Back to Search Start Over

Student affect during learning with a MOOC

Authors :
Sidney K. D'Mello
John Dillon
Prasenjit Dey
Nirandika Wanigasekara
Bikram Sengupta
Malolan Chetlur
G. Alex Ambrose
Source :
LAK
Publication Year :
2016
Publisher :
ACM Press, 2016.

Abstract

This paper presents affect data collected from periodic emotion detection surveys throughout an introductory Statistics MOOC called "I Heart Stats." This is the first MOOC, to our knowledge, to capture valuable student affect data through self-reported surveys. To collect student affect, we used two self-reporting methods: (1) The Self-Assessment Manikin and (2) A discrete emotion list. We found that the most common reported MOOC emotion was Hope followed by Enjoyment and Contentment. There were substantial shifts in affective states over the course, notably with Anxiety and Pride. The most valuable result of our study is a preliminary description of the methods for collecting self-reported student affect at scale in a MOOC setting.

Details

Database :
OpenAIRE
Journal :
Proceedings of the Sixth International Conference on Learning Analytics & Knowledge - LAK '16
Accession number :
edsair.doi...........493e94761dcbe9d4af2fd33838ec2468
Full Text :
https://doi.org/10.1145/2883851.2883960