Exploring the digital development of art education can effectively enhance students’ creativity in art design. This paper constructs a digital teaching platform for art education based on big data technology and analyzes student learning behavior data in the teaching platform. For student learning behavior with a new Hawkes process for data extraction, the decomposition of the student learning effect is realized by data encoder, event-level decoder and course-level decoder. Performance tests and art teaching effect analysis were conducted for the platform built in this paper. From the performance test, the throughput of the test interface is 580 when the server CPU is maintained at about 26%, memory is maintained at about 48.62%, and load is maintained at about 4.7. From the teaching effect, the four dimensions of students’ creativity changes had significant differences; namely, the p-values of adventurousness, curiosity, imagination, and challenge were 0.189, 0.247, 0.076, and 0.425, respectively. This indicates that the digital teaching platform for art education built by using big data technology can effectively enhance students’ creativity and also provide a new direction for the digital development of art education.