[1]牟智佳.“人工智能+”时代的个性化学习理论重思与开解[J].远程教育杂志,2017,(03):022-30.[doi:10.15881/j.cnki.cn33-1304/g4.2017.03.003]
 Mou Zhijia.The Reconsideration and Solution of Personalized Learning Theory in the Era of “Artificial Intelligence Plus”[J].Distance Education Journal,2017,(03):022-30.[doi:10.15881/j.cnki.cn33-1304/g4.2017.03.003]
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“人工智能+”时代的个性化学习理论重思与开解()
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《远程教育杂志》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2017年03期
页码:
022-30
栏目:
前沿探索
出版日期:
2017-05-15

文章信息/Info

Title:
The Reconsideration and Solution of Personalized Learning Theory in the Era of “Artificial Intelligence Plus”
作者:
牟智佳
江南大学 教育信息化研究中心,江苏无锡 214122
Author(s):
Mou Zhijia
Research Center for Educational Informatization, Jiangnan University, Wuxi Jiangsu 214122
关键词:
“人工智能+”时代人工智能技术学习行为个性化学习掌握学习教育云服务
Keywords:
“Artificial intelligence plus” era Artificial intelligence technology Learning behavior personalized learning Mastery learning Educational cloud service
分类号:
G420
DOI:
10.15881/j.cnki.cn33-1304/g4.2017.03.003
文献标志码:
A
摘要:
个性化学习是技术与教育深度融合的高级阶段表现形式,以机器学习和深度学习为关键支撑的人工智能技术的回归对个性化学习进行了重塑和再造。在“人工智能+”时代下,个性化学习应具备“一个中心,三个导向”的理论支撑,即以学习者为中心,以目标、过程和评价为导向。个性化学习的应然特征包括心智分析性、服务差异性和目标导向性三个层面。个性化学习首先要把握学习者的心智特征,在此基础上为其全学习过程提供符合其个性需求的内容、活动、路径和评价,最终在学习目标上实现自我导向的有意义学习,在成长目标上培育自主发展核心素养。个性化学习服务的确立应当以基于人工智能技术的智能教育云服务平台为支持,以需求本位的个性化学习内容推送、能力本位的个性化学习路径生成和掌握本位的个性化学习评价为服务方向。
Abstract:
Personalized learning is the advanced stage of the deep integration of technology and education. The return of artificial intelligence technology, which regards machine learning and deep learning as the key support, has remodeled and reconstructed personalized learning. In the era of “artificial intelligence”, personalized learning should have the theoretical support of “one center and three orientations” that is learner centered and the goal, the process and the evaluation oriented. The characteristic of personalized learning include three levels which include mind analysis, service differentiation and goal orientation. It’s essential to grasp learner’s mind characteristic for personalized learning. Based on that, the content, activities, path and evaluation that meet individual needs should be provided for the whole learning process. Ultimately, we hope to achieve self-oriented meaningful learning in the learning objective and cultivate the core literacies of independent development in the growing objective. The establishment of personalized learning service should include the support of intelligent education cloud service platform which is based on artificial intelligence technology and three service directions which contain personalized learning content recommendation based on demand, personalized learning path generation based on competency, personalized learning evaluation based on mastery.

相似文献/References:

[1]菅保霞,姜 强,赵 蔚,等.大数据背景下自适应学习个性特征模型研究 ——基于元分析视角[J].远程教育杂志,2017,(04):087.[doi:10.15881/j.cnki.cn33-1304/g4.2017.04.009]
 Jian Baoxia,Jiang Qiang,Zhao Wei,et al.Research on Students’ Personality Traits Modeling in Adaptive Learning on the Background of Big Data:Based on the Perspective of Meta-analysis[J].Distance Education Journal,2017,(03):087.[doi:10.15881/j.cnki.cn33-1304/g4.2017.04.009]
[2]李欢冬,樊 磊.“可能”与“不可能”:当前人工智能技术教育价值的再探讨——《高等学校人工智能创新行动计划》解读之一[J].远程教育杂志,2018,(05):038.[doi:10.15881/j.cnki.cn33-1304/g4.2018.05.006]
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备注/Memo

备注/Memo:
基金项目:本文系中央高校基本科研业务费专项资金资助课题“互联网+”环境下的理解性学习与认知研究(课题编号:2017JDZD07)的研究成果。
更新日期/Last Update: 2017-05-15