User-controlled Form Adaptation by Unsupervised Learning

Adaptive user interfaces; Adaptivity; Form design; User control; Adaptive user interface; Data items; Potential negative effects; Scoring functions; Systems and OR; Unsupervised learning method; Web environment; Human-Computer Interaction; Computer Networks and Communications; Computer Vision and Pattern Recognition; Software

Abstract :

[en] Forms are one of the most popular and widespread methods of interaction, yet they remain largely improper for adaptation. We argue that forms should be adapted to the user and their context in a controllable way, to minimize the potential negative effects of any adaptation. This can be accomplished with Scaler, a novel web environment for designing and deploying forms in which adaptation is initiated by the system and/or the user according to a vector profile, but always under the user’s control, using two unsupervised learning methods: (1) A scoring function that ranks the most usable widgets for each data item on the form, balancing the input and preferences of the stakeholders involved in the form (i.e., user, designer, and developer). (2) A widget recommendation that contrasts the user’s profile and those of all other users who have used the same form, whether they have modified it before or not. Our experiment with a car booking form shows that, after some interaction sessions (from 1 to 50 depending on the form field) and some user-controlled adaptations (from 3 to 29 depending on the field), the form design converged to a stabilized selection.

Disciplines :

Computer science

Author, co-author :

Eloi, Diego ; Université Catholique de Louvain, LouRIM, Louvain-la-Neuve, Belgium

Sahraoui, Alaa ; Université Catholique de Louvain, LouRIM, Louvain-la-Neuve, Belgium

Vanderdonckt, Jean ; Université Catholique de Louvain, LouRIM, Louvain-la-Neuve, Belgium

LEIVA, Luis A. ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)

External co-authors :

yes

Language :

English

Title :

User-controlled Form Adaptation by Unsupervised Learning

Publication date :

13 October 2024

Event name :

Adjunct Proceedings of the 2024 Nordic Conference on Human-Computer Interaction

Event place :

Uppsala, Swe

Event date :

13-10-2024 => 16-10-2024

Audience :

International

Main work title :

Adjunct Proceedings of the 13th Nordic Conference on Human-Computer Interaction, NordiCHI 2024

Publisher :

Association for Computing Machinery

ISBN/EAN :

9798400709654

Peer reviewed :

Peer reviewed

Additional URL :

https://dl.acm.org/doi/10.1145/3677045.3685431

European Projects :

HE - 101071147 - SYMBIOTIK - Context-aware adaptive visualizations for critical decision making

Funders :

European Union

Funding text :

This work is supported by the European Innovation Council Pathfinder-Awareness Inside challenge "Symbiotik" project (1 Oct. 2022-31 Dec. 2026) under Grant no. 101071147. We thank Nicolas Foret for his contributions to this work.

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