Journal of Guangxi Teachers Education University (Philosophy and Social Sciences Edition) ›› 2023, Vol. 59 ›› Issue (4): 68-79.doi: 10.16088/j.issn.1001-6597.2023.04.007

Previous Articles     Next Articles

Artificial Intelligence Enabling Personalized Learning: Implications, Mechanisms and Pathways

XU Feng-hua, HU Xian-jin   

  1. School ofEducation, Central China Normal University, Wuhan 430079, China
  • Received:2023-05-14 Online:2023-07-15 Published:2023-08-10

Abstract: Personalized learning based on artificial intelligence technology is the demand of the times to adapt to the future society and promote individual development. Based on the learning behavior data of learners' personality characteristics, it applies massive data analysis and model algorithm recommendation to carry out intelligent choice, decision and service so as to set learning path, provide learning resources, create interactive situation and give real-time feedback for learners; it realizes personalized learning objectives through synchronous adjustment and optimization of secondary supply of learning data. Such is the closed-loop operating mechanism of artificial intelligence technology enabling personalized learning. By combing the dynamic hierarchical relationship of learners' basic data, intelligent decision making and personalized service, and learning model construction, this paper proposes the practical approaches ofits enabling personalized learning: 1) to accurately draw the digital portrait of learners by data mining, and guide quantitative self and quantitative learning; 2) to adapt management system through the recommendation algorithm and the learning of artificial intelligence for intelligent decision-making and personalized service;3) to build a humanistic ecosystem of deep learning through machine learning for a shift from superficial to deep.

Key words: artificial intelligence technology, personalized learning, digital portrait, machine learning, ChatGPT

CLC Number:  G43
[1] 中华人民共和国教育部. 教育部关于印发《教育信息化“十三五”规划》的通知[EB/OL]. (2016-06-07)[2023-05-09]. http://www.moe.gov.cn/srcsite/A16/s3342/201606/t20160622_269367.html.
[2] 中华人民共和国教育部.教育部关于印发《教育信息化2.0行动计划》的通知[EB/OL]. (2018-04-18)[2023-05-09]. http://www.moe.gov.cn/srcsite/A16/s3342/201804/t20180425_334188.html.
[3] 中华人民共和国教育部. 义务教育课程方案(2022年版)[M]. 北京: 北京师范大学出版社, 2022.
[4] 师亚飞, 彭红超, 童名文. 基于学习画像的精准个性化学习路径生成性推荐策略研究[J]. 中国电化教育, 2019(5): 84-91.
[5] 李香勇, 左明章, 王志锋. 数据驱动的自适应学习分析模型研究[J]. 现代教育技术, 2017(10): 19-25.
[6] 樊敏生, 武法提. 数据驱动的动态学习干预系统设计[J]. 电化教育研究, 2020(11): 87-93.
[7] 杨丽娜, 魏永红, 肖克曦, 等. 教育大数据驱动的个性化学习服务机制研究[J]. 电化教育研究, 2020(9): 68-74.
[8] Tadesse A T, Davidsen P I. Framework to support personalized learning in complex systems[J]. Journal of Applied Research in Higher Education, 2020(1): 57-85.
[9] Brass J, Lynch T L. Personalized learning: a history of the present[J]. Journal of Curriculum Theorizing, 2020(2): 3-21.
[10] 但金凤, 王正青. 预测与干预:美国中学基于大数据分析的早期预警系统建设与运行[J]. 比较教育研究, 2021(9): 71-78.
[11] 岳伟, 闫领楠.智能时代学生主体性的异化风险及其规避[J]. 中国电化教育, 2023(2): 90-97.
[12] [美]尼古拉·尼葛洛庞蒂.数字化生存[M]. 海口: 海南出版社, 1997.
[13] [美]约翰·杜威.学校与社会——明日之学校[M]. 赵祥麟, 任钟印,吴志宏, 译. 北京: 人民教育出版社, 2004.
[14] 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(3): 22-30.
[15] 联合国教科文组织. 一起重新构想我们的未来——为教育打造新的社会契约[M]. 北京: 教育科学出版社, 2022.
[16] 中共中央、国务院印发《中国教育现代化2035》[N]. 人民日报, 2019-02-24(1).
[17] 王媛媛, 何高大. 美国《国家教育技术计划》的创新及其启示——基于五轮(1996-2016)教育技术发展规划的比较与分析[J]. 远程教育杂志, 2016(2): 11-18.
[18] 杨秀治. 从《不让一个孩子掉队法案》到《每个学生都成功法案》:美国中小学教育问责体系的演变[J].外国教育研究, 2017(5): 18-25.
[19] 何克抗. 促进个性化学习的理论、技术与方法——对美国《教育传播与技术研究手册(第四版)》的学习与思考之三[J]. 开放教育研究, 2017(2): 13-21.
[20] 徐振国, 张冠文, 石林,等. 下一代学习管理系统:内涵、核心要素及其发展[J]. 电化教育研究, 2017(10): 62-67,81.
[21] Zimmerman M A.Taking aim on empowerment research: on the distinction between individual and psychological conceptions[J]. American Journal of community psychology, 1990(1): 169-177.
[22] 袁磊, 张淑鑫, 雷敏, 等. 技术赋能教育高质量发展: 人工智能、区块链和机器人应用前沿[J]. 开放教育研究, 2021(8): 4-16.
[23] Han J W, Kamber M, Pei J. 数据挖掘概念与技术[M]. 范明, 孟小峰, 译. 北京: 机械工业出版社, 2001.
[24] Baker R,Yacef K. The state of educational data mining in 2009 : a review and future visions[J]. Journal of Educational Data Mining, 20091(1): 3-17.
[25] Data Quality Campaign. New resources show that data makes personalized learning possible[EB/OL]. (2017-08-17)[2022-01-20]. https:/dataqualitycampaign.org/news-new-resources-show-data-makes-personalized-learning-possible/.
[26] Bucher T. The algorithmic imaginary: exploring the ordinary affects of Facebook algorithms[J]. Information, communication & society, 2017(1):30-44.
[27] 唐烨伟, 茹丽娜, 范佳荣, 等. 基于学习者画像建模的个性化学习路径规划研究[J]. 电化教育研究, 2019(10): 53-60.
[28] 郭华. 深度学习及其意义[J]. 课程·教材·教法, 2016(11): 25-32.
[29] 韩雪童. 大数据时代个性化学习的技术曲解、本源廓清与突围路径[J]. 电化教育研究, 2022(6): 25-31, 60.
[30] 郭元祥. 深度教学:促进学习者素养发育的教学变革[M]. 福州: 福建教育出版社, 2021.
[31] 庞金友. 数字秩序的“阿喀琉斯之踵”:当代数据治理的迷思与困境[J]. 广西师范大学学报(哲学社会科学版), 2022(5): 11-20.
[1] YUAN Fang-cheng1, WEI Yu-xin2. The More Radical, the More Conservative: Technological Regulation of Society and Its Redemption [J]. Journal of Guangxi Teachers Education University (Philosophy and Social Sciences Edition), 2023, 59(4): 124-135.
[2] Yu Wen-xuan, MA Liang, WANG Dian-li, HAN Zhi-ming, XIE Xin-shui, YE Lin, WEN Hong. Discussion on the Application and Regulation of ChatGPT, the New Generation Artificial Intelligence Technology [J]. Journal of Guangxi Teachers Education University (Philosophy and Social Sciences Edition), 2023, 59(2): 28-53.
[3] ZHANG Ai-jun. The Possible Dimensions of ChatGPT’s Promoting the Dissemination of Online Politics Paradox [J]. Journal of Guangxi Teachers Education University (Philosophy and Social Sciences Edition), 2023, 59(2): 54-65.
[4] WU Xiao-lin, Xing Yi-fei. Knowledge Replication or Innovation Stimulation? —Challenges and Opportunities of Artificial Intelligence (ChatGPT) for Social Science Graduate Education [J]. Journal of Guangxi Teachers Education University (Philosophy and Social Sciences Edition), 2023, 59(2): 66-74.
[5] CHEN Zeng-zhao, SHI Ya-wen, WANG Meng-ke. The Realistic Picture of Artificial Intelligence Driving Educational Transformation —An Analysis of Teachers’ Coping Strategies with ChatGPT [J]. Journal of Guangxi Teachers Education University (Philosophy and Social Sciences Edition), 2023, 59(2): 75-85.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
[1] CHEN Xin-xia. The Philosophical Foundation of Marxist Theory on Human Development[J]. Journal of Guangxi Teachers Education University (Philosophy and Social Sciences Edition), 2023, 59(4): 1 -8 .
[2] PANG Jin-you, CHEN Meng-xue. Intelligent Entry and the Dilemma of Democracy: Risks and Challenges of Democratic Politics in the Age of Artificial Intelligence[J]. Journal of Guangxi Teachers Education University (Philosophy and Social Sciences Edition), 2023, 59(4): 9 -20 .
[3] DI Jin-hua, HUANG Qian. Regional Hierarchy and Expansion of Incentive Space for Primary-level Officials —Reflections Based on Fieldwork in Xiangxian County[J]. Journal of Guangxi Teachers Education University (Philosophy and Social Sciences Edition), 2023, 59(4): 21 -33 .
[4] WEI Cheng-Lin. Street Bureaucrats and Resilient City Building: The Perspective of Mass Work[J]. Journal of Guangxi Teachers Education University (Philosophy and Social Sciences Edition), 2023, 59(4): 34 -45 .
[5] DAI Yi-yuan, LI Zhen-zhen. Will the Improvement of Artificial Intelligence Literacy Bring About More Concerns for Personal Information Privacy? —A Research on Mesomeric Effect Based on Protection Consciousness and Technology Trust[J]. Journal of Guangxi Teachers Education University (Philosophy and Social Sciences Edition), 2023, 59(4): 46 -57 .
[6] YU Wei, SU Ling-min. Learning to Learn: An Essential Perspective on the Transformation of Learning Methods in the Era of Intelligence[J]. Journal of Guangxi Teachers Education University (Philosophy and Social Sciences Edition), 2023, 59(4): 58 -67 .
[7] WANG Xiao-gang, GE Hai-shan. Research on the Impact of Digital Inclusive Finance on the Income Gap between Urban and Rural Areas —An Analysis of Influencing Factors Based on Panel Change Point Model[J]. Journal of Guangxi Teachers Education University (Philosophy and Social Sciences Edition), 2023, 59(4): 80 -96 .
[8] YANG Zhi-yuan, XU Hao. Global Value Chain Position, Labor Skill Difference and Labor Income Gap[J]. Journal of Guangxi Teachers Education University (Philosophy and Social Sciences Edition), 2023, 59(4): 97 -109 .
[9] LIU Shou-gang. What Kind of Public, and Whose Public? —A Focus on the Comparison of Huang Zongxi's and Locke's Fiscal Publicity Thoughts[J]. Journal of Guangxi Teachers Education University (Philosophy and Social Sciences Edition), 2023, 59(4): 110 -123 .
[10] YUAN Fang-cheng1, WEI Yu-xin2. The More Radical, the More Conservative: Technological Regulation of Society and Its Redemption[J]. Journal of Guangxi Teachers Education University (Philosophy and Social Sciences Edition), 2023, 59(4): 124 -135 .