How Does My Time Use Align With My Values? Personal Informatics for Connecting Abstract Values to Everyday Life

Paper Title

How Does My Time Use Align With My Values? Personal Informatics for Connecting Abstract Values to Everyday Life

Publication Info

• Topic area: Personal informatics systems for values-based reflection and behavior alignment.
• Keywords: Personal informatics, values, time use, self-reflection, behavior change, AI-assisted tracking, visualization, life studies, value-action gap, multi-level reflection.

Background and Problem

• Problem / challenge: Existing personal informatics systems track time use but fail to explicitly connect it to abstract personal values. This leaves a gap in understanding how technology can support meaningful reflection on the alignment between values and daily activities.
• Significance: Aligning time use with personal values is critical for well-being and living a fulfilling life. Addressing the value-action gap can help individuals make more intentional life choices.
• Motivation and related work: Prior work in personal informatics has explored tracking time and fostering reflection but has not focused on abstract values. Studies in HCI have shown the importance of grounding abstract values in specific contexts, but existing systems lack tools to connect values to daily activities.

Solution

• Proposed approach: eValuATE, a personal informatics system designed to help individuals reflect on the alignment between their time use and personal values through activity annotation, visualization, and AI-assisted tracking.
• Novelty:
  1. A customizable library of values drawn from psychological theories and world religions to scaffold high-level reflection.
  2. Integration of AI-assisted voice tools for narrating and reconstructing daily activities, reducing the cognitive burden of self-tracking.
  3. A dynamic network visualization connecting abstract values to concrete activities for multi-level reflection.
  4. Introduction of the concept of short-term "life studies" for intensive, periodic self-tracking and reflection.
• Procedure and key techniques:
  • Participants elicit personal values using a pre-defined library or create custom sets.
  • Daily activities are reconstructed using a calendar interface and annotated with values using sliders.
  • AI voice tools assist in narrating and parsing activities.
  • A bipartite network visualization aggregates and connects values with activities for reflective insights.

Results

• Concrete findings:
  • Participants collectively recorded 1,600 hours of activity data and annotated 1,254 activities with over 4,100 value annotations.
  • 53% of participants reported behavior changes, and all participants reported gaining new self-insights.
  • Average System Usability Score (SUS): 76/100; Technology Supported Reflection Inventory (TSRI): 42/63.
• Advantage over baselines:
  • Unlike prior systems, eValuATE explicitly connects abstract values to time use, enabling deeper reflection and value refinement.
  • AI-assisted tracking reduced the effort of data collection compared to manual-only systems.
• Experiments / evaluation:
  • A three-stage study with 15 participants: an opening think-aloud session, 2–4 weeks of in situ deployment, and a closing interview.
  • Participants used the system to annotate activities, reflect on values, and explore visualizations.
  • Metrics included Satisfaction with Life Scale (SWLS), usability surveys, and qualitative interviews.
• Limitations and future work:
  • Limited generalizability due to a small, highly educated sample.
  • High cognitive burden of value annotation despite AI assistance.
  • Future work could explore automated value annotation, goal-directed tracking, and longitudinal studies with predefined value sets.

Summary

This study introduced eValuATE, a personal informatics system that connects abstract values to daily activities through annotation, AI-assisted tracking, and visualization. The system helped participants refine their values, reflect on their time use, and, for some, change their behavior. Findings suggest that personal informatics systems can support reflection across abstraction levels, motivating the concept of short-term "life studies" for intensive self-tracking. The study contributes to the design of PI systems by presenting a multi-level reflection model and offering insights into scaffolding value-based reflection in everyday life.