EASE 2023
Tue 13 - Fri 16 June 2023 Oulu, Finland
Thu 15 Jun 2023 09:30 - 09:50 at Aurora Hall - Human Factors Chair(s): Rahul Mohanani

Background: 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. User experience is an important quality factor that has been primarily evaluated with classical measures (e.g. effectiveness, efficiency, satisfaction), but to a lesser extent with physiological measures, such as emotion recognition, skin response, or brain activity. Aim: 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. Method: We conducted a strict 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. Results: 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’ user experience ratings and the EEG signals, and a trend regarding performance has emerged from our analysis. Conclusions: These findings suggest that EEG signals could be used to evaluate user experience. 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.

Presentation (EASE Presentation.pptx)12.84MiB

Thu 15 Jun

Displayed time zone: Athens change

08:30 - 10:00
08:30
20m
Paper
Understanding self-efficacy in the context of Software Engineering: A qualitative study in the Industry.
Research (Full Papers)
Danilo Ribeiro Zup Innovation and SENAC University , Rayfran Lima SIDIA R&D Institute, César França Universidade Federal Rural de Pernambuco, Alberto de Souza Zup Innovation, Isadora Silva , Gustavo Pinto Federal University of Pará (UFPA) and Zup Innovation
Pre-print File Attached
08:50
10m
Short-paper
Barriers for Social Inclusion in Online Software Engineering Communities - A Study of Offensive Language Use in Gitter ProjectsShort Paper
Short Papers and Posters
Bastin Tony Roy Savarimuthu University of Otago, Dunedin, New Zealand, Zoofishan Zareen Independent Researcher, Jithin Cheriyan University of Otago, Muhammad Yasir university of otago, Matthias Galster University of Canterbury
Link to publication DOI Pre-print Media Attached File Attached
09:00
20m
Paper
Developers' Perception of GitHub Actions: A Survey Analysis
Research (Full Papers)
Pre-print File Attached
09:20
10m
Paper
Exploring the UK Cyber Skills Gap through a mapping of active job listings to the Cyber Security Body of Knowledge (CyBOK)
Vision and Emerging Results
Sam Attwood University of Central Lancashire, Ashley Williams Manchester Metropolitan University
Link to publication DOI Pre-print File Attached
09:30
20m
Paper
Measuring User Experience of Adaptive User Interfaces using EEG: A Replication Study
Research (Full Papers)
Daniel Gaspar Figueiredo Universitat Politècnica de València, Spain, Silvia Abrahão Universitat Politècnica de València, Emilio Insfran Universitat Politècnica de València, Spain, Jean Vanderdonckt Université catholique de Louvain
DOI Pre-print File Attached
09:50
10m
Short-paper
Replication and Extension of Schnappinger’s Study on Human-level Ordinal Maintainability Prediction Based on Static Code MetricsShort Paper
Short Papers and Posters
Sébastien Bertrand onepoint, Silvia Ciappelloni onepoint, Pierre-Alexandre Favier IMS UMR 5218, Jean-Marc André University of Bordeaux
Link to publication DOI File Attached