Automatic Content Analysis of Student Moral Discourse in a Collaborative Learning Activity

Claudio Alvarez*, Gustavo Zurita, Andrés Carvallo, Pablo Ramírez, Eugenio Bravo, Nelson Baloian

*Autor correspondiente de este trabajo

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

2 Citas (Scopus)

Resumen

In most computer supported collaborative learning activities, the teacher monitors and/or reviews data generated by students and groups as they complete the learning tasks, in order to provide guidance and feedback. Without appropriate technological means that support the processes of collection and selection of students’ generated responses, these duties can result in a high cognitive load for teachers, especially if students generate textual, qualitative content that requires real-time reviewing. In this research we deal with EthicApp, a collaborative application in which this problem is apparent, as students analyze a given ethics case individually and in small groups and deliver written judgements in each phase of the activity. We present a solution to the problem, based on enhancing EthicApp’s teacher’s interface with automated content analysis capabilities. This includes a dashboard that automatically displays students’ most relevant contributions, and cluster visualizations that permit identifying groups of students with similar responses to activity tasks. Validation of the approach was based on a dataset comprising 4,366 comments about an academic ethics case, which were written by 520 students divided into 19 class groups. Expert judgement was applied to evaluate content analysis effectiveness at selecting comments that are both meaningful and representative of students’ different views. More than 80% of comment selections were found valuable, according to experts’ analysis.
Idioma originalInglés
Título de la publicación alojadaLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditoresDavinia Hernandez-Leo, Reiko Hishiyama, Gustavo Zurita, Benjamin Weyers, Alexander Nolte, Hiroaki Ogata
EditorialSpringer Science and Business Media Deutschland GmbH
Páginas3-19
Número de páginas17
ISBN (versión impresa)9783030850708
DOI
EstadoPublicada - 2021
Evento27th International Conference on Collaboration Technologies and Social Computing, CollabTech 2021 - Virtual, Online
Duración: 30 ago. 20212 sept. 2021

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen12856 LNCS
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia27th International Conference on Collaboration Technologies and Social Computing, CollabTech 2021
CiudadVirtual, Online
Período30/08/212/09/21

Nota bibliográfica

Publisher Copyright:
© 2021, Springer Nature Switzerland AG.

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