基于社会网络的高等教育智能化适应性辅导

IF 1.4 4区 计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS
C. Troussas, Akrivi Krouska, Efthymios Alepis, M. Virvou
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引用次数: 10

摘要

社交媒体已经成为人们之间交流的工具,其中大多数属于年轻一代。因此,在教育领域利用它们可以促进学生和教师之间的交流与合作。此外,使用更多的教学工具(如评估和适应性)来扩展它们,可以进一步改善学习成果。鉴于此,本文提出了基于Facebook的编程学习智能辅导应用i-LearnC#。这款Facebook应用程序扩展了Facebook平台的功能,可以用作综合辅导系统。特别是,i-LearnC#体现了一个智能的虚拟教练,提供个性化的建议,覆盖学生的知识空白,并解决对未知学习概念的疑问。在学生的评估方面,i- learn#应用了修订后的Bloom分类法,并通过虚拟教练为他们提供个性化的帮助。最后,i-LearnC#采用聚类分析向学生推荐最佳合作小组。i- learn#使用一个众所周知的框架、统计假设检验和系统日志文件进行评估。结果表明,i- learn#作为一种自适应的智能社会学习环境,在教育上对高等教育学生有益,促进了计算机教育的有效学习和教学,取得了很高的接受率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Intelligent and adaptive tutoring through a social network for higher education
ABSTRACT Social Media have become a tool for communication among people, the majority of whom belong to the younger generation. Hence, exploiting them in the educational field can promote communication and collaboration among students and instructors. Moreover, expanding them with more pedagogical tools, such as assessments and adaptivity, can improve further the learning outcomes. In view of the above, this paper presents i-LearnC#, an intelligent tutoring application over Facebook, for learning programming. This Facebook app extends the capabilities of Facebook platform to be used as an integrated tutoring system. In particular, i-LearnC# embodies an intelligent Virtual Coach offering individualised advice, covering students’ knowledge gaps and solving queries on unknown learning concepts. Regarding students’ assessment, i-LearnC# applies the Revised Bloom Taxonomy and delivers personalised assistance to them through the Virtual Coach. Finally, i-LearnC# employs cluster analysis for recommending the optimal groups for collaboration to students. i-LearnC# was evaluated using a well-known framework, the statistical hypothesis test and system's log files. The results are very promising, showing that i-LearnC# has been educationally beneficial to students in higher education promoting effective learning and teaching of computing education and achieving high acceptance rate as an adaptive intelligent social learning environment.
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来源期刊
New Review of Hypermedia and Multimedia
New Review of Hypermedia and Multimedia COMPUTER SCIENCE, INFORMATION SYSTEMS-
CiteScore
3.40
自引率
0.00%
发文量
4
审稿时长
>12 weeks
期刊介绍: The New Review of Hypermedia and Multimedia (NRHM) is an interdisciplinary journal providing a focus for research covering practical and theoretical developments in hypermedia, hypertext, and interactive multimedia.
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