Practical Evaluation of Human–Computer Interaction and Artificial Intelligence Deep Learning Algorithm in Innovation and Entrepreneurship Teaching Evaluation

Abstract

The rise of knowledge economy has drawn much attention to Innovation and Entrepreneurship Education (IEE). IEE is conducive to helping graduates relieve employment pressure, and also to cultivating students’ innovation ability and entrepreneurial willingness, which is also of great significance for promoting high-quality quantitative and sustainable development of social economy. However, the current IEE still has some limitations, such as the students’ insufficient entrepreneurial willingness, low innovation practice ability, and unreasonable evaluation methods of innovation and entrepreneurship teaching, which hinder the further development of IEE. Therefore, for the purpose of further promoting the development of IEE, this article studied the evaluation of innovation and entrepreneurship teaching, and proposed an innovation and entrepreneurship teaching evaluation system combining Human–Computer Interaction (HCI) and Deep Learning (DL). The evaluation system was used to evaluate the innovation and entrepreneurship teaching of Class A and Class B. The evaluation result showed that Class A’s innovation and entrepreneurship teaching evaluation score was 7; Class B’s innovation and entrepreneurship teaching evaluation score was 7.1. The evaluation of innovation and entrepreneurship teaching in Class A and Class B was still not high enough, and the teaching quality and effect still needed to be improved; the innovation and entrepreneurship teaching evaluation system combined with HCI and DL had strong operability.