Abstract
Between Seeing and Measuring: The Human Aspect of Defining Variables with Image-Based Data
Sibel Kazak, Middle East Technical University (METU), Türkiye
What happens when future mathematics teachers explore data using photographs instead of spreadsheets? This presentation focuses on how pre-service teachers identified and generated variables while investigating a set of selected images from the Dollar Street website (www.gapminder.org/dollarstreet) during task-based interviews. The findings highlight that working with image-based data is not just a technical task, but a deeply interpretive process. Pre-service teachers made observations from photographs and inferred meaning based on personal perspectives as they transformed these observations into variables. While some variables were easy to define, others were more complex due to the nature of individual interpretations or assumptions about what was seen in the images. These inferential variables raised important questions about how to define and measure things clearly and objectively. In this talk, I will share examples of the human side of working with image-based data and discuss what this means for bringing meaningful data experiences into K–12 classrooms.
Sibel Kazak
Dr. Sibel Kazak is an Associate Professor of Mathematics Education at Middle East Technical University (METU), Türkiye. She has a Ph.D. in Mathematics Education (Washington University in St. Louis), an M.Ed. in Mathematics Education (Pennsylvania State University), and a B.S. in Mathematics Education (METU). She has an extensive research background in statistics and probability education, with a strong publication record at both national and international levels. Her work spans the design and study of technological tools to support teaching and learning of data and chance topics from grade 4 through university. She was a post-doctoral fellow in the Model Chance project at the University of Massachusetts Amherst (2006-2008), contributing to the development of probability-modeling tools and instructional materials within TinkerPlots. As a Marie Curie research fellow at the University of Exeter (2012–2014), she led the STATSTALK project, investigating how young students develop statistical understanding through technology and dialogue. Her recent research activities include a series of EU-funded projects (SPIDAS and DataSETUP) focusing on developing data analytics and data science skills at school and initial teacher education levels.
