Publication
LAK 2016
Conference paper

Student affect during learning with a MOOC

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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.

Date

25 Apr 2016

Publication

LAK 2016

Authors

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