  Adaptive user interfaces have the advantage of being able to dynamically
change their aspect and/or behaviour depending on the characteristics of the
context of use, i.e. to improve user experience(UX). UX is an important quality
factor that has been primarily evaluated with classical measures but to a
lesser extent with physiological measures, such as emotion recognition, skin
response, or brain activity.In a previous exploratory experiment involving
users with different profiles and a wide range of ages, we analysed user
experience in terms of cognitive load, engagement, attraction and memorisation
when employing twenty graphical adaptive menus through the use of an
Electroencephalogram (EEG) device. The results indicated that there were
statistically significant differences for these four variables. However, we
considered that it was necessary to confirm or reject these findings using a
more homogeneous group of users.We conducted an operational internal
replication study with 40 participants. We also investigated the potential
correlation between EEG signals and the participants' user experience ratings,
such as their preferences.The results of this experiment confirm that there are
statistically significant differences between the EEG variables when the
participants interact with the different adaptive menus. Moreover, there is a
high correlation among the participants' UX ratings and the EEG signals, and a
trend regarding performance has emerged from our analysis.These findings
suggest that EEG signals could be used to evaluate UX. With regard to the menus
studied, our results suggest that graphical menus with different structures and
font types produce more differences in users' brain responses, while menus
which use colours produce more similarities in users' brain responses. Several
insights with which to improve users' experience of graphical adaptive menus
are outlined.

Human-Computer Interaction;Software Engineering