DiSCoKit: An Open-Source Toolkit for Deploying Live LLM Experiences in Survey Research
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arXiv
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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2026
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| Acceso en línea: | |
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| _version_ | 1866915794046156800 |
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| author | Banks, Jaime Stromer-Galley, Jon Singh, Samiksha Capano, Collin |
| author_facet | Banks, Jaime Stromer-Galley, Jon Singh, Samiksha Capano, Collin |
| contents | Advancing social-scientific research of human-AI interaction dynamics and outcomes often requires researchers to deliver experiences with live large-language models (LLMs) to participants through online survey platforms. However, technical and practical challenges (from logging chat data to manipulating AI behaviors for experimental designs) often inhibit survey-based deployment of AI stimuli. We developed DiSCoKit--an open-source toolkit for deploying live LLM experiences (e.g., ones based on models delivered through Microsoft Azure portal) through JavaScript-enabled survey platforms (e.g., Qualtrics). This paper introduces that toolkit, explaining its scientific impetus, describes its architecture and operation, as well as its deployment possibilities and limitations. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_11230 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | DiSCoKit: An Open-Source Toolkit for Deploying Live LLM Experiences in Survey Research Banks, Jaime Stromer-Galley, Jon Singh, Samiksha Capano, Collin Human-Computer Interaction Advancing social-scientific research of human-AI interaction dynamics and outcomes often requires researchers to deliver experiences with live large-language models (LLMs) to participants through online survey platforms. However, technical and practical challenges (from logging chat data to manipulating AI behaviors for experimental designs) often inhibit survey-based deployment of AI stimuli. We developed DiSCoKit--an open-source toolkit for deploying live LLM experiences (e.g., ones based on models delivered through Microsoft Azure portal) through JavaScript-enabled survey platforms (e.g., Qualtrics). This paper introduces that toolkit, explaining its scientific impetus, describes its architecture and operation, as well as its deployment possibilities and limitations. |
| title | DiSCoKit: An Open-Source Toolkit for Deploying Live LLM Experiences in Survey Research |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2602.11230 |