A Study on an AI Evaluation Model for Improving Kiosk Accessibility for the Elderly 


Vol. 14,  No. 11, pp. 940-949, Nov.  2025
https://doi.org/10.3745/TKIPS.2025.14.11.940


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  Abstract

This study was conducted in response to the surge in demand for barrier-free kiosks following the 2025 amendment to the Anti-Discrimination against Persons with Disabilities Act. Given the limitations of the existing government certification process— characterized by prolonged duration (over two months), high costs, and the risk of evaluation failure—the research sought to explore a practical alternative solution. Grounded in the philosophy of Transgenerational Design (TD), the study aimed to develop an AI-based persona simulation system that reflects the cognitive and motor constraints of older adults, thereby establishing a framework for quantitatively evaluating kiosk usability in advance. Methodologically, the Proximal Policy Optimization(PPO) reinforcement learning algorithm was employed to train user interaction policies. Based on real usage logs collected from older adults (N=9) at welfare centers in Seoul, behavioral parameters such as slow movement speed, hand tremors, and overshoot errors were modeled and incorporated into the simulation environment. Furthermore, to replace conventional observational studies, a novel “Gaze-path Visualization Technique” was proposed, which records gaze and click events as visual traces, enhancing the intuitiveness of log-based analysis. The results of this study present a pre-assessment framework that integrates the Gaze-path Visualization Technique with PPO reinforcement learning, while also implementing an LLM-based feedback module capable of generating intuitive UI/UX improvement guidelines and automated reports. Beyond merely ensuring regulatory compliance, this system defines practical usability as a core evaluation criterion, thereby significantly reducing pre-release risks and assessment costs. Ultimately, it offers a viable solution for promoting a culture of accessibility-centered quality management.

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[IEEE Style]

C. H. Seok, K. H. Seo, J. Y. Hwan, L. C. Eun, D. Yoo, "A Study on an AI Evaluation Model for Improving Kiosk Accessibility for the Elderly," The Transactions of the Korea Information Processing Society, vol. 14, no. 11, pp. 940-949, 2025. DOI: https://doi.org/10.3745/TKIPS.2025.14.11.940.

[ACM Style]

Choi Hyeon Seok, Kang Hyeon Seo, Ji Yu Hwan, Lim Chae Eun, and Dong-Young Yoo. 2025. A Study on an AI Evaluation Model for Improving Kiosk Accessibility for the Elderly. The Transactions of the Korea Information Processing Society, 14, 11, (2025), 940-949. DOI: https://doi.org/10.3745/TKIPS.2025.14.11.940.

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