Enregistré dans:
Détails bibliographiques
Auteurs principaux: Yun, Hyeonggeun, Jang, Jinkyu
Format: Preprint
Publié: 2025
Sujets:
Accès en ligne:https://arxiv.org/abs/2504.09169
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
_version_ 1866908316660137984
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