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Making sense of sensing: Learning through maker-based civic engagement

Science and Information Technology

Karin Ekman is defending her doctoral thesis for the Degree of Doctor of Philosophy in Information Technology and Learning.

Dissertation
Date
25 Mar 2022
Time
13:00 - 15:00
Location
Torg Grön, institutionen för tillämpad informationsteknologi, Göteborgs universitet, Hus Patricia, Forskningsgången 6, Göteborg
Additional info
Link to
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Good to know
The doctoral defence is also available via Zoom. Webinar ID: 683 8901 2966. Passcode: 630664

Faculty opponent is professor Palmyre Pierroux, institutt for pedagogikk, Oslo University
Organizer
Department of Applied Information Technology

Description of the thesis:

Through a multi-sited ethnography this dissertation contributes with two perspectives on DIY monitoring; how an institutionally organized initiative perceives outcomes of public engagement and how a grassroot civic mobilization initiative act and learn while DIY monitoring.

The institutionally organized initiative planned for public participation and wanted to influence people. However, they prioritized getting sensors up and running since not knowing how to address issues of empowerment. In the grassroot civic mobilization initiative, the maker-based social media setting allowed for meaningful participation through a participatory culture. By sharing knowledge, information, ideas, and feedback, members developed an understanding of the reasons for high levels of air pollution through productive and social talk. This new understanding was scaffolded through the social and shared practice as common community knowledge.

The maker-based civic engagement enables a particular form of interest-driven and peer-supported learning. This highlights the importance of social talk and the need to acknowledge local, experiential knowledge from interest-driven initiatives. Rather than finding members of the grassroot initiative changing their behaviors or showing traditional civic engagement regarding to matters of air pollution, they generate hyperlocal open real-time air pollution data.

To full text version of the thesis