User Experience with Adaptive User Interfaces: Comparing Performance and Preferences

[EN] Adaptive user interfaces dynamically change their content, presentation, and behavior to optimize the user experience, which has been primarily evaluated using classic usability measures but to a lesser extent by using neurological measures. While the perceived preference of specific user inter...

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Detalles Bibliográficos
Autores: Gaspar-Figueiredo, Daniel, Vanderdonckt, Jean, Abrahao Gonzales, Silvia Mara|||0000-0003-3580-2014, Insfran, Emilio|||0000-0003-0855-5564
Tipo de recurso: artículo
Fecha de publicación:2026
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/232121
Acceso en línea:https://riunet.upv.es/handle/10251/232121
Access Level:acceso abierto
Palabra clave:Adaptive systems
User interfaces
User experience
Electroencephalogram
Experiment
Descripción
Sumario:[EN] Adaptive user interfaces dynamically change their content, presentation, and behavior to optimize the user experience, which has been primarily evaluated using classic usability measures but to a lesser extent by using neurological measures. While the perceived preference of specific user interface elements, such as graphical adaptive menus, has already been studied, no consensus exists regarding their performance and how to substitute a static menu with an adaptive one. To gain insights into how graphical adaptive menus could influence the user experience and to identify any correlation between users¿ performance and their preferences, we conducted an experiment in which forty participants used twenty graphical adaptive menus while their brain activity was captured by employing electroencephalography to derive four measures (i.e., cog- nitive load, engagement, attraction, and memorization). User performance was measured using task completion time, specifically the time to select menu items. Statistical analysis suggested which graphical adaptive menus were significantly better or worse than the static menu, our baseline. These results are used as the basis to suggest implications for software developers and researchers to design more effective adaptive user interfaces.