What emotional experience can students live in digital mediated learning processes? In this paper we connect Learning analytics and Grounded theory to analyse the emotional presence of students in 11 courses within EduOpen (www.eduopen.org) MOOCs’ platform. Namely, we analysed through a bottom up process and Nvivo 11 Plus software the forum dedicated to the students’ self-presentation from all of the courses. By going ahead with the analysis, we defined a set of categories composed by a three-levels system. At a more general level we have the macrodimensions “Sentiment about EduOpen” and “Emotions toward topics”. Each of these dimensions is composed by a number of child” categories and subcategories (which are the nodes to Nvivo’s language). After defining the entire set of categories and categorizing all the texts (which was a circular process), we run some graphs on Nvivo showing the hierarchical structure of dimensions, the relations among dimensions and sources, and the clusters of dimensions by coding similarity. Results show how some courses are more composed by negative or positive sentiments (both toward the topic or the logistic arrangement of the course) and how the motivations dimension heavily characterizes the broad emotional dimension of students. In an evidence based action-research perspective, these results give interesting suggestions to personalize the learning activities proposed to students by EduOpen.

Qualitative Learning Analytics to Understand the Students’ Sentiments and Emotional Presence in EduOpen.

Loperfido, Fedela Feldia;Scarinci, Alessia
2018

Abstract

What emotional experience can students live in digital mediated learning processes? In this paper we connect Learning analytics and Grounded theory to analyse the emotional presence of students in 11 courses within EduOpen (www.eduopen.org) MOOCs’ platform. Namely, we analysed through a bottom up process and Nvivo 11 Plus software the forum dedicated to the students’ self-presentation from all of the courses. By going ahead with the analysis, we defined a set of categories composed by a three-levels system. At a more general level we have the macrodimensions “Sentiment about EduOpen” and “Emotions toward topics”. Each of these dimensions is composed by a number of child” categories and subcategories (which are the nodes to Nvivo’s language). After defining the entire set of categories and categorizing all the texts (which was a circular process), we run some graphs on Nvivo showing the hierarchical structure of dimensions, the relations among dimensions and sources, and the clusters of dimensions by coding similarity. Results show how some courses are more composed by negative or positive sentiments (both toward the topic or the logistic arrangement of the course) and how the motivations dimension heavily characterizes the broad emotional dimension of students. In an evidence based action-research perspective, these results give interesting suggestions to personalize the learning activities proposed to students by EduOpen.
978-615-5511-23-3
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11586/239781
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