Developing a Data-Driven Learning Interest Recommendation System to Promoting Self-Paced Learning on MOOCs

被引：8

作者：

Chang, Hsuan-Ming ^{[1
]}

Huang, Nen-Fu ^{[1
]}

Kuo, Tonny Meng-Lun ^{[2
]}

Chen, So -Chen ^{[1
]}

Li, Chia -An ^{[1
]}

Huang, Yi-Wei ^{[1
]}

Cheng, Yu-Cheng ^{[1
]}

Hsu, Hao-Hsuan ^{[1
]}

Tzeng, Jian-Wei ^{[3
]}

机构：

[1] Natl Tsing Hua Univ, Dept Comp Sci, Hsinchu, Taiwan

[2] Natl Tsing Hua Univ, Inst Learning Sci, Hsinchu, Taiwan

[3] Natl Tsing Hua Univ, Off Acad affairs, Hsinchu, Taiwan

来源：

2016 IEEE 16TH INTERNATIONAL CONFERENCE ON ADVANCED LEARNING TECHNOLOGIES (ICALT) | 2016年

关键词：

MOOCs; self-paced learning; keywords cloud; subtitles;

D O I：

10.1109/ICALT.2016.42

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

A "keywords cloud" learning interest/difficult reminding system based on learners' video watching logs and subtitles is proposed for promoting self-paced MOOC learning. By identifying the hot video segments (via video seek event counts) and weighting the keywords of hot video segments, we are able to establish the "keywords cloud" of each learning topic. This feature is valuable for learners to quick identify the most important or difficult concepts of each topic. This is also useful for the teacher to more understand which parts of the contents of each topic are most difficult for the learners which can be further improved.

引用

页码：23 / 25

页数：3

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