[1]孙发勤,冯 锐.编程教育中的智能导师系统:架构、设计与应用[J].远程教育杂志,2020,(01):061-68.[doi:10.15881/j.cnki.cn33-1304/g4.2020.01.006]
 Sun Faqin,Feng Rui.Intelligent Tutor System in Programming Education: Architecture, Design and Application[J].Distance Education Journal,2020,(01):061-68.[doi:10.15881/j.cnki.cn33-1304/g4.2020.01.006]
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编程教育中的智能导师系统:架构、设计与应用()
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《远程教育杂志》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2020年01期
页码:
061-68
栏目:
前沿探索
出版日期:
2020-01-07

文章信息/Info

Title:
Intelligent Tutor System in Programming Education: Architecture, Design and Application
作者:
孙发勤; 冯 锐
1.扬州大学 新闻与传媒学院,江苏扬州 225009;2.南京农业大学 公共管理学院,江苏南京 210095
Author(s):
Sun Faqin; Feng Rui
1.School of Journalism and Communication, Yangzhou University, Yangzhou Jiangsu 225009;2.College of Public Administration, Nanjing Agricultural University, Nanjing Jiangsu 210095
关键词:
智能导师系统编程教育K-12体系架构计算思维学习分析
Keywords:
Intelligent Tutoring System Programming Education K-12 ArchitectureComputational ThinkingLearning Analysis
分类号:
G420
DOI:
10.15881/j.cnki.cn33-1304/g4.2020.01.006
文献标志码:
A
摘要:
新一轮科技革命和产业革命对教育提出了新的要求,在K-12阶段(中小学)设置编程相关课程成为大势所趋,编程智能导师系统成为解决编程师资匮乏及满足个性化学习的最佳方案。由于编程教育需要更多的关注认知过程、情感支持及认知过程,因此,编程教育智能导师系统的体系架构除了包含领域模型、学生模型、评估模型等常规模型外,还应该包含追踪模型、适应模型、媒体模型。编程智能导师系统模型的设计采用了知识图谱、学习者画像、知识追踪、多模态学习感知、深度学习等相关技术。通过可视化编程、协作编程、开放接口、智能导师及智能学伴等五方面重点实施,可实现编程教育的可视化、协作化、智能化、个性化学习,提高编程智能导师对编程课堂的课前、课中及课后三个环节的教学支持。
Abstract:
The new round of scientific and technological revolution and industrial revolution have put forward new requirements for education. It is a general trend to set up programming-related courses at K-12 (primary and secondary school level), and the intelligent programming mentor system has become the best solution to solve the shortage of programming teachers and meet personalized learning. Because programming education needs more attention to cognitive processes, emotional support, and cognitive processes, the architecture of the intelligent mentor system for programming education should include tracking models, adaptations models and media models, in addition to conventional models such as domain models, student models, and evaluation models. The design of the programming intelligent tutoring system model uses related technologies such as knowledge map, learner portrait, knowledge tracking, multi-modal learning perception, and deep learning. Through the five key implementations of visual programming, collaborative programming, open interfaces, intelligent tutoring and intelligent learning partners, it can realize the visualization, collaborative, intelligent, and personalized learning of programming education, and improve the pre-class, during and after class can be improved.

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备注/Memo

备注/Memo:
基金项目:本文系教育部人文社会科学研究一般项目“大规模在线开放课程学习行为分析研究”(项目编号:15YJC880065);江苏高校哲学社会科学研究项目“在线网络课程学习行为分析与应用研究”(项目编号:2015SJB809)成果。
更新日期/Last Update: 1900-01-01