Common classroom teaching analysis, which has focused on counting and coding the teacher-student behaviors and discourse interactions, faces many difficulties as content-free, low efficiency, and small scale in analysis. To overcome these shortcomings, and foster high-quality classroom teaching, the current study proposes a blended human and Artificial Intelligence (AI) technology for classroom teaching analysis named as TESTII. It consists of five steps identifying teaching events, sequencing the pedagogies of classroom teaching structure, analyzing teacher-student interaction, interpreting teaching meaning, and providing improvement strategies for high-quality classroom teaching.