Teaching Strategies and Psychological Effects of Entrepreneurship Education for College Students Majoring in Social Security Law Based on Deep Learning and Artificial Intelligence

Abstract

This study aims to achieve the goal of cultivating and reserving emerging professional talents in social security law, improve the curriculum and mechanism of entrepreneurship education, and improve students’ entrepreneurial willingness and entrepreneurial ability. Deep learning technology is used to study the psychological effects of entrepreneurship education for college students majoring in social security law. Firstly, the concept of entrepreneurial psychology is elaborated and summarized. A related model is designed using the theory of proactive personality and planned behavior through questionnaire survey and regression analysis to explore the relationship between students’ entrepreneurial psychology and entrepreneurial intention. Secondly, an entrepreneurship education method based on deep learning is proposed, and a teaching model of multi-dimensional collaborative entrepreneurship education practice is constructed. On this basis, the deep learning algorithm combines the characteristics of the personalized recommendation algorithm to construct an efficient Problem-Based Learning (PBL) learning resource recommendation algorithm. Finally, the proposed method is tested. The results show that the Significant (Sig.) value of students who have participated in PBL deep learning courses is less than 0.05, indicating that PBL significantly improves students’ learning ability and the ability to deal with entrepreneurial environments. The results verify the impact of entrepreneurial learning on entrepreneurial intentions. The research on PBL online learning recommendation system shows that the proposed recommendation algorithm is superior to the traditional recommendation algorithm in both roots mean square error value and mean absolute error value on both datasets. The proposed method provides a new idea of reform and innovation to cultivate social security law professionals and the cultivation of the reserve model.

How do we choose the appropriate deep learning method for our case? A systematic literature review

“…AE is capable of processing numerical data as well as text. In addition to being able to process panel design parameters as previously described, AE is able to produce output in the form of a learning model that can improve students' skills in entrepreneurship Zhu & Zhang (2022).The fifth deep learning method is BP which able to process numerical data. The last deep learning method is RNN which able to process text data.…”

“…This deep learning-based online PBL learning model also shows a better learning model algorithm compared to conventional methods. Zhu and Zhang (2022)  Deep learning is able to help assess student performance during online classes through students' expressions and postures. This assessment can help teachers to compare student performance when online classes and offline classes, so teachers can find effective ways to improve student performance in learning.…”

Artificial intelligence in entrepreneurship education: a scoping review

“…4.1.2 Machine learning. Nine of 13 studies mentioned machine learning (Alqahtani, 2023;Shepherd and Majchrzak, 2022;Xu and Zhang, 2021;Liang et al, 2021;Tkachenko et al, 2019;Botha et al, 2021;Chen et al, 2021;Zhao et al, 2022;Zhu and Zhang, 2022). Except for educational purposes, the findings were coded from data sourcing, sample size, machine learning algorithm and validation of algorithm, summarized from Luan and Tsai's (2021) methodology of machine learning analysis.…”

“…The application of AI is pointed out with possible utilization, which is still broad and lacks empirical proof (Tarabasz et al, 2018). Learning content recommendations have been discussed (Zhu and Zhang, 2022). Research such as the integration of specific learning content and intelligent technologies, visualization and data privacy will be the further step for educators and software developers.…”

You Can Handle, You Can Teach It: Systematic Review on the Use of Extended Reality and Artificial Intelligence Technologies for Online Higher Education

“…Two publications examined the impact and effectiveness of AI-enabled elearning interaction in online learning during the pandemic in areas related to Education sciences [101], and also in no particular domain in higher education but rather a selection of students and instructors from different majors [102]. One paper focused on Business, Economics, and Administration in entrepreneurship education [103]. Coded within the Humanities, Yang et al [58] integrated an intelligent cloud platform for practical personalized teaching on a cultural industry management major based on a massive online and self-paced open course.…”