In order to overcome the limitations of low recall rate and low accuracy of evaluation indicators in traditional online course teaching effectiveness evaluation methods, a new evaluation method of ChatGPT intervention in online course teaching effectiveness using principal component regression analysis is proposed. Principal component regression analysis is adopted to screen evaluation indicators to establish an evaluation index system for ChatGPT intervention in online course teaching effectiveness. The evaluation index data is clustered using Gaussian mixture model, and then input into RBF neural network to obtain the evaluation results of ChatGPT intervention in online course teaching effectiveness. The experimental results show that the proposed method achieves a maximum recall rate of 98.74% in evaluation indicates, a minimum screening time of 1.28 seconds, and evaluation accuracy ranging from 63.8% to 85.8%.
Wang et al. (Thu,) studied this question.