Pair Sensemaking of Personal Data: An Approach for Fostering Reflection on Personal Experiences

Motivation: In today’s increasingly digital world, making sense of personal data has become a valuable approach for individuals to understand their behavior and reflect on lived experiences. Across fields such as personal informatics, data visualization, and design, supporting reflection through sensemaking of personal data is increasingly recognized as a critical for promoting behavior change and cultivating deeper self-understanding. Within the literature on collaborative sensemaking, pair collaboration has emerged as a particularly promising strategy for supporting reflective practices. It offers unique advantages— such as the integration of diverse perspectives, focused dyadic comparison, and rich interaction dynamics—that are especially effective for surfacing tacit knowledge and generating deeper insights. Despite this promise, most existing research in personal informatics and visualization has focused on individual engagement with personal data, with limited exploration of collaborative or group-level interactions. In particular, the distinctive characteristics of pair collaboration remain underexplored in the context of personal data. This reveals a significant gap in understanding how to effectively support pair sensemaking of personal data in order to foster reflection.
Objective: To address this gap, this dissertation introduces and develops the pair sensemaking of personal data approach—a novel method for fostering reflection through pair engagement with personal data. This approach emphasizes the integration of both one’s own and others’ data, dyadic comparison within subjective data representations, and reciprocal, reflective dialogues between pairs to co-construct self-knowledge and deepen personal reflection. To realize this objective, the thesis adopts a progressive, mixed-methods research strategy, unfolding across three empirical studies. Each study incrementally explores and refines how pair sensemaking of personal data can be effectively designed to enhance reflective engagement and foster meaningful insights into lived experiences.