MetaCues: Enabling Critical Engagement with Generative AI for Information Seeking and Sensemaking
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arXiv
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| Format: | Preprint |
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2026
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| _version_ | 1866910060769181696 |
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| author | Singh, Anjali Taneja, Karan Guan, Zhitong Rieh, Soo Young |
| author_facet | Singh, Anjali Taneja, Karan Guan, Zhitong Rieh, Soo Young |
| contents | Generative AI (GenAI) search tools are increasingly used for information seeking, yet their design tends to encourage cognitive offloading, which may lead to passive engagement, selective attention, and informational homogenization. Effective use requires metacognitive engagement to craft good prompts, verify AI outputs, and critically engage with information. We developed MetaCues, a novel GenAI-based interactive tool for information seeking that delivers metacognitive cues alongside AI responses and a note-taking interface to guide users' search and associated learning. Through an online study (N = 146), we compared MetaCues to a baseline tool without cues, across two broad search topics that required participants to explore diverse perspectives in order to make informed judgments. Preliminary findings regarding participants' search behavior show that MetaCues leads to increased confidence in attitudinal judgments about the search topic as well as broader inquiry, with the latter effect emerging primarily for the topic that was less controversial and with which participants had relatively less familiarity. Accordingly, we outline directions for future qualitative exploration of search interactions and inquiry patterns. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_19634 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | MetaCues: Enabling Critical Engagement with Generative AI for Information Seeking and Sensemaking Singh, Anjali Taneja, Karan Guan, Zhitong Rieh, Soo Young Human-Computer Interaction Artificial Intelligence Computers and Society Information Retrieval Generative AI (GenAI) search tools are increasingly used for information seeking, yet their design tends to encourage cognitive offloading, which may lead to passive engagement, selective attention, and informational homogenization. Effective use requires metacognitive engagement to craft good prompts, verify AI outputs, and critically engage with information. We developed MetaCues, a novel GenAI-based interactive tool for information seeking that delivers metacognitive cues alongside AI responses and a note-taking interface to guide users' search and associated learning. Through an online study (N = 146), we compared MetaCues to a baseline tool without cues, across two broad search topics that required participants to explore diverse perspectives in order to make informed judgments. Preliminary findings regarding participants' search behavior show that MetaCues leads to increased confidence in attitudinal judgments about the search topic as well as broader inquiry, with the latter effect emerging primarily for the topic that was less controversial and with which participants had relatively less familiarity. Accordingly, we outline directions for future qualitative exploration of search interactions and inquiry patterns. |
| title | MetaCues: Enabling Critical Engagement with Generative AI for Information Seeking and Sensemaking |
| topic | Human-Computer Interaction Artificial Intelligence Computers and Society Information Retrieval |
| url | https://arxiv.org/abs/2603.19634 |