Construction and Application of Teaching Quality Evaluation System under the Mathematical Intelligence Teaching Reform

Abstract

With the advent of the digital intelligence era, reforms in digital intelligence-based teaching present new opportunities and challenges for evaluating teaching quality. This paper examines the significance of teaching quality evaluation in the context of digital intelligence teaching reform, emphasizing its role in enhancing instructional quality, supporting student development, and fostering educational innovation. A teaching quality evaluation index system is constructed, outlining evaluation objectives, defining evaluation content, and highlighting the system's key characteristics. Various evaluation methods are explored, including the establishment of interactive digital classrooms, the development of an intelligent learning resource supply system, and the application of a "digital intelligence integration" evaluation strategy. The paper analyzes the impact of digital intelligence teaching reform on teaching quality, including the provision of new tools and approaches, enrichment of instructional resources, and promotion of teachers' professional growth and instructional innovation. Finally, a teaching quality evaluation system tailored to the digital intelligence teaching environment is developed. By integrating big data and artificial intelligence technologies, an evaluation model is established based on the principles of comprehensiveness, objectivity, and scientific rigor, utilizing intelligent evaluation tools and methods. The proposed approach aims to improve teaching quality, support the holistic development of students, and drive innovative advancements in education.