基于智适应学习系统的小学语文 个性化教学路径探究
Exploring the Personalized Teaching Path of Primary School Chinese Based on an Intelligent Adaptive Learning System
摘要: 智适应学习系统在小学语文教学中存在“技术中心主义”迷思,即把复杂的语文学习简化为可量化的知识点训练,遮蔽了文本细读的温度与意义生成。其原因在于相关研究多集中于理工学科,系统设计缺乏对语文学科人文特质的关照。针对上述问题,基于叶圣陶“教是为了达到不需要教”、王荣生“教学内容的确定性与学生理解的差异性”、维果茨基“最近发展区”及人本主义学习理论,构建一种人机协同的个性化教学路径。具体包括课前借助系统进行前置检测、分层规划与资源推送,实现学情诊断与路径规划;课中通过分层授课、实时互动与动态调整,实现深度互动与动态生成;课后依托个性化巩固、精准评价与复盘优化,实现分层拓展与长效追踪。该路径明确智适应系统的辅助定位——赋能教师精准识别学生的“最近发展区”,而非替代教师判断,从而在班级授课制下实现规模化教育与个性化培养的统一。
Abstract: The intelligent adaptive learning system harbors a myth of “techno centrism” in primary school Chinese teaching, which simplifies the complex process of Chinese learning into quantifiable knowledge-point drills, thereby obscuring the warmth and meaning-making inherent in close reading of texts. This issue stems from the fact that relevant studies are predominantly concentrated in science and engineering disciplines, leading to system designs that lack sufficient consideration for the humanistic qualities of the Chinese subject. To address these problems and grounded in Ye Sheng Tao’s concept that “teaching is for the purpose of achieving the state where teaching is no longer needed”, Wang Rongsheng’s theory on “the certainty of teaching content and the diversity of student understanding”, Vygotsky’s “Zone of Proximal Development” (ZPD), and humanistic learning theory, this study constructs a human-machine collaborative personalized teaching path. Specifically, this path includes pre-class pre-assessment, tiered planning, and resource recommendation via the system to achieve learning diagnosis and path planning; in-class tiered instruction, real-time interaction, and dynamic adjustment to achieve deep interaction and dynamic generation; and post-class personalized consolidation, precise evaluation, and review optimization to achieve tiered expansion and long-term tracking. This path clarifies the auxiliary role of the intelligent adaptive system—empowering teachers to accurately identify students’ “Zone of Proximal Development” rather than replacing teachers’ professional judgment—thereby achieving the unity of large-scale education and personalized cultivation within the class-based instruction system.
文章引用:李慧, 黄媛媛. 基于智适应学习系统的小学语文 个性化教学路径探究[J]. 教育进展, 2026, 16(7): 692-699. https://doi.org/10.12677/ae.2026.1671422

参考文献

[1] 邓宏宝, 顾彬彬. 个性化教学: 内涵、价值与实现路径[J]. 中国教育学刊, 2021(8): 65-69.
[2] 辛涛, 姜宇. 基于核心素养的教育改革: 政策、理论与实践[M]. 北京: 北京师范大学出版社, 2019: 156-158.
[3] 李伟. 个性化教学的教师之维与建构[J]. 教育研究, 2013, 34(5): 134-138.
[4] 中共中央、国务院印发《中国教育现代化2035》[J]. 中华人民共和国教育部公报, 2019(Z1): 2-5.
[5] 中华人民共和国教育部. 义务教育语文课程标准(2022年版) [S]. 北京: 北京师范大学出版社, 2022: 3, 45.
[6] 卢文辉. AI + 5G视域下智适应学习平台的内涵、功能与实现路径——基于智能化无缝式学习环境理念的构建[J]. 远程教育杂志, 2019, 37(3): 38-46.
[7] 牟智佳, 岳婷, 朱陶. 人机协同视域下基于认知智能大模型的个性化学习设计研究[J]. 电化教育研究, 2025, 46(2): 80-87.
[8] 李海峰, 王炜. 人工智能支持下的智适应学习模式[J]. 中国电化教育, 2018(12): 88-95, 112.
[9] 刘胤衡. AI助教进课堂让语文课趣味盎然[N]. 中国青年报, 2025-12-23(006).
[10] 张秀玲. 基于学科知识图谱的初中语文智适应学习实践探索[J]. 教育传播与技术, 2022(S1): 50-54.
[11] 高承海, 党宝宝, 王冰洁, 等. 人工智能的语言优势和不足: 基于大语言模型与真实学生语文能力的比较[J]. 心理学报, 2025, 57(6): 947-973.
[12] 叶圣陶. 叶圣陶语文教育论集[M]. 北京: 教育科学出版社, 2015: 152.
[13] 王荣生. 语文教学内容的确定性及其面临的问题[J]. 语文学习, 2009(9): 5-7.
[14] (苏)维果茨基. 维果茨基全集: 第6卷 教育心理学[M]. 龚浩然, 主编. 合肥: 安徽教育出版社, 2016: 473.
[15] Corbett, A.T. and Anderson, J.R. (1995) Knowledge Tracing: Modeling the Acquisition of Procedural Knowledge. User Modelling and User-Adapted Interaction, 4, 253-278. [Google Scholar] [CrossRef
[16] Embretson, S.E. and Reise, S.P. (2000) Item Response Theory for Psychologists. Lawrence Erlbaum Associates, 1-30.
[17] 周琴, 文欣月. 从自适应到智适应: 人工智能时代个性化学习新路径[J]. 现代教育管理, 2020(9): 89-96.
[18] Krashen, S.D. (1985) The Input Hypothesis: Issues and Implications. Longman, 20-30.
[19] 束夏梅. “数字眼”引发教学“蝶变” [N]. 中国教育报, 2025-03-17(004).
[20] 刘丽. 龙岗“数智教师”加速上线, “AI + 教育”全面赋能课堂创新[EB/OL]. 2025-03-05.
https://www.dutenews.com/n/article/10298328?r=1, 2026-05-17.
[21] 马爱格. 小学语文差异化教学的实施路径与效果评估[N]. 中国教师报, 2026-01-14(013).
[22] 中新网广东. 海珠区教育局正式接入上线满血版DeepSeek大模型! [EB/OL]. 2025-02-28.
https://www.gd.chinanews.com.cn/wap/2025/2025-02-28/440612.shtml, 2026-06-08.
[23] 武汉大学第一附属小学. AI赋能新课堂, 数据助力新成长——武大一附小五年级语文教研组展示课成果分享[EB/OL]. 2025-11-20.
https://fuxiao.whu.edu.cn/info/1261/27331.htm, 2026-06-08.
[24] 王荣生. 从教学内容角度看《少年闰土》的教学价值[J]. 语文建设, 2010(11): 13-16.
[25] 甄卓, 蒋颖妍, 刘盾. 广州市越秀区小北路小学: AI为单元教学改革添动能[N/OL]. 中国教育新闻网.
http://m.jyb.cn/rmtzcg/xwy/wzxw/202601/t20260105_2111433665_wap.html, 2026-01-05.
[26] 应用为王 智绘未来|人工智能赋能教育交流展示活动在市南区成功举行[EB/OL]. 2025-10-27.
https://finance.sina.com.cn/tjhz/2025-10-27/doc-infvinsm5120356.shtml, 2026-06-08.
[27] 育才二小. 数据解码课堂! 让AI成为教师专业成长“好帮手” [EB/OL]. 2025-12-27.
https://mp.weixin.qq.com/s?__biz=MzA4MTQwNDQzNQ==&mid=2650272456&idx=1&sn=c42ae6a1ca381828e38dba56fe1dbb96, 2026-06-08.