An educational dashboard can provide opportunities for new methodologies and learning
activities aligned with the 21st
-century skills and the challenges of our society, such as the fight
against climate change. In the context of the TEASPILS project, a dashboard has been
developed as part of an IoT system to monitor the environmental conditions of plants, with the
aim to promote environmental awareness among students and their teachers. The adoption of
such a learning technology enables ...
An educational dashboard can provide opportunities for new methodologies and learning
activities aligned with the 21st
-century skills and the challenges of our society, such as the fight
against climate change. In the context of the TEASPILS project, a dashboard has been
developed as part of an IoT system to monitor the environmental conditions of plants, with the
aim to promote environmental awareness among students and their teachers. The adoption of
such a learning technology enables experience-based activities, but can also arise multiple
questions about its impact on students. While dashboard tools for teachers in formal education
have been extensively covered in the literature, fewer studies have focused on students, and
even lesser on environmental dashboards for education. This research has addressed the
implementation of a dashboard for environmental awareness education from different points
of view, by designing learning activities based on the TEASPILS dashboard and by
implementing and analysing the impact of different dashboard systems -mirroring, alerting,
and advising- on the problem-solving skills of primary school students. For these purposes, a
workshop around the topic of data analysis to understand the best conditions for a plant was
conducted with primary and high school students, bringing the concept of the TEASPILS IoT
system into real classrooms for the first time. Results showed a significant positive impact of
the activities on the environmental awareness goal. Although no significant differences were
found in problem-solving performance between experimental groups, other differences and
observations allowed us to gain insight and to unfold some preliminary answers and further
questions on the use of AI in education through alerting systems.
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