Yanbing Liang, Jun Wu
School of Economics and Management, Guangdong Vocational College of Post and Telecom, Guangzhou, Guangdong, China
To realize the deep integration of artificial intelligence and vocational education and promote the reform of teaching and learning supply mode is the basic path to continuously improve the quality of talent training. This paper starts with the current situation and existing problems of artificial intelligence embedding in higher vocational teaching, and takes the three-core links of teaching, learning and evaluation as the path of embedding artificial intelligence key technology into education. By studying “what to teach”, “how to teach”, “how to learn” and “how to evaluate”, this paper deeply empowers teachers, students and educational management with artificial intelligence to achieve accurate education, personalized learning and dynamic evaluation. The core courses of marketing major are selected to carry out teaching practice. The research finds that the embedding of artificial intelligence in higher vocational teaching can effectively solve the problems of students' diversified learning needs, low lasting enthusiasm for learning, and insufficient systematic assessment and evaluation, which can improve students' academic performance, enhance students' learning initiative, and enhance students' satisfaction with courses.
Artificial Intelligence, Higher Vocational Education, Teaching Reform, Path Study
Yanbing Liang, Jun Wu. Research on the Method and Path of Embedding Artificial Intelligence into Higher Vocational Teaching Reform. Frontiers in Educational Research (2023) Vol. 6, Issue 18: 53-58. https://doi.org/10.25236/FER.2023.061810.
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