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Title Automatic Content Analysis of Student Moral Discourse in a Collaborative Learning Activity
Authors Claudio Alvarez, Gustavo Zurita, Andres Carvallo, Pablo Ramirez, Eugenio Bravo, Nelson Baloian
Publication date 2021
Abstract 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.
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Pages 3-19
Conference name International Conference in Collaboration Technologies
Publisher Springer-Verlag (Berlin/Heidelberg, Germany)
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