Structure and Implementation of New Practical English Textbooks Driven by Artificial Intelligence

Forum topic · 小凯 · 2026-09-06

Summary

A paper by Ya Wang, Lei Zhang, and Xueguang Yang (arXiv:2509.00001) explores how artificial intelligence is transforming applied English teaching materials from fixed paper sequences into adaptive learning systems that diagnose learners, recommend tasks, and deliver formative feedback. The authors propose a five-layer architecture consisting of knowledge mapping, learner profiling, task generation, feedback orchestration, and teacher-side governance. A prototype system was evaluated with 186 non-English-major undergraduates over eight weeks of instruction. Compared with a static digital textbook, the AI-driven system raised unit completion accuracy from 72.4% to 84.9%, improved average speaking task scores by 10.8 points, and reduced teacher correction time by 31.6%. The results suggest AI-driven textbooks can offer personalized learning paths, rich practice materials, and traceable classroom data while preserving curriculum stability.

论文概要

Research area: AI/ML Authors: Ya Wang, Lei Zhang, Xueguang Yang Published: 2026-09-06 arXiv: 2509.00001

Abstract

Artificial intelligence is changing the form of applied English materials from fixed paper sequences to adaptive learning systems that can diagnose learners, recommend tasks, and provide formative feedback. This paper studies the structure and application of a new practical English textbook driven by artificial intelligence.

Five-Layer Architecture

The proposed AI-driven textbook is built on a five-layer architecture:

1. Knowledge mapping 2. Learner profiling 3. Task generation 4. Feedback orchestration 5. Teacher-side governance

Evaluation Results

A prototype was tested on 186 non-English-major undergraduates over eight weeks of teaching. Compared with a static digital textbook, the proposed system:

Increased unit completion accuracy from 72.4% to 84.9%
Raised the average score for speaking tasks by 10.8 points
Reduced the teacher's correction time by 31.6%

Conclusion

AI-driven textbooks can deliver personalized learning paths, rich practice materials, and traceable classroom data while maintaining curriculum stability.

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*Auto-collected on 2026-09-06*