methodology involves evaluating student’s physical training based on big data analysis (ESPT-BDA) to compensate voluntary sport behavior by neglecting its unwanted attitude or values and solving the problem of uniform learning to meet the student’s requirements. Repetition helps hone a talent by putting it to use repeatedly. The interval at which a skill is performed is another critical component of repetition. Using spaced repetition as a learning strategy involves gradually increasing the time between repetitions of the same piece of knowledge. The regulating intelligent control framework is used to compute an effective method of directing the insufficient and improper system to achieve a specific objective in an uncertain context. A convolution neural network is implemented to automatically detect vital physical activity characteristics without a need for human monitoring. Various experiment’s findings demonstrate the effect of different sequences up to 96.51% properly classified test data and improve evaluation of intelligent control framework, intelligent practicing intensity control 94.3%.