The Optimization of Digital Art Teaching Platform Based on Information Technology and Deep Learning

Abstract

The study aims to improve the daily teaching level of the school and make students enjoy better teaching methods. Firstly, the Internet of Things (IoT) and deep learning (DL) are deeply studied through information technology (IT). Secondly, the calculation methods based on the IoT and DL are analyzed, through which the research model is constructed. Finally, a digital teaching platform is established through the research model to conduct a real-time statistical survey of students and teachers. The results show that students are leading in the daily teaching process. According to the survey results, most students spend 3 to 4 hours in daily extra-curricular learning; 45% of them acquire knowledge mainly through classroom learning, and 23% through online learning. Their main difficulty in learning is learning ability, accounting for 48%. Moreover, it is an energy problem, accounting for 28%. 64% of students are passive learning, far more than 37% of active learning students. This study combines multiple fields across disciplines, such as IT, IoT, and DL. Digital art teaching platforms usually focus on creativity and performance, and combining IoT and DL can provide art students with a more personalized, real-time teaching experience, and promote the cross-application of digital art and cutting-edge technologies.

Keywords

• Information technology
• Internet of Things
• deep learning
• digitization
• teaching platform