Affiliations: School of Literature and Law, North China Institute of Science and Technology, Sanhe, Hebei, China
Correspondence:
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Corresponding author. Wang Li, School of Literature and Law, North China Institute of Science and Technology, Sanhe, Hebei, China. E-mail: wangli@mailfence.com.
Abstract: The teaching of linguistics is limited by the influence of various factors, which leads to poor teaching effect, and the teaching process is difficult to evaluate. In order to improve the efficiency of linguistics teaching, this paper uses improved machine learning algorithms to construct a linguistics artificial intelligence teaching model. According to the teaching needs of linguistics, the efficiency of the teaching process is improved, and the teaching evaluation is performed, and the root cause analysis algorithm based on MCTS is optimized. Moreover, according to the frequent item set algorithm in data mining, a layered pruning strategy is proposed to further reduce the search space and improve the efficiency of the model. In addition, this study combines with the comparative teaching experiment to study the efficiency of artificial intelligence models in linguistics teaching. The statistical results show that the model proposed in this paper has a certain effect.
