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Student affect during learning with a MOOC
- 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.
- Subjects :
- Pride
Data collection
media_common.quotation_subject
05 social sciences
Emotion detection
Contentment
050301 education
0102 computer and information sciences
Affect (psychology)
01 natural sciences
010201 computation theory & mathematics
Scale (social sciences)
Pedagogy
medicine
Mathematics education
Anxiety
medicine.symptom
Psychology
0503 education
media_common
Subjects
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