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教育大模型应用现状、技术挑战及路径探析展望

The Current Progress, Technical Challenges and Future Prospects of Educational Large Models

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【作者】 熊余张璐吴超

【Author】 Xiong Yu;Zhang Lu;Wu Chao;Research Center for Artificial Intelligence and Smart Education, Chongqing University of Posts and Telecommunications;Research Center for Education Big Data, Chongqing University of Posts and Telecommunications;

【机构】 重庆邮电大学人工智能与智慧教育研究中心重庆市教育大数据研究中心

【摘要】 以DeepSeek为代表的大模型正在重塑教育生态系统,其在多场景、多用途和跨学科任务处理中的卓越能力,推动了知识生产方式、教育教学模式和未来学习形态的智能化转型。尽管教育大模型为教育领域带来了前所未有的机遇,但在实际应用中,它仍面临场景适配、数据采集、逻辑推理、资源生成和价值对齐等诸多挑战。本文综合分析了国内外20个典型教育大模型的功能特点,聚焦其价值体现、应用场景和底座构建,深入探讨了教育大模型的潜在技术实施路径,旨在为教育大模型的开发与应用提供创新思路,并为教育实践者提供实施框架,以促进教育大模型的有效应用和加快其发展。

【Abstract】 Large models represented by DeepSeek are reshaping the educational ecosystem. Their outstanding capabilities in handling multi-scenario, multi-purpose and interdisciplinary tasks are driving the intelligent transformation of knowledge production methods, teaching models, and learning paradigms. Although educational large models have brought unprecedented opportunities to education, their practical application still faces numerous challenges, including scenario adaptation, data collection, logical reasoning, resource generation, and value alignment. This paper provides a comprehensive analysis of the functional characteristics of 20 representative educational large models at home and abroad, with a focus on their value manifestation, application scenarios and foundational architecture. It also explores potential construction methods of educational large models. The aim of this study is to offer innovative ideas for the development and application of educational large models, and to provide an implementation framework for educational practitioners.

【基金】 国家自然科学基金面上项目“教师课堂教学投入的智能识别与可解释评价研究”(课题编号:62377007);重庆市高等教育教学改革研究重点项目“教育数字化转型背景下学生综合素质智能评价研究与探索”(课题编号:232073);重庆市教委科学技术研究重大项目“人机共生学习环境下可解释学习推荐技术研究”(课题编号:KJZD-M202400606);重庆市教委科学技术研究重大项目“面向复杂数据类型的科研平台全生命周期管理研发与实践”(课题编号:KJZD-M202300603);重庆市自然科学基金创新发展联合基金(重点)项目“教育元宇宙多模态虚拟教室智能生成理论与方法研究”(课题编号:CSTB2024NSCQ-LZX0133)
  • 【文献出处】 教师教育论坛 ,Teacher Education Forum , 编辑部邮箱 ,2025年02期
  • 【分类号】G434
  • 【下载频次】77
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