Evaluation of College Teachers’ Information Teaching Ability Based on Adaptive Genetic Algorithm

There are some problems in the evaluation of University teachers’ information teaching ability ability, such as the fuzziness of the evaluation results, the difficulty in implementation of the evaluation, and the singleness of the evaluation methods. Based on this, this paper establishes the evaluation index system of teachers’ education technical ability, evaluates it through the JZ online platform, and takes the survey data as a learning sample. This paper establishes the theoretical model of BP network, uses the adaptive genetic algorithm to optimize it, substitutes the optimization results into the network to train the learning samples, and forms the evaluation model of University teachers’ information teaching ability ability. Finally, through specific examples, the superiority of the educational technology capability model of university teachers is analyzed. The results show that the algorithm optimization effect of the model is obvious. At the same time, the efficiency and accuracy of evaluation are better than other models. The evaluation results can scientifically reflect the educational technology ability of University teachers.