In this paper we analyse the emotional experience of students in 11 courses within EduOpen (www.eduopen.org), an international Moocs’ platform. The main theoretical idea is that communities of inquiry (Garrison, Anderson, & Archer, 2000) are digital learning experiences characterized by an emotional dimension strongly impacting on learning (Cleveland-Innes, & Campbell., 2012). Our methodological approach refers to the field of qualitative learning analytics (ibidem; Loperfido, Dipace, Scarinci, in press), which connects the attention to the personalization of learning with the understanding of the students’ experience from a microlevel point of view. Therefore, we connect the use of the general sentiment analysis, which looks at both negative and positive feelings, with Grounded theory approach, which looks at specific emotions. Through a bottom up process and Nvivo 11 Plus software, we analysed the forum dedicated to the students’ selfpresentation from all of the 11 courses. We defined a set of categories composed by a three-levels system. At a 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. 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 and how the motivations dimension heavily characterizes the emotional dimension of students.
Analysing emotions to personalise learning for EduOpen Moocs’ students / Dipace, A.; Loperfido, F. F.; Scarinci, A.. - (2018). (Intervento presentato al convegno Conference Proceedings The Online, Open and Flexible Higher Education Conference tenutosi a Aarhus nel 10-12/10/2018).
Analysing emotions to personalise learning for EduOpen Moocs’ students
Dipace A.;
2018
Abstract
In this paper we analyse the emotional experience of students in 11 courses within EduOpen (www.eduopen.org), an international Moocs’ platform. The main theoretical idea is that communities of inquiry (Garrison, Anderson, & Archer, 2000) are digital learning experiences characterized by an emotional dimension strongly impacting on learning (Cleveland-Innes, & Campbell., 2012). Our methodological approach refers to the field of qualitative learning analytics (ibidem; Loperfido, Dipace, Scarinci, in press), which connects the attention to the personalization of learning with the understanding of the students’ experience from a microlevel point of view. Therefore, we connect the use of the general sentiment analysis, which looks at both negative and positive feelings, with Grounded theory approach, which looks at specific emotions. Through a bottom up process and Nvivo 11 Plus software, we analysed the forum dedicated to the students’ selfpresentation from all of the 11 courses. We defined a set of categories composed by a three-levels system. At a 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. 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 and how the motivations dimension heavily characterizes the emotional dimension of students.File | Dimensione | Formato | |
---|---|---|---|
0062-AC-2018-analysing-emotions.pdf
Open access
Tipologia:
Versione pubblicata dall'editore
Dimensione
2.02 MB
Formato
Adobe PDF
|
2.02 MB | Adobe PDF | Visualizza/Apri |
Pubblicazioni consigliate
I metadati presenti in IRIS UNIMORE sono rilasciati con licenza Creative Commons CC0 1.0 Universal, mentre i file delle pubblicazioni sono rilasciati con licenza Attribuzione 4.0 Internazionale (CC BY 4.0), salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris