Investigation cycle for analysing image-based data: perspectives from three contexts

Author(s)
Kazak, Sibel
Fielding, Jill
Zapata-Cardona, Lucia
Publication Date
2022
Abstract
Paper presented by Sibel Kazak
Abstract
<p>A traditional data investigation cycle includes problem posing, planning and collecting data, analysing data, and making conclusions. This research studies the data investigation cycle for analysing image-based data. In three independent research projects, students at different educational levels and from different countries were provided photographic data of families and their environments around the world from the Dollar Street project. Data collected included classroom video-recordings (Australia), individual student interviews (Colombia), and pre-service mathematics teachers' interviews (Turkey). Analysis focused on the sequence of actions that helped students when attempting to pose and answer questions based on the data set. Findings suggested a similar, iterative sequence of actions across all cohorts: context and data set familiarisation, variable identification/generation, problem posing and planning, data organisation and analysis, and drawing conclusions.</p>
Citation
Bridging the Gap: Empowering and Educating Today's Learners in Statistics: Proceedings of the 11th International Conference on Teaching Statistics!, p. 1-6
Link
Publisher
International Association for Statistical Education (IASE)
Title
Investigation cycle for analysing image-based data: perspectives from three contexts
Type of document
Conference Publication
Entity Type
Publication

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