Demo Data from EDBT 2026 / reviewers in the wild / expert
Sena Yildiz-Degirmenci
dblp:387/4177
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2024
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021Human-computer interaction and ubiquitous computing · 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 · 87% Human-AI interaction · 13% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Learning and educational technologies › literacy learning
data literacy education |
0.8 | 1 | 2024 | DataliVR: Transformation of Data Literacy Education through Virtual Reality with ChatGPT-Powered Enhancements · ISMAR 2024 |
Learning and educational technologies › immersive learning
virtual reality learning environment |
0.8 | 1 | 2024 | DataliVR: Transformation of Data Literacy Education through Virtual Reality with ChatGPT-Powered Enhancements · ISMAR 2024 |
Human-AI interaction › large language model interaction
LLM chatbot |
0.2 | 1 | 2024 | DataliVR: Transformation of Data Literacy Education through Virtual Reality with ChatGPT-Powered Enhancements · ISMAR 2024 |
Methods — techniques the papers use, named apart from their topics
large language model · 0.8gamification · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | DataliVR: Transformation of Data Literacy Education through Virtual Reality with ChatGPT-Powered EnhancementsabstractData literacy is essential in today’s data-driven world, emphasizing individuals’ abilities to effectively manage data and extract meaningful insights. However, traditional classroom-based educational approaches often struggle to fully address the multifaceted nature of data literacy. As education undergoes digital transformation, innovative technologies such as Virtual Reality (VR) offer promising avenues for immersive and engaging learning experiences. This paper introduces DataliVR, a pioneering VR application aimed at enhancing the data literacy skills of university students within a contextual and gamified virtual learning environment. By integrating Large Language Models (LLMs) like ChatGPT as a conversational artificial intelligence (AI) chatbot embodied within a virtual avatar, DataliVR provides personalized learning assistance, enriching user learning experiences. Our study employed an experimental approach, with chatbot availability as the independent variable, analyzing learning experiences and outcomes as dependent variables with a sample of thirty participants. Our approach underscores the effectiveness and user-friendliness of ChatGPT-powered DataliVR in fostering data literacy skills. Moreover, our study examines the impact of the ChatGPT-based AI chatbot on users’ learning, revealing significant effects on both learning experiences and outcomes. Our study presents a robust tool for fostering data literacy skills, contributing significantly to the digital advancement of data literacy education through cutting-edge VR and AI technologies. Moreover, our research provides valuable insights and implications for future research endeavors aiming to integrate LLMs (e.g., ChatGPT) into educational VR platforms. Hong Gao 0008, Haochuan Huai, Sena Yildiz-Degirmenci, Maria Bannert, Enkelejda Kasneci |
ISMAR | 3 |