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This study investigates how engaging with data physicalizations, in combination with conventional representations such as numerical summaries and visualizations, impacts college students’ data investigation processes and the development of data-driven storytelling. Situated within a phenomenological framework (van Manen, 2023), the research examined how students' experiences with multiple modalities of data representation deepened their analytical engagement, supported iterative sense-making, and enhanced their ability to construct coherent, data-driven narratives. Addressing gaps in existing frameworks that often privilege numerical and visual modes, the study explored how multisensory, embodied interaction with data fosters more critical, creative, and communicatively effective engagement with data-driven insights.
Guided by two central research questions: (1) how making physicalizations to tell a data-driven story impacts participants’ data investigation processes, and (2) how conventional methods and physicalizations compare in supporting participants’ understanding of data and storytelling, this study collected data through participant artifacts, observations, and semi-structured interviews. Thematic analysis and content analysis were employed to interpret students' experiences across multiple phases of data engagement, capturing how iterative exploration, representational design, and narrative construction unfolded through interactions with numerical, visual, and physical modalities.
Findings indicated that the goal of making a physicalization substantially deepened participants’ engagement with the data investigation process by fostering iterative analysis, focused hypothesis refinement, and multimodal reasoning. Participants used physical construction as a generative tool to synthesize prior numerical and visual insights, resulting in more coherent, audience-centered narratives. Conventional methods, numerical summaries and visualizations, supported structured exploration, statistical reasoning, and hypothesis testing. However, physicalizations prompted deeper interpretive integration, emotional resonance, and expressive storytelling. Together, these modalities functioned synergistically, affirming the pedagogical value of blending analytical precision with embodied, narrative-rich representations to foster comprehensive data literacy.
The findings build upon and extend existing models of data investigation, data representation, and embodied interaction by bridging insights from information visualization, human-computer interaction, and statistics education. While the Extended InfoVis Pipeline Model (Jansen & Dragicevic, 2013) and the Data Investigation Processes Framework (Lee et al., 2022) offer valuable structures for understanding representational and analytical processes, they underrepresent the iterative, motivational, and narrative-driven dynamics that emerged through embodied engagement with data. This study proposes a conceptual reframing in which data storytelling and physicalization act as reciprocal and generative forces within the data inquiry cycle. Embedding tangible, multimodal practices alongside conventional methods fosters deeper analytical reasoning, creative meaning-making, and communicative clarity, offering important implications for designing inclusive, narrative-centered data literacy curricula.
Overall, this study advances the understanding of how tangible, multimodal engagement with data can deepen analytical reasoning, foster iterative storytelling, and expand the repertoire of representational practices available to learners. Physicalization functioned as a narrative scaffold, helping participants embody the structure, emotion, and logic of their data stories through spatial arrangement, metaphor, and material expression. While bounded by its small sample size, time constraints, and material limitations, the study offers transferable insights into how physicalization, when scaffolded by conventional analytical methods, can enhance data literacy and narrative communication. Future research is needed to examine physicalization across more diverse educational contexts, explore its long-term impacts on data engagement and retention, and investigate its affective and civic dimensions as a tool for critical data storytelling. These findings invite a reimagining of data literacy education as a multimodal, iterative, and narrative-centered practice that cultivates not only analytical skill but also creative and critical engagement with the world through data.