Research on the Mechanism of the Impact of Artificial Intelligence Literacy on the English Learning Behavior Intention of Higher Vocational Students
Abstract
The artificial intelligence technology has experienced explosive growth and has permeated into every corner of society, reshaping people's lifestyles, work patterns, and learning methods. This article conducts an in-depth examination of how the three core competence elements of higher vocational college students - artificial intelligence literacy and learning outcomes - influence the decision-making mechanism of students' intentions to adopt AI tools to assist in English learning in an educational environment where generative AI technology is developing rapidly. By constructing a multi-dimensional theoretical analysis framework, this study focuses on analyzing the paths of interaction between these three key variables and the AI-assisted learning behavior intentions. This study uses the questionnaire survey method to collect data and employs the structural equation model for empirical testing. The research findings reveal that intelligent knowledge, intelligent skills, and intelligent thinking in artificial intelligence literacy significantly positively influence students' intentions for English learning behavior, while intelligent assessment cannot affect students' English learning behavior intentions; learning outcomes play a significant mediating role between artificial intelligence literacy and behavior intentions. The research results indicate the importance of enhancing students' technical literacy in the context of the artificial intelligence era for promoting language learning, providing theoretical basis and practical guidance for the reform of higher vocational English teaching. This study innovatively incorporates artificial intelligence literacy into the research field of language learning behavior, expanding the theoretical boundaries of educational technology application.
Full Text:
PDFDOI: https://doi.org/10.22158/wjeh.v7n6p70
Refbacks
- There are currently no refbacks.
Copyright © SCHOLINK INC. ISSN 2687-6760 (Print) ISSN 2687-6779 (Online)