[1]冷 静,徐浩鑫.探析深度学习表征的一种新方法:社会认知网络特征(SENS)[J].远程教育杂志,2020,(03):086-94.[doi:10.15881/j.cnki.cn33-1304/g4.2020.03.009]
 Leng Jing,Xu Haoxin.A New Method of Deep Learning Representation: Social Epistemic Network Signature[J].Distance Education Journal,2020,(03):086-94.[doi:10.15881/j.cnki.cn33-1304/g4.2020.03.009]
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探析深度学习表征的一种新方法:社会认知网络特征(SENS)()
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《远程教育杂志》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2020年03期
页码:
086-94
栏目:
学习新论
出版日期:
2020-05-15

文章信息/Info

Title:
A New Method of Deep Learning Representation: Social Epistemic Network Signature
作者:
冷 静; 徐浩鑫
1.华东师范大学 教育学部 教育信息技术学系;2.上海数字化教育装备工程技术研究中心 华东师范大学,上海 200062
Author(s):
Leng Jing; Xu Haoxin
1.Department of Educational Information Technology, Faculty of Education, East China Normal University; 2. Shanghai Engineering Technology Research Center of Digital Education Equipment, East China Normal University, Shanghai 200062
关键词:
深度学习认知网络分析社会网络分析社会认知网络特征SENS
Keywords:
Deep Learning Epistemic Network Analysis Social Network Analysis Social Epistemic Network SignatureSENS
分类号:
G420
DOI:
10.15881/j.cnki.cn33-1304/g4.2020.03.009
文献标志码:
A
摘要:
近年来,深度学习在教育领域越来越受到重视,它被划分为三大维度:认知领域、人际领域和自我领域。现有基于问卷、测试题和访谈等方式进行的学习效果分析,难以满足人们对于深度学习中动态、过程和综合的分析需求。作为一种新的研究方法,社会认知网络特征(SENS)结合了社会网络分析(SNA)和认知网络分析(ENA),能够很好地对深度学习的三个领域进行分析。本研究首先通过对原有的SENS方法进行改进,提出适合深度学习的SENS方法的一般步骤,并对每个步骤进行详细的介绍;接着通过两个典型案例介绍了如何利用SENS来促进深度学习,并将深度学习和在线协作数据分析相结合;最后给出了应用SENS的一些经验与建议,以期为今后研究深度学习提供新的思路和方法。
Abstract:
In recent years, deep learning has received more and more attention in the field of education, which is divided into three dimensions: cognitive, interpersonal and intrapersonal aspects. Current learning effect analysis are based on questionnaires, test questions and interviews, which are difficult to meet people’s demands for dynamic, procedural and comprehensive analysis in deep learning. As a new research method, social epistemic network signature (SENS) combines social network analysis (SNA) and cognitive network analysis (ENA) to analyze the three areas of deep learning. This study first modifies original SENS method, and puts forward the general steps of SENS method which was suitable for deep learning, with each step be explained in detail. Then, it introduces how SENS can be used to promote deep learning and combine deep learning with online collaborative data analysis through two typical cases. Finally, some experience and suggestions on the application of SENS are given in order to provide new ideas and methods for future researchers to carry out deep learning research.

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备注/Memo

备注/Memo:
基金项目:本文系2017年度中央高校基本科研业务费项目华东师范大学人文社会科学青年预研究项目“互联网+环境下的学习焦虑如何克服?——基于大学生语言学习策略分析”(项目编号:2017ECNU-YYJ047)的研究成果。
更新日期/Last Update: 1900-01-01