人工智能赋能高校教师教研能力提升的策略研究
Research on Strategies for Enhancing University Teachers’ Teaching and Research Capabilities Empowered by Artificial Intelligence
DOI: 10.12677/ces.2026.142090, PDF,    科研立项经费支持
作者: 万志龙*, 王 刚, 尤海鹏, 王昌英, 李 鹤:常州工学院理学院,江苏 常州;谢金楼:常州工学院经济与管理学院,江苏 常州
关键词: 数智赋能教研能力提升策略Mathematical Empowerment Teaching and Research Skills Strategies for Enhancement
摘要: 教学研究是高校教师探索教学的本质和规律所必须掌握的一项技能,也是高校教师实现个人专业成长和提升教育教学质量的重要手段。随着人工智能时代的到来,教学研究被赋予了新的意义和内涵。人工智能背景下高校教师教研能力的提升是促进教师专业化发展的有效途径。本文分析了人工智能赋能教师教研工作的必要性,剖析了教师教研能力存在的现状和困境,并从加强顶层设计、健全教研能力培训保障体系、加强数智化教学平台建设和完善教师信息化教学评价体系四个方面介绍了人工智能背景下高校教师教研能力的提升策略,并针对性讨论了AI赋能教研过程中可能面临的风险、挑战和伦理问题。
Abstract: Teaching research is a skill that college teachers must master to explore the nature and laws of teaching, and it is also an important means for college teachers to realize their personal professional growth and improve the quality of education and teaching. With the arrival of the era of artificial intelligence, teaching research has been given a new meaning and connotation. The improvement of college teachers’ teaching and research ability in the context of artificial intelligence is an effective way to promote teachers’ professional development. This paper analyzes the necessity of artificial intelligence to empower teachers’ teaching and research work, analyzes the status quo and dilemma of teachers’ teaching and research ability, and introduces the strategies for improving the teaching and research ability of college teachers under the background of artificial intelligence in the four aspects of strengthening the top-level design, improving the training and guarantee system of teaching and research ability, strengthening the construction of the digital teaching platform, and perfecting the teachers’ informatization teaching evaluation system. Additionally, it addresses the potential risks, challenges, and ethical issues that may arise during the AI-empowered teaching research process.
文章引用:万志龙, 谢金楼, 王刚, 尤海鹏, 王昌英, 李鹤. 人工智能赋能高校教师教研能力提升的策略研究[J]. 创新教育研究, 2026, 14(2): 18-25. https://doi.org/10.12677/ces.2026.142090

参考文献

[1] 张应腾, 徐晶晶. AI大模型赋能高等教育的路径探索[J]. 科教文汇, 2025(12): 1-5.
[2] 朱洪涛, 黄小林, 杨子泉, 等. 人工智能背景下高校教师教学能力提升策略研究[J]. 广西开放大学学报, 2025, 36(2): 12-17.
[3] 安晓春, 张旭. 基于多模态信息融合的个性化教学策略研究[J]. 计算机技术与发展, 2025, 35(2): 200-204.
[4] 李雪. 数智赋能校本教研的现实困境及其破解[J]. 教学与管理, 2025(10): 20-23.
[5] 杨冬. 人工智能变革工程教育: 应用场景与功能向度[J]. 西北工业大学学报(社会科学版), 2025(4): 60-66.
[6] 左腾, 吴彤, 宋小伟, 等. 人工智能赋能高等教育转型的困境与路径探索[J]. 高教发展与评估, 2025, 41(4): 30-41+130-131.
[7] 汪超. 高校青年教师教研能力提升: 现实困境与实现路径[J]. 煤炭高等教育, 2022, 40(2): 76-81.