Reflection Before Action: Designing a Framework for Quantifying Thought Patterns for Increased Self-awareness in Personal Decision Making
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| Main Authors: | , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866914076298313728 |
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| author | Tarvirdians, Morita Chandrasegaran, Senthil Hung, Hayley Jonker, Catholijn M. Oertel, Catharine |
| author_facet | Tarvirdians, Morita Chandrasegaran, Senthil Hung, Hayley Jonker, Catholijn M. Oertel, Catharine |
| contents | When making significant life decisions, people increasingly turn to conversational AI tools, such as large language models (LLMs). However, LLMs often steer users toward solutions, limiting metacognitive awareness of their own decision-making. In this paper, we shift the focus in decision support from solution-orientation to reflective activity, coining the term pre-decision reflection (PDR). We introduce PROBE, the first framework that assesses pre-decision reflections along two dimensions: breadth (diversity of thought categories) and depth (elaborateness of reasoning). Coder agreement demonstrates PROBE's reliability in capturing how people engage in pre-decision reflection. Our study reveals substantial heterogeneity across participants and shows that people perceived their unassisted reflections as deeper and broader than PROBE's measures. By surfacing hidden thought patterns, PROBE opens opportunities for technologies that foster self-awareness and strengthen people's agency in choosing which thought patterns to rely on in decision-making. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_04364 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Reflection Before Action: Designing a Framework for Quantifying Thought Patterns for Increased Self-awareness in Personal Decision Making Tarvirdians, Morita Chandrasegaran, Senthil Hung, Hayley Jonker, Catholijn M. Oertel, Catharine Human-Computer Interaction When making significant life decisions, people increasingly turn to conversational AI tools, such as large language models (LLMs). However, LLMs often steer users toward solutions, limiting metacognitive awareness of their own decision-making. In this paper, we shift the focus in decision support from solution-orientation to reflective activity, coining the term pre-decision reflection (PDR). We introduce PROBE, the first framework that assesses pre-decision reflections along two dimensions: breadth (diversity of thought categories) and depth (elaborateness of reasoning). Coder agreement demonstrates PROBE's reliability in capturing how people engage in pre-decision reflection. Our study reveals substantial heterogeneity across participants and shows that people perceived their unassisted reflections as deeper and broader than PROBE's measures. By surfacing hidden thought patterns, PROBE opens opportunities for technologies that foster self-awareness and strengthen people's agency in choosing which thought patterns to rely on in decision-making. |
| title | Reflection Before Action: Designing a Framework for Quantifying Thought Patterns for Increased Self-awareness in Personal Decision Making |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2510.04364 |