Construction and Application of Undergraduate Teaching Evaluation System Based on Big Data Technology

In response to the requirements for intelligence, collaboration, and interactivity in undergraduate teaching evaluation under the background of big data technology, this paper proposed an undergraduate education teaching evaluation system based on big data technology. Based on the Analytic Hierarchy Process and Entropy Weight Method, the system linearly fits the two weights to calculate the indicator system weights for teaching evaluation. Under the indicator system framework, the system can achieve multi-form, multi-dimensional, and three-dimensional undergraduate evaluation data collection, monitoring, and analysis to assist schools in providing accurate support for training programs, teaching investment, scientific innovation, and employment. The system focuses on the real-time and dynamic nature of self-evaluation in universities, integrating data collection, intelligent analysis, and precise decision support, enhancing the role of evaluation in promoting teaching, optimizing the decision-making ability of universities, and realizing the re-evaluation of the value of evaluation in universities.