Deep learning based AI-driven teaching models in Chinese high school English class
A case study of reading lessons
Bibliographic Data
| ID | 22162052 |
|---|---|
| Authors | Yuxin Liu (0000-0001-9753-2617), Yu‐xin Liu (0000-0002-5815-8244, Beijing Jiaotong University), Chengche Qiao (0000-0002-0531-9585, Beijing Jiaotong University, corresponding author) |
| Year | 2025 |
| Volume | 10 |
| Publication date | 2025-05-30 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Frontiers in Education (JOURNAL) |
| Journal identifiers | ISSN: 2504-284X • E-ISSN: 2504-284X |
| Publisher | Frontiers Media SA (PUBLISHER • CH) |
| DOI | 10.3389/feduc.2025.1591393 |
| OpenAlex | W4410905621 |
| Language | EN |
| Citations received | 1 |
| References cited | 26 |
The traditional English teaching model placed more emphasis on the rote memorization of knowledge, with less focus on encouraging deeper cognitive engagement, which may lead to more fragmented understanding among students. Nowadays, as intelligent technology evolves and educational objectives shift, traditional teaching models face new challenges, suggesting the need for innovative adaptation in high school education. Based on the theory of deep learning, this paper explores an AI-driven instruction model for high school English reading from five dimensions, that is, theoretical foundation, implementation conditions, teaching objectives, operational procedures, and teaching assessment, in an attempt to support deep thinking and core competencies of students, thus providing a possible direction for the sustainable development of high school English education. The practice of AI-driven education based on high school English indicates that the proposed instruction model not only optimizes traditional teaching models but also enhances the deep learning capabilities and higher-order thinking skills of students
Deep learning · Linguistics · Mathematics education · AI and Big Data Applications · Computer Science · Educational Technology and Pedagogy · Online Learning and Analytics · Psychology · Artificial Intelligence
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| Citations per year | 1 |
|---|---|
| Citation span | 2026 - 2026 (1) |
| Highly cited | No |