[1]李凤英,龙紫阳.从自适应学习推荐到自适应学习牵引模型——“智能+”教育时代自适应学习研究取向[J].远程教育杂志,2020,(06):022-31.[doi:10.15881/j.cnki.cn33-1304/g4.2020.06.003]
 Li Fengying,Long Ziyang.From the Model of Adaptive Learning Recommendation to the One of Adaptive Learning Pulling: The Research Trend of Adaptive Learning in the Age of “Intelligence + Education”[J].Distance Education Journal,2020,(06):022-31.[doi:10.15881/j.cnki.cn33-1304/g4.2020.06.003]
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从自适应学习推荐到自适应学习牵引模型——“智能+”教育时代自适应学习研究取向()
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《远程教育杂志》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2020年06期
页码:
022-31
栏目:
前沿探索
出版日期:
2020-11-22

文章信息/Info

Title:
From the Model of Adaptive Learning Recommendation to the One of Adaptive Learning Pulling: The Research Trend of Adaptive Learning in the Age of “Intelligence + Education”
作者:
李凤英; 龙紫阳
1.上海交通大学 继续教育学院; 2.上海交通大学 高等教育研究院,上海 200240
Author(s):
Li Fengying; Long Ziyang
1.School of Continuing Education, Shanghai Jiaotong University; 2.Graduate School of Education, Shanghai Jiaotong University, Shanghai 200240
关键词:
自适应学习自适应学习系统学习推荐学习牵引学习分析教育4.0“智能+”教育
Keywords:
Adaptive Learning Adaptive Learning System Learning Recommendation Learning Pulling Study Analysis Education 4.0 Intelligence + Education
分类号:
G420
DOI:
10.15881/j.cnki.cn33-1304/g4.2020.06.003
文献标志码:
A
摘要:
伴随着人工智能、大数据、学习分析技术等在教育中的深度应用,自适应学习成为在线教育新的研究热点。近年来的研究表明,智能技术促进自适应学习的主要方式,在于构建并应用自适应学习推荐模式。学习推荐技术是自适应学习的关键,它依赖于大数据与学习分析;但在学习分析过程中会给学习者带来隐私泄露等风险。基于此,区别于目前常用的自适应学习推荐技术,提出了具有数据隐私保护功能的自适应学习牵引模型,在应用过程中分为学习数据分析、学习需求展示筛选、隐私保护防御、智能代理、学习牵引和牵引结果展示等六个阶段。这也预示着,在“智能+教育”时代促进自适应学习研究的新取向,主要表现在认知突破、技术突破、情感突破、“两张皮”突破和隐私保护突破等五个方面,这些既丰富了自适应学习的内涵与外延,也有助于推进自适应学习理论与技术的发展。
Abstract:
With the deep application of artificial intelligence, big data and learning analysis in education, adaptive learning has been one new research hotspot of online education. Recent years’ research shows that the main way that smart technology promotes adaptive learning is the construction and application of recommendation pattern of adaptive learning. Learning recommendation is the key technique of adaptive learning, which depends on big data and learning analysis. However, learning analysis brings the risk of privacy leakage to learners. Based on it and different from current adaptive learning recommendation, adaptive learning pulling model with privacy protection is put forward. The model comprises learning data analysis, learning requirement listing and choosing, privacy protection and defense, smart agent, learning pulling and pulling data showing. The reform also predicts that in the era of smart plus education, the new trend of adaptive learning research is composed of cognitive breakthrough, technology breakthrough, emotion breakthrough, discipline gap breakthrough and privacy risk breakthrough. They enrich the connotation and extension of adaptive learning, and make a progress for the theory and technology of adaptive learning.

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备注/Memo

备注/Memo:
基金项目:本文系国家社科基金项目“基于贝叶斯方法的社会网络大数据使用与隐私保护平衡机制研究”(编号:16BGLOO3);国家自然科学基金“基于位置的认证协议研究”(编号:61170227);教育部人文社科项目“基于数字认证的MOOC诚信机制研究”(编号:14YJA880033)的阶段性研究成果。
更新日期/Last Update: 1900-01-01