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Authors: Yutan Huang ; Tanjila Kanij ; Anuradha Madugalla ; Shruti Mahajan ; Chetan Arora and John Grundy

Affiliation: Department of Software Systems and Cybersecurity, Monash University, Clayton, Melbourne, Australia

Keyword(s): Adaptive UI/UX, User-Centered Designs, Generative AI, ChatGPT, Persona.

Abstract: Developing user-centred applications that address diverse user needs requires rigorous user research. This is time, effort and cost-consuming. With the recent rise of generative AI techniques based on Large Language Models (LLMs), there is a possibility that these powerful tools can be used to develop adaptive interfaces. This paper presents a novel approach to develop user personas and adaptive interface candidates for a specific domain using ChatGPT. We develop user personas and adaptive interfaces using both ChatGPT and a traditional manual process and compare these outcomes. To obtain data for the personas we collected data from 37 survey participants and 4 interviews in collaboration with a not-for-profit organisation. The comparison of ChatGPT generated content and manual content indicates promising results that encourage using LLMs in the adaptive interfaces design process.

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Paper citation in several formats:
Huang, Y., Kanij, T., Madugalla, A., Mahajan, S., Arora, C. and Grundy, J. (2024). Unlocking Adaptive User Experience with Generative AI. In Proceedings of the 19th International Conference on Evaluation of Novel Approaches to Software Engineering - ENASE; ISBN 978-989-758-696-5; ISSN 2184-4895, SciTePress, pages 760-768. DOI: 10.5220/0012741000003687

@conference{enase24,
author={Yutan Huang and Tanjila Kanij and Anuradha Madugalla and Shruti Mahajan and Chetan Arora and John Grundy},
title={Unlocking Adaptive User Experience with Generative AI},
booktitle={Proceedings of the 19th International Conference on Evaluation of Novel Approaches to Software Engineering - ENASE},
year={2024},
pages={760-768},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012741000003687},
isbn={978-989-758-696-5},
issn={2184-4895},
}

TY - CONF

JO - Proceedings of the 19th International Conference on Evaluation of Novel Approaches to Software Engineering - ENASE
TI - Unlocking Adaptive User Experience with Generative AI
SN - 978-989-758-696-5
IS - 2184-4895
AU - Huang, Y.
AU - Kanij, T.
AU - Madugalla, A.
AU - Mahajan, S.
AU - Arora, C.
AU - Grundy, J.
PY - 2024
SP - 760
EP - 768
DO - 10.5220/0012741000003687
PB - SciTePress

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