Demo Data from VLDB 2026 / reviewers in the wild / expert
Assia Boukezzi
dblp:403/8013
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2025
0009-0002-5274-2594ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Human-computer interaction and pervasive computing
1 paper |
Learning and educational technologies · 39% Immersive interaction · 30% Human-robot interaction · 30% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Human-robot interaction
augmented feedback |
0.9 | 1 | 2025 | Mentor-Guided Learning in Immersive Virtual Environments: The Impact of Visual and Haptic Feedback on Skill Acquisition · IEEE Trans. Vis. Comput. Graph. 2025 |
Learning and educational technologies
skill acquisition |
0.9 | 1 | 2025 | Mentor-Guided Learning in Immersive Virtual Environments: The Impact of Visual and Haptic Feedback on Skill Acquisition · IEEE Trans. Vis. Comput. Graph. 2025 |
Immersive interaction
virtual reality |
0.9 | 1 | 2025 | Mentor-Guided Learning in Immersive Virtual Environments: The Impact of Visual and Haptic Feedback on Skill Acquisition · IEEE Trans. Vis. Comput. Graph. 2025 |
Methods — techniques the papers use, named apart from their topics
user study · 0.9NASA-TLX · 0.9
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Mentor-Guided Learning in Immersive Virtual Environments: The Impact of Visual and Haptic Feedback on Skill AcquisitionabstractIn the early stages of learning a technical skill, trainees require guidance from a mentor through augmented feedback to develop higher expertise. However, the impact of such feedback and the different modalities used to communicate it remain underexplored in immersive virtual environments (IVE). This paper presents a study in which 27 participants were divided into three groups to learn a tool manipulation trajectory in an IVE. Two experimental groups received guidance from an expert using visual and/or haptic augmented feedback, while the control group received no feedback. The results indicate that both experimental groups showed significantly greater improvement in tool trajectory performance than the control group from pre- to post-test, with no significant differences between them. Analysis of their learning curves revealed similar performance improvements in tool trajectory across trials, outperforming the control group. Additionally, the visual-haptic feedback condition was linked to lower task load in three out of six dimensions of the NASA-TLX and a higher perceived interdependence with the expert's actions. These findings suggest that augmented feedback from an expert enhances the learning of tool manipulation skills. Although adding haptic feedback did not lead to better learning outcomes compared to visual feedback alone, it did enhance the overall user experience. These results offer valuable insights for designing IVEs that support mentor-trainee interactions through augmented feedback. Flavien Lebrun, Cassandre Simon, Assia Boukezzi, Samir Otmane, Amine Chellali |
IEEE Trans. Vis. Comput. Graph. | 3 |