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<p>This paper studies the use of artificial intelligence technology in the field of education and the way of empowering vocational education and constructs a wisdom teaching model of vocational education based on artificial intelligence. It also applies entropy weight and a fuzzy comprehensive evaluation model to determine evaluation indexes and weights, constructs a fuzzy relationship matrix, and synthesizes a fuzzy comprehensive evaluation model. Based on the model, the teaching effect of vocational education with artificial intelligence is studied, and the advantages of wisdom teaching in the creation of a learning environment and the triggering of students’ interest in learning, creative thinking and problem-solving ability are analyzed by comparing with traditional teaching methods. The results show that there is a significant difference between the effect of AI teaching and traditional teaching, p&lt;0.05. For problem-solving ability, the average score of AI teaching students (M=4.049) is higher than the average score of traditional teaching (M=3.153), where t=14.745, p=0&lt;0.05. The study is crucial for the utilization of artificial intelligence in education and the modernization and reform of teaching.</p>
</abstract>

This paper studies the use of artificial intelligence technology in the field of education and the way of empowering vocational education and constructs a wisdom teaching model of vocational education based on artificial intelligence. It also applies entropy weight and a fuzzy comprehensive evaluation model to determine evaluation indexes and weights, constructs a fuzzy relationship matrix, and synthesizes a fuzzy comprehensive evaluation model. Based on the model, the teaching effect of vocational education with artificial intelligence is studied, and the advantages of wisdom teaching in the creation of a learning environment and the triggering of students’ interest in learning, creative thinking and problem-solving ability are analyzed by comparing with traditional teaching methods. The results show that there is a significant difference between the effect of AI teaching and traditional teaching, p<0.05. For problem-solving ability, the average score of AI teaching students (M=4.049) is higher than the average score of traditional teaching (M=3.153), where t=14.745, p=0<0.05. The study is crucial for the utilization of artificial intelligence in education and the modernization and reform of teaching.

Research on Artificial Intelligence Enabling High-Quality Development of Vocational Education

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

This paper studies the use of artificial intelligence technology in the field of education and the way of empowering vocational education and constructs a...

Research on Artificial Intelligence Enabling High-Quality Development of Vocational Education

Publié en ligne: 05 déc. 2023

Pages: -

Reçu: 04 févr. 2023

Accepté: 15 juin 2023

DOI: https://doi.org/10.2478/amns.2023.2.01346

Mots clés
Entropy weight method, Fuzzy comprehensive evaluation method, Relationship matrix, Pearson chi-square test, Vocational education

© 2023 Ming Kong et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Research on Artificial Intelligence Enabling High-Quality Development of Vocational Education

Publié en ligne: 05 déc. 2023

Pages: -

Reçu: 04 févr. 2023

Accepté: 15 juin 2023

DOI: https://doi.org/10.2478/amns.2023.2.01346

Mots clésEntropy weight method, Fuzzy comprehensive evaluation method, Relationship matrix, Pearson chi-square test, Vocational education

© 2023 Ming Kong et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Mots clés
Entropy weight method, Fuzzy comprehensive evaluation method, Relationship matrix, Pearson chi-square test, Vocational education