In music classroom teaching, traditional digital applications mostly stay at the level of courseware display and resource playback, which is difficult to form a continuous recognition of students ‘learning status, and it is difficult to support immediate regulation in the classroom. To solve this problem, this paper constructs a music classroom teaching model assisted by digital technology, which integrates audio collection, behavior log analysis, learning feedback processing and resource intelligent matching into the same teaching link, forming a classroom operation mechanism of “data perception – state recognition – interaction support – result reflux”. The study adopted a 16-week quasi-experimental design, and took 96 students as objects to compare and analyze the implementation effect of digital teaching mode and conventional teaching mode. The results showed that the comprehensive score of music skills in the experimental group increased from 68.42 to 84.76 points, the correct rate of pitch recognition increased from 71.08% to 89.63%, the rate of rhythm stability increased from 72.35% to 90.27%, and the classroom participation index reached 87.56 points, which were significantly better than those in the control group. The research shows that embedding computer data processing methods into music classroom is helpful to improve the timeliness of teaching feedback, the pertinence of resource support and the controllability of learning process, which has practical significance for the optimization of music classroom teaching mode.
