With the rapid development of big data and smart education, the application of diagnostic learning analysis technology has become an important trend in the field of education. The purpose of this study is to explore the application effect of this technology in education, especially in the aspects of personalized learning and teaching efficiency improvement. The attitudes of educators and learners were collected through questionnaires, the practical application effect of the technology was verified by experimental design, and the effectiveness of the technology was analyzed deeply through model construction and evaluation. The results show that diagnostic learning analytics can significantly improve teaching quality and learning outcomes, despite data privacy and technology acceptance challenges. This study reveals the application potential of this technology in the field of education, and provides a valuable reference for future research in related fields. Despite the limitations of sample representation and long-term effect analysis, this study still has important guiding significance for the future development of educational technology.