arXiv subjects

Jean Vanderdonckt

Publications and source records attributed to Jean Vanderdonckt.

6 recordsLinked to original sources

arXiv2025

Context-aware Adaptive Visualizations for Critical Decision Making

Effective decision-making often relies on timely insights from complex visual data. While Information Visualization (InfoVis) dashboards can support this process, they rarely adapt to users' cognitive state, and less so in real time. We present Symbiotik, an intelligent, context-aware adaptive visualization system that leverages neurophysiological signals to estimate mental workload (MWL) and dynamically adapt visual dashboards using reinforcement learning (RL). Through a user study with 120 participants and three visualization types, we demonstrate that our approach improves task performance and engagement. Symbiotik offers a scalable, real-time adaptation architecture, and a validated methodology for neuroadaptive user interfaces.

cs.HC↗

arXiv2024

Pattern Recognition or Medical Knowledge? The Problem with Multiple-Choice Questions in Medicine

Large Language Models (LLMs) such as ChatGPT demonstrate significant potential in the medical domain and are often evaluated using multiple-choice questions (MCQs) modeled on exams like the USMLE. However, such benchmarks may overestimate true clinical understanding by rewarding pattern recognition and test-taking heuristics. To investigate this, we created a fictional medical benchmark centered on an imaginary organ, the Glianorex, allowing us to separate memorized knowledge from reasoning ability. We generated textbooks and MCQs in English and French using leading LLMs, then evaluated proprietary, open-source, and domain-specific models in a zero-shot setting. Despite the fictional content, models achieved an average score of 64%, while physicians scored only 27%. Fine-tuned medical models outperformed base models in English but not in French. Ablation and interpretability analyses revealed that models frequently relied on shallow cues, test-taking strategies, and hallucinated reasoning to identify the correct choice. These results suggest that standard MCQ-based evaluations may not effectively measure clinical reasoning and highlight the need for more robust, clinically meaningful assessment methods for LLMs.

cs.CL↗

arXiv2024

Awareness in robotics: An early perspective from the viewpoint of the EIC Pathfinder Challenge "Awareness Inside''

Consciousness has been historically a heavily debated topic in engineering, science, and philosophy. On the contrary, awareness had less success in raising the interest of scholars in the past. However, things are changing as more and more researchers are getting interested in answering questions concerning what awareness is and how it can be artificially generated. The landscape is rapidly evolving, with multiple voices and interpretations of the concept being conceived and techniques being developed. The goal of this paper is to summarize and discuss the ones among these voices connected with projects funded by the EIC Pathfinder Challenge called ``Awareness Inside'', a nonrecurring call for proposals within Horizon Europe designed specifically for fostering research on natural and synthetic awareness. In this perspective, we dedicate special attention to challenges and promises of applying synthetic awareness in robotics, as the development of mature techniques in this new field is expected to have a special impact on generating more capable and trustworthy embodied systems.

cs.RO↗

arXiv2023

Measuring User Experience of Adaptive User Interfaces using EEG: A Replication Study

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.

cs.HC↗

arXiv2023

Enabling Astronaut Self-Scheduling using a Robust Advanced Modelling and Scheduling system: an assessment during a Mars analogue mission

Human long duration exploration missions (LDEMs) raise a number of technological challenges. This paper addresses the question of the crew autonomy: as the distances increase, the communication delays and constraints tend to prevent the astronauts from being monitored and supported by a real time ground control. Eventually, future planetary missions will necessarily require a form of astronaut self-scheduling. We study the usage of a computer decision-support tool by a crew of analog astronauts, during a Mars simulation mission conducted at the Mars Desert Research Station (MDRS, Mars Society) in Utah. The proposed tool, called Romie, belongs to the new category of Robust Advanced Modelling and Scheduling (RAMS) systems. It allows the crew members (i) to visually model their scientific objectives and constraints, (ii) to compute near-optimal operational schedules while taking uncertainty into account, (iii) to monitor the execution of past and current activities, and (iv) to modify scientific objectives/constraints w.r.t. unforeseen events and opportunistic science. In this study, we empirically measure how the astronauts, who are novice planners, perform at using such a tool when self-scheduling under the realistic assumptions of a simulated Martian planetary habitat.

cs.RO↗

arXiv2004

Generative Programming of Graphical User Interfaces

Generative Programming (GP) is a computing paradigm allowing automatic creation of entire software families utilizing the configuration of elementary and reusable components. GP can be projected on different technologies, e.g. C++-templates, Java-Beans, Aspect-Oriented Programming (AOP), or Frame technology. This paper focuses on Frame Technology, which aids the possible implementation and completion of software components. The purpose of this paper is to introduce the GP paradigm in the area of GUI application generation. It demonstrates how automatically customized executable applications with GUI parts can be generated from an abstract specification.

cs.HC↗