%0 Journal Article %T AI赋能下中学学困生英语听力学习策略培训研究
AI-Enabled Training of English Listening Strategies for Academically Challenged Secondary School Students %A 林佳鑫 %A 左义 %J Advances in Education %P 762-769 %@ 2160-7303 %D 2025 %I Hans Publishing %R 10.12677/ae.2025.155830 %X 在英语核心素养培养的背景下,听力作为语言输入的核心技能,对学生的语言习得至关重要。然而,中学学困生在英语听力学习中面临诸多困难,如何有效提升其听力能力成为教育领域的重要课题。本文通过综述国内外相关文献,探讨了学困生听力学习策略的使用现状及其影响因素,并重点分析了人工智能(AI)技术在听力策略培训中的应用潜力。研究表明,AI技术能够通过个性化学习路径、动态反馈和情感支持,显著提升学困生的元认知、认知及社会/情感策略运用能力。此外,本文还探讨了AI辅助教学的实施可行性,包括技术适配性、教师培训及伦理风险规避等问题。未来研究应进一步探索AI与听力策略培训的深度融合,以期为学困生的英语听力教学提供理论与实践参考。
Under the framework of cultivating English core competencies, listening, as a fundamental language input skill, plays a pivotal role in students’ language acquisition. However, academically challenged students in secondary schools face numerous difficulties in English listening comprehension, making the improvement of their listening abilities a critical issue in education. This paper reviews relevant domestic and international literature to explore the current usage of listening strategies among academically challenged students and their influencing factors, with a particular focus on the potential of artificial intelligence (AI) technology in listening strategy training. Research indicates that AI can significantly enhance students’ metacognitive, cognitive, and social/affective strategy application through personalized learning pathways, dynamic feedback, and emotional support. Additionally, this paper examines the feasibility of AI-assisted instruction, including technical adaptability, teacher training, and ethical risk mitigation. Future research should further investigate the deep integration of AI and listening strategy training to provide theoretical and practical insights for teaching English listening to academically challenged students. %K 学困生, %K 英语听力, %K 学习策略, %K 人工智能, %K 策略培训
Underachiever %K English Listening %K Learning Strategies %K Artificial Intelligence %K Strategy Training %U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=114860