Unlocking Adaptive User Experience with Generative AI

Yutan Huang, Tanjila Kanij, Anuradha Madugalla, Shruti Mahajan, Chetan Arora, John Grundy

2024

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.

Paper Citation

in Harvard Style

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 - Volume 1: ENASE; ISBN 978-989-758-696-5, SciTePress, pages 760-768. DOI: 10.5220/0012741000003687

in Bibtex Style

@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 - Volume 1: ENASE},
year={2024},
pages={760-768},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012741000003687},
isbn={978-989-758-696-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 19th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE
TI - Unlocking Adaptive User Experience with Generative AI
SN - 978-989-758-696-5
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