Emotional Multifaceted Feedback on AI Tool Use in EFL Learning Initiation: Chain-Mediated Effects of Motivation and Metacognitive Strategies in an Optimized TAM Model
Project Overview
The document examines the role of generative AI in enhancing English as a Foreign Language (EFL) learning by analyzing how technology acceptance constructs—such as perceived usefulness, ease of use, and self-efficacy—affect learners' motivation and metacognitive strategies. It emphasizes that positive perceptions of AI tools significantly contribute to increased engagement and resilience among students, ultimately leading to better learning outcomes. The findings advocate for educators to harness AI technologies effectively, suggesting that by optimizing instructional practices with AI support, educators can foster a more motivating and resilient learning environment. This integration of AI not only aids in language acquisition but also empowers learners to develop essential cognitive strategies necessary for overcoming challenges in their educational journeys.
Key Applications
AI-assisted language learning tools
Context: First-year English majors in EFL contexts in China
Implementation: A survey was conducted among 730 students using structural equation modeling to analyze the data on their engagement with AI tools.
Outcomes: Enhanced learning motivation and metacognitive strategies, leading to improved psychological resilience and adaptability in language learning.
Challenges: Limited understanding of the interplay between technology acceptance and motivational elements in existing literature.
Implementation Barriers
Research gaps
Current literature has predominantly focused on isolated aspects of AI tool adoption without addressing their interplay with intrinsic motivations and metacognitive strategies.
Proposed Solutions: Future research should aim for more comprehensive models that integrate these factors.
Project Team
Le Yao
Researcher
Yantong Liu
Researcher
Contact Information
For information about the paper, please contact the authors.
Authors: Le Yao, Yantong Liu
Source Publication: View Original PaperLink opens in a new window
Project Contact: Dr. Jianhua Yang
LLM Model Version: gpt-4o-mini-2024-07-18
Analysis Provider: Openai