人工智能人才培养的模式、资源与平台：围绕新形态科教案例的结构重组

李莎莎; 李骁; 周丽涛; 李莹

您当前的位置：

首页 >

文章列表页 >

人工智能人才培养的模式、资源与平台：围绕新形态科教案例的结构重组

AI人才培养 | 更新时间：2023-12-05

- 人工智能人才培养的模式、资源与平台：围绕新形态科教案例的结构重组
- Mode, Resources, and Platforms for Artificial Intelligence Talent Training: Structural Reorganization Around New Forms of Science and Education Cases
- 科教发展研究 2023年3卷第3期页码：106-122
- 作者机构：
  
  1.国防科技大学计算机学院
  2.国防科技大学军事职业教育技术服务中心
  3.头歌教学研究中心
  4.北京航空航天大学计算机学院
- 作者简介：
  
  李莎莎，国防科技大学计算机学院副教授，博士；研究领域为自然语言处理、知识图谱。
  李骁，国防科技大学军事职业教育技术服务中心副研究员，博士；研究领域为教育数据分析、人工智能教育应用。
  周丽涛，头歌教学研究中心副主任，硕士；研究领域为计算机应用。
  李莹，北京航空航天大学计算机学院副教授，博士；研究领域为精准教育理论研究、虚实融合平台构建。
- 基金信息：
  
  科技创新2030 —“新一代人工智能”重大项目(2021ZD0110700)
- DOI：
  中图分类号：
扫描看全文
李莎莎，李骁，周丽涛，等.人工智能人才培养的模式、资源与平台：围绕新形态科教案例的结构重组[J].科教发展研究，2023，3（3）：106-122.

LI Shasha, LI Xiao, ZHOU Litao, et al. Mode, Resources, and Platforms for Artificial Intelligence Talent Training: Structural Reorganization Around New Forms of Science and Education Cases[J]. Journal of Science, Technology and Education Studies, 2023, 3(3): 106-122.
李莎莎，李骁，周丽涛，等.人工智能人才培养的模式、资源与平台：围绕新形态科教案例的结构重组[J].科教发展研究，2023，3（3）：106-122. DOI：

LI Shasha, LI Xiao, ZHOU Litao, et al. Mode, Resources, and Platforms for Artificial Intelligence Talent Training: Structural Reorganization Around New Forms of Science and Education Cases[J]. Journal of Science, Technology and Education Studies, 2023, 3(3): 106-122. DOI：

摘要

近年来，人工智能技术的加速发展引领了新一轮的技术革命。一方面，其影响渗透到各行各业，对现存产业结构产生颠覆性的影响；另一方面，人工智能技术竞争将涉及技术、政治、经济等诸多领域，成为大国博弈的下一个战场，引发国际技术格局与制度的变迁。人工智能人才培养是在这场大变革中制胜的重要一环。人工智能的发展性与复杂性，决定了其“科教融合”“以实践为中心”的内在要求，以实践项目为主体的科教案例成为人工智能人才培养的重要载体。作为重要的教育教学资源，科教案例应具备创新性、前沿性和挑战度。文章提出了新形态科教案例的结构模型及支撑新形态科教案例开发、运行、应用的全生命周期的一体化平台，并对促进人工智能人才培养过程中更广范围的科教案例开放与共享提出意见和建议。

Abstract

In recent years, the rapid development of artificial intelligence technology has led to a new round of technological revolution. On the one hand, its impact permeates various industries and has a disruptive impact on the existing industrial structure; on the other hand, the competition in artificial intelligence technology will involve many fields such as technology, politics, economy, etc., becoming the next battlefield of the great powers’ game, triggering changes in the international technological landscape and institutions. Artificial intelligence talent training is important for winning in this major transformation. The development and complexity of artificial intelligence make it necessary that its talent training integrates science and education and is "practice centered". Science and education cases with practical projects as the main body have become an important carrier for artificial intelligence talents training. As an important educational and teaching resource, science and education cases should be innovative, cutting-edge, and challenging. This article proposes a structural model for new forms of science and education cases and an integrated platform that supports the entire lifecycle of the development, operation, and application of new forms of science and education cases. It also provides opinions and suggestions on promoting the opening and sharing of a wider range of science and education cases in the process of cultivating artificial intelligence talents.

关键词

人工智能人才培养科教案例结构模型一体化平台

Keywords

Artificial Intelligence Talent TrainingScience and Education CasesStructural ModelIntegrated Platform

references

王淑营，杨燕，李天瑞，等.“科教+思政”融合的人工智能拔尖人才培养模式探索[J].计算机教育，2023(6):1.

WANG Shuying, YANG Yan, LI Tianrui, et al. An Exploration of Artificial Intelligence Top Talents Cultivation Mode through the Integration of Science, Education, Ideology and Politics[J]. Computer Education, 2023(6):1 (in Chinese).

张波，徐立，潘建国，等.基于产教融合的新工科人工智能教育人才实践能力培养体系建设[J].计算机教育，2023(5):1.

ZHANG Bo, XU Li, PAN Jianguo, et al. Construction of Artificial Intelligence Practical Ability Cultivation System for Emerging Engineering Based on Industry–Education Integration[J]. Computer Education, 2023(5):1 (in Chinese).

郑庆华，武乐飞，董博，等. 面向新一代人工智能的科教资源管理体系：软件定义范式和协同共建机制[J]. 科教发展研究，2022，2(4):31.

ZHENG Qinghua, WU Yuefei, DONG Bo, et al. A New Generation of AI Based Science and Education Resource Management System: A Software-Defined Paradigm and Collaborative Co-construction Mechanism[J]. Journal of Science, Technology and Education Studies, 2022, 2(4):31 (in Chinese).

刘三女牙.人工智能与教育双向赋能的人才培养模式创新和体系重构[J].科教发展研究，2022，2(2):50.

LIU Sannyuya. Innovation of Talent Training Mode and Reconstruction of the Supporting System by Bidirectional Empowerment of Artificial Intelligence and Education[J]. Journal of Science, Technology and Education Studies, 2022, 2(2):50 (in Chinese).

吴文峻.面向智慧教育的学习大数据分析技术[J].电化教育研究，2017，38(6):92.

WU Wenjun. Learning Analytics for Smart Education[J]. e-Education Research, 2017, 38(6):92 (in Chinese).

CHI M T H. Active-Constructive-Interactive: A Conceptual Framework for Differentiating Learning Activities[J]. Topics in Cognitive Science, 2009, 1(1):73-105.

CHI M T H, WYLIE R. The ICAP Framework: Linking Cognitive Engagement to Active Learning Outcomes[J]. Educational Psychologist, 2014, 49(4):219-243.

李培根，郭卉.工程教育需要实现多重超越[J].科教发展研究，2023，3(1):2-15.

LI Peigen, GUO Hui. Engineering Education Needs to Achieve Multiple Transcendence[J]. Journal of Science, Technology and Education Studies, 2023, 3(1):2-15 (in Chinese).

浏览量

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

暂无数据