FlexMind: Supporting Deeper Creative Thinking with LLMs
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arXiv
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| Autores principales: | , , , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866916977268752384 |
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| author | Yang, Yaqing Mohanty, Vikram Chen, Yan-Ying Hong, Matthew K. Martelaro, Nikolas Kittur, Aniket |
| author_facet | Yang, Yaqing Mohanty, Vikram Chen, Yan-Ying Hong, Matthew K. Martelaro, Nikolas Kittur, Aniket |
| contents | Effective ideation requires both broad exploration of diverse ideas and deep evaluation of their potential. Generative AI can support such processes, but current tools typically emphasize either generating many ideas or supporting in-depth consideration of a few, lacking support for both. Research also highlights risks of over-reliance on LLMs, including shallow exploration and negative creative outcomes. We present FlexMind, an AI-augmented system that scaffolds iterative exploration of ideas, tradeoffs, and mitigations. FlexMind exposes users to a broad set of ideas while enabling a lightweight transition into deeper engagement. In a study comparing ideation with FlexMind to ChatGPT, participants generated higher-quality ideas with FlexMind, due to both broader exposure and deeper engagement with tradeoffs. By scaffolding ideation across breadth, depth, and reflective evaluation, FlexMind empowers users to surface ideas that might otherwise go unnoticed or be prematurely discarded. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_21685 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | FlexMind: Supporting Deeper Creative Thinking with LLMs Yang, Yaqing Mohanty, Vikram Chen, Yan-Ying Hong, Matthew K. Martelaro, Nikolas Kittur, Aniket Human-Computer Interaction Effective ideation requires both broad exploration of diverse ideas and deep evaluation of their potential. Generative AI can support such processes, but current tools typically emphasize either generating many ideas or supporting in-depth consideration of a few, lacking support for both. Research also highlights risks of over-reliance on LLMs, including shallow exploration and negative creative outcomes. We present FlexMind, an AI-augmented system that scaffolds iterative exploration of ideas, tradeoffs, and mitigations. FlexMind exposes users to a broad set of ideas while enabling a lightweight transition into deeper engagement. In a study comparing ideation with FlexMind to ChatGPT, participants generated higher-quality ideas with FlexMind, due to both broader exposure and deeper engagement with tradeoffs. By scaffolding ideation across breadth, depth, and reflective evaluation, FlexMind empowers users to surface ideas that might otherwise go unnoticed or be prematurely discarded. |
| title | FlexMind: Supporting Deeper Creative Thinking with LLMs |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2509.21685 |