Predicting the decrease of engagement indicators in a MOOC

被引：43

作者：

Bote-Lorenzo, Miguel L. ^{[1
]}

Gomez-Sanchez, Eduardo ^{[1
]}

机构：

[1] Univ Valladolid, GSIC EMIC Res Grp, Valladolid, Spain

来源：

SEVENTH INTERNATIONAL LEARNING ANALYTICS & KNOWLEDGE CONFERENCE (LAK'17) | 2017年

关键词：

MOOC; engagement; supervised machine learning;

D O I：

10.1145/3027385.3027387

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Predicting the decrease of students' engagement in typical MOOC tasks such as watching lecture videos or submitting assignments is key to trigger timely interventions in order to try to avoid the disengagement before it takes place. This paper proposes an approach to build the necessary predictive models using students' data that becomes available during a course. The approach was employed in an experimental study to predict the decrease of three different engagement indicators in a MOOC. The results suggest its feasibility with values of area under the curve for different predictors ranging from 0.718 to 0.914.

引用

页码：143 / 147

页数：5