基于逆向设计与AIGC融合的高中英语阅读“教–学–评”一体化的课例研究——以人教版选择性必修一“Tu Youyou Awarded Nobel Prize”为例
A Lesson Study on “Teaching-Learning-Assessment” Integration in Senior High School English Reading Based on the Integration of Backward Design and AIGC—A Case of “Tu Youyou Awarded Nobel Prize” from PEP Selective Compulsory English Book 1
摘要: 《普通高中英语课程标准(2017年版2025年修订)》提出“教–学–评”一体化理念,在目前高中英语阅读教学过程中,教学目标设置与评价脱节现象依然严重。逆向设计是“以终为始”的思想,将评价前置到目标设定之前,是教、学、评一致性的有效实施策略。同时,生成式人工智能(AIGC)对教学情境创设、知识点呈现以及即时反馈等方面带来新的支持。本文基于课例研究,“Tu Youyou Awarded Nobel Prize”阅读课为例,进行逆向设计与AIGC相结合的一致性教学尝试。结果发现二者结合可以更好地锁定教学目标,评价量表前置以及多方参与评价有利于以评助学,学生英语学科核心素养协调发展,这对一线教师开展阅读教学具有借鉴意义。
Abstract: The English Curriculum Standards for General Senior High Schools (2017 Edition, 2025 Revision) advocates the concept of “teaching-learning-assessment” integration. Nevertheless, a pronounced misalignment between instructional goal-setting and assessment persists in current senior high school English reading instruction. Rooted in the core principle of “beginning with the end in mind”, Backward Design positions assessment prior to the formulation of instructional objectives, representing an effective strategy for advancing teaching-learning-assessment alignment. Meanwhile, generative artificial intelligence (AIGC) delivers novel support for creating instructional scenarios, presenting knowledge points, providing real-time feedback, and other instructional dimensions. Adopting a lesson study approach, this paper explores the integrated application of Backward Design and AIGC in aligned instruction, with the reading lesson “Tu Youyou Awarded Nobel Prize” as the research case. The findings demonstrate that the integration of the two approaches enables more precise anchoring of instructional objectives. The front-loading of assessment rubrics and multi-stakeholder engagement in assessment promote assessment-supported learning and foster the coordinated development of students’ core competencies in English. This study bears practical implications for frontline teachers in implementing English reading instruction.
文章引用:蔡旺鑫, 帅至徽, 陈英. 基于逆向设计与AIGC融合的高中英语阅读“教–学–评”一体化的课例研究——以人教版选择性必修一“Tu Youyou Awarded Nobel Prize”为例[J]. 教育进展, 2026, 16(8): 830-839. https://doi.org/10.12677/ae.2026.1681699

参考文献

[1] 中华人民共和国教育部. 普通高中英语课程标准(2017年版2025年修订) [S]. 北京: 人民教育出版社, 2025.
[2] 万珊珊, 曹永胜. 基于逆向教学设计的小学英语“教-学-评”一体化设计研究[J]. 中国教育技术装备, 2026(5): 137-140, 145.
[3] Wiggins, G. and McTighe, J. (2017) Understanding by Design. 2nd Edition, Association for Supervision and Curriculum Development.
[4] 黄莉. 逆向教学设计促进初中英语教学评一体化的阅读课例研究[J]. 中学生英语, 2022(48): 80-82.
[5] 吴婧怡. 智能时代初中英语阅读逆向教学设计研究[J]. 英语教师, 2026, 26(2): 20-24.
[6] 何洪飞, 白玲. 基于逆向设计的高中英语单元整体教学设计[J]. 中小学外语教学, 2024, 47(11): 25-30.
[7] 郑鸥. 初中英语听说整合教学中“教-学-评”一体化逆向设计探究[J]. 中小学英语教学与研究, 2025(6): 69-72, 81.
[8] 杨榕. 基于逆向设计促进初中英语听说“教-学-评”一体化的课例研究[J]. 校园英语, 2024(22): 52-54.
[9] 王蔷, 李亮. 推动核心素养背景下英语课堂教-学-评一体化: 意义、理论与方法[J]. 课程·教材·教法, 2019, 39(5): 114-120.
[10] 李亮, 王蔷. 核心素养背景下高中英语“教-学-评”一体化: 理据与例析[J]. 天津师范大学学报(基础教育版), 2023, 24(4): 12-18.
[11] 程晓堂, 谢诗语. 英语“教-学-评”一体化的理念与实践[J]. 中小学外语教学(中学篇), 2023, 46(1): 1-8.
[12] 古敏. 基于逆向教学设计的高中英语“教-学-评”一体化教学设计[J]. 中小学外语教学(中学篇), 2024, 47(10): 20-24.
[13] Qaralleh, R. and Ahmed, S.N. (2024) Advancing Transnational Education by Integrating Artificial Intelligence Technology and Backward Design Principles in Technical English Curriculum. In: Naseer, F., Yu, C., Dulloo, R., Abdul Kader Jilani, M. and Shaheen, M., Eds., Bridging Global Divides for Transnational Higher Education in the AI Era, IGI Global, 101-120.
https://doi.org/10.4018/979-8-3693-7016-2.ch005
[14] Ruan, W., Qi, T., He, J., Sun, B. and Zheng, G. (2025) Backward Design-Driven Modular Retrieval-Augmented Generation Framework for Automated Instructional Design in Chinese Language Education. 2025 International Joint Conference on Neural Networks (IJCNN), Rome, 30 June 2025-5 July 2025, 1-8.
https://doi.org/10.1109/ijcnn64981.2025.11228999
[15] Nettles, B. (2026) Leveraging Artificial Intelligence to Facilitate Backward Design and Competency Scaffolding in Undergraduate Nursing Education. Journal of Professional Nursing, 64, 53-57.
https://doi.org/10.1016/j.profnurs.2026.02.013
[16] Ahn, J. (2025) Integrating ADDIE, Backward Design, and AI to Develop Curriculum Design Competencies in Preservice Special Education Teachers. Korean Educational Research Association, 63, 29-79.
https://doi.org/10.30916/kera.63.7.29
[17] 冷佳慧. 逆向设计视角下AI赋能英语读写结合教学实践探索[J]. 广东教育(综合版), 2026(6): 45-46.
[18] Hamzehloo, M., Azar, A.S. and Hamzehloo, M. (2026) Comparing Teacher and ChatGPT Feedback in EFL/ESL Writing. In: Sorayyaei Azar, A., Ghosh, R., Çela, E. and Flett, D., Eds., Bridging Global Divides for Transnational Higher Education in the AI Era, IGI Global Scientific Publishing, 143-164.
https://doi.org/10.4018/979-8-3373-5601-3.ch007
[19] Wetzler, E.L., Cassidy, K.S., Jones, M.J., Frazier, C.R., Korbut, N.A., Sims, C.M., et al. (2024) Grading the Graders: Comparing Generative AI and Human Assessment in Essay Evaluation. Teaching of Psychology, 52, 298-304.
https://doi.org/10.1177/00986283241282696
[20] Zhuang, Y., Zhao, R., Xie, Z. and Yu, P.L.H. (2025) Enhancing Language Learning through Generative AI Feedback on Picture-Cued Writing Tasks. Computers and Education: Artificial Intelligence, 9, Article 100450.
https://doi.org/10.1016/j.caeai.2025.100450
[21] Yuan, Z., Felice, M., Lan, Y. and Wang, Q. (2025) NLP and Generative AI for Language Learning and Assessment: Synergies between Research and Practice. In: Cristea, A.I., Walker, E., Lu, Y., Santos, O.C. and Isotani, S., Eds., Communications in Computer and Information Science, Springer, 300-307.
https://doi.org/10.1007/978-3-031-99267-4_39
[22] 金岚, 刘峻利. 人工智能辅助形成性评价应用于高中英语词汇教学的研究——以外研社必修3 Unit4 Science and technology为例[J]. 人文社会科学, 2025, 1(9): 49-54.
[23] 庄晓瑛. 生成式人工智能在高中英语写作教学中的融合应用实践——以ChatGPT为例[J]. 新课程评论, 2025(5): 89-98.
[24] 瞿锦雯, 叶丽新, 孙潘懿, 等. 大语言模型作文评价反馈质量的实证分析[J]. 现代教育技术, 2026, 36(3): 62-71.
[25] 胡立, 张放平. 人工智能时代外语教育教学评价与考核创新[J]. 惠州学院学报, 2022, 42(2): 118-123.
[26] 汪辰静. “评估连续统”在初中英语阅读教学中的运用[J]. 中小学英语教学与研究, 2023(2): 77-81.