人工智能赋能个性化学习：E-Learning推荐系统研究热点与展望

被引：26

作者：

谢浩然 ^{[1
]}

陈协玲 ^{[2
]}

郑国城 ^{[2
]}

王富利 ^{[3
]}

机构：

[1] 岭南大学电脑及决策科学学系

[2] 香港教育大学数学与信息科技学系

[3] 香港都会大学科技学院

来源：

现代远程教育研究 | 2022年 / 34卷 / 03期

关键词：

E-Learning; 个性化推荐系统; 个性化学习; 人工智能; 研究热点;

D O I：

暂无

中图分类号：

G434 [计算机化教学]; TP18 [人工智能理论]; TP391.3 [检索机];

学科分类号：

040110 ; 081104 ; 0812 ; 0835 ; 1405 ; 081203 ;

摘要：

E-Learning领域的推荐系统在满足学习者个性化学习需求方面发挥着重要作用。近年来，国际上围绕E-Learning推荐系统开展的研究迅速增多。采用文献计量分析方法对该领域的研究进行系统分析，有助于为E-Learning推荐系统的高水平研究和高质量应用提供镜鉴。综括而言，当前国际E-Learning领域的推荐系统研究热点及其演变趋势集中体现在6个方面：一是融合多种技术优势的混合推荐日益受到重视且逐渐成为主流。二是伴随技术支持下群体学习的多元发展，个性化推荐由关注个体推荐逐步转向关注群体推荐。三是随着大规模开放在线课程的流行，个性化推荐逐步突破小规模而面向大规模学习者群体，重视通过对海量学习资源和过程数据的搜集和挖掘而提供个性化推荐。四是从心理学层面关注学习者情绪变化，并据此构建上下文推荐系统，通过优化调整推荐内容不断促进学习者高效完成学习任务。五是在推荐功能上更加强调学习模型构建，重视提升学习者的深层次认知能力和促进有效学习。六是在先进技术的支持上，个性化推荐系统强调引入深度学习技术，不断优化其表征能力、融合效率和推荐效果。

引用

页码：15 / 23+57 +57

页数：10

共 31 条

[21]

A General Framework for Intelligent Recommender Systems[J] . Jose Aguilar,Priscila Valdiviezo-Díaz,Guido Riofrio.Applied Computing and Informatics . 2016 (2)

[22]

A bibliometric review on natural resource accounting during 1995–2014[J] . Shaozhuo Zhong,Yong Geng,Wenjing Liu,Cuixia Gao,Wei Chen.Journal of Cleaner Production . 2016

[23]

Toward interactive context-aware affective educational recommendations in computer-assisted language learning[J] . Olga C. Santos,Mar Saneiro,Jesus G. Boticario,M.C. Rodriguez-Sanchez.New Review of Hypermedia and Multimedia . 2016 (1-2)

[24]

Recommender systems in e-learning environments: a survey of the state-of-the-art and possible extensions[J] . Aleksandra Kla?nja-Mili?evi?,Mirjana Ivanovi?,Alexandros Nanopoulos.Artificial Intelligence Review . 2015 (4)

[25]

A recommender agent based on learning styles for better virtual collaborative learning experiences[J] . Maria-Iuliana Dascalu,Constanta-Nicoleta Bodea,Alin Moldoveanu,Anca Mohora,Miltiadis Lytras,Patricia Ordo?ez de Pablos.Computers in Human Behavior . 2015

[26] e-Learning recommender system for a group of learners based on the unified learner profile approach [J].

Dwivedi, Pragya ;

Bharadwaj, Kamal K. .

EXPERT SYSTEMS, 2015, 32 (02) :264-276

[27]

The reciprocal links between school engagement, youth problem behaviors, and school dropout during adolescence[J] . Wang Ming-Te,Fredricks Jennifer A.Child development . 2014 (2)

[28]

Culture effects on the knowledge sharing in multi-national virtual classes: A mixed method[J] . Xi Zhang,Patricia Ordó?ez de Pablos,Qingkun Xu.Computers in Human Behavior . 2014

[29]

Improving e-learning communities through optimal composition of multidisciplinary learning groups[J] . Maria-Iuliana Dascalu,Constanta-Nicoleta Bodea,Miltiadis Lytras,Patricia Ordo?ez de Pablos,Alexandru Burlacu.Computers in Human Behavior . 2014

[30] A Generic Architecture for Emotion-based Recommender Systems in Cloud Learning Environments [J].

Leony, Derick ;

Parada Gelvez, Hugo A. ;

Munoz-Merino, Pedro J. ;

Pardo, Abelardo ;

Delgado Kloos, Carlos .

JOURNAL OF UNIVERSAL COMPUTER SCIENCE, 2013, 19 (14) :2075-2092

← 1 2 3 4 →