Quality Evaluation Method of a Mathematics Teaching Model Reform Based on an Improved Genetic Algorithm

The poor comprehensiveness of the evaluation indexes of quality evaluation methods for the traditional college mathematics teaching model reform results in low accuracy of the evaluation outcomes. In this paper, aiming at this problem, a quality evaluation method for the college mathematics teaching model reform, based on the genetic algorithm, is proposed. The simulated annealing algorithm uses the weighted comprehensive objective evaluation multiobjective optimization effect that can effectively improve the accuracy of the evaluation results. In the training process, the gradient descent back-propagation training method is used to obtain new weights for the quality evaluation of college mathematics teaching mode reforms and to score various indicators and evaluate the indicators. The mean value of the outcomes is the result of mathematics teaching quality evaluation. The experimental results show that the training error of the convolutional network of the proposed method is significantly small. Based on the genetic algorithm that improves the convolutional network training process, the obtained quality evaluation outcomes are higher in accuracy, better in goodness of fitness function, and considerably lower than other state-of-the-art methods. We observed that the improved genetic algorithm has a more than 90% goodness of fit and the error is significantly lower, that is, 0.01 to 0.04, than the classical genetic algorithm.

Research on Online Mathematics Teaching in Chinese Colleges

Aims: This paper was carried out to understand the situation and implementation effect of mathematics education and teaching work in colleges under the epidemic situation, grasp the problems and solving strategies in the practical processes, provide new ideas for mathematics education researchers and new inspiration for optimizing online teaching. Methodology: The researcher checked all references that met the research criteria and finally identified 37 papers as research papers and summarized all the achievements by taking notes. Conclusions: It is found that the current research results for college mathematics online teaching can be roughly divided into three types: college mathematics online teaching models and platforms, implementation strategies, and evaluation reflections. (1) Current domestic studies mainly focus on the selection of online teaching platforms and models, the implementation strategies of college mathematics online teaching (including strategies before class, during class and after class), and evaluation and reflection (advantages, limitations, factors and optimization). Previous studies have included many achievements with a certain depth and laid a good foundation for future research. (2) Previous studies have great limitations in the selection of research methods, and lack of empirical research to strengthen persuasiveness and reliability. Secondly, although the predecessors have obtained many results, the depth and breadth are very limited. (3) There is still a lot of room for research on this subject, such as online teaching research for other narrow higher mathematics courses, research on online teaching models suitable for students of different professional categories and ability levels, and establishing a sound evaluation system of blended learning model, etc.