Evaluation of Teaching Reliability of Ideological and Political Courses in Colleges and Universities Based on DTW Algorithm

The evaluation of ideological and political courses in universities involves a large amount of time series data, which has complex and nonlinear characteristics, resulting in low reliability of teaching evaluation. Therefore, a reliability evaluation method for ideological and political education courses in universities based on the DTW algorithm is proposed. By using DTW algorithm and cascade filtering technology, useful teaching reliability data is mined from a large amount of raw data and preprocessed to reduce the complexity and nonlinearity of the data. The TF-IDF algorithm is used to calculate the keyword weights of preprocessed data. Through manual label word selection and fine-grained sentiment analysis based on deep learning, multi-dimensional and deep level analysis of teaching evaluation is achieved, thereby more accurately evaluating teaching effectiveness. Tests have shown that the accuracy of the evaluation reaches 98.75%, effectively improving the efficiency and quality of the evaluation.