UX Remix: Improving Measurement Item Design Process Using Large Language Models and Prior Literature
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arXiv
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| Format: | Preprint |
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2025
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| _version_ | 1866908316660137984 |
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| author | Yun, Hyeonggeun Jang, Jinkyu |
| author_facet | Yun, Hyeonggeun Jang, Jinkyu |
| contents | Researchers often struggle to develop measurement items and lack a standardized process. To support the design process, we present UX Remix, a system to help researchers develop constructs and measurement items using large language models (LLMs). UX Remix leverages a database of constructs and associated measurement items from previous papers. Based on the data, UX Remix recommends constructs relevant to the research context. The researchers then select appropriate constructs based on the recommendations. Afterward, selected constructs are used to generate a custom construct, and UX Remix recommends measurement items. UX Remix streamlines the process of selecting constructs, developing measurement items, and adapting them to research contexts, addressing challenges in the selection and reuse of measurement items. This paper describes the implementation of the system, the potential benefits, and future directions to improve the rigor and efficiency of measurement design in human-computer interaction (HCI) research. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_09169 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | UX Remix: Improving Measurement Item Design Process Using Large Language Models and Prior Literature Yun, Hyeonggeun Jang, Jinkyu Human-Computer Interaction Researchers often struggle to develop measurement items and lack a standardized process. To support the design process, we present UX Remix, a system to help researchers develop constructs and measurement items using large language models (LLMs). UX Remix leverages a database of constructs and associated measurement items from previous papers. Based on the data, UX Remix recommends constructs relevant to the research context. The researchers then select appropriate constructs based on the recommendations. Afterward, selected constructs are used to generate a custom construct, and UX Remix recommends measurement items. UX Remix streamlines the process of selecting constructs, developing measurement items, and adapting them to research contexts, addressing challenges in the selection and reuse of measurement items. This paper describes the implementation of the system, the potential benefits, and future directions to improve the rigor and efficiency of measurement design in human-computer interaction (HCI) research. |
| title | UX Remix: Improving Measurement Item Design Process Using Large Language Models and Prior Literature |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2504.09169 |