This study explores how youth establish personal relevance with data within a data-art inquiry program. To be specific, this study aims to use the Personal Data Relevance (PDR) framework, adapted from Priniski et al.’s (2018) personally meaningful learning framework, to examine how youth’s engagement with data topics, data sets and data products contributes to meaningful data science learning.
The PDR framework is the main framework for understanding personal data relevance in this study. The authors implemented a data-art inquiry program with 16 high school participants in a rural high school setting in East Tennessee. The data included youth-generated data visualizations and transcripts from group interviews, and the analysis involved a qualitative approach combining deductive and inductive coding.
Youth’s personal connections with data are through three key dimensions of the PDR framework: Personal Data Association, Personal Data Usefulness and Personal Data Identification. The findings reveal that participants were most engaged with data topics reflecting personal experiences, that they were able to develop situational interest in data in the program, and that their final data visualizations provided a medium for expressing social values and identity.
This study’s findings may be context-specific due to the structured sequential nature of the data-art inquiry program. Future research could explore the PDR framework’s applicability in varied instructional designs and investigate interactions among the PDR dimensions more deeply.
Educators designing data science curricula should explicitly incorporate opportunities for youth to select personally relevant data topics, actively engage in data set exploration and reflect on the social implications of their data products to enhance data engagement and data science learning.
Encouraging youth to find personal relevance in data can foster deeper engagement with data-based societal issues, which can promote informed and active participation in public discourse through data literacy.
This study introduces the PDR framework, providing a structured approach for analyzing and designing data science programs that emphasize youth’s personally meaningful connections with data. This study contributes uniquely to the field by explicitly linking personal relevance to interdisciplinary data-art inquiry contexts.
