TY - GEN
T1 - DataliVR
T2 - 23rd IEEE International Symposium on Mixed and Augmented Reality, ISMAR 2024
AU - Gao, Hong
AU - Huai, Haochuan
AU - Yildiz-Degirmenci, Sena
AU - Bannert, Maria
AU - Kasneci, Enkelejda
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Data 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.
AB - Data 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.
KW - ChatGPT
KW - data literacy
KW - digital transformation
KW - immersive learning
KW - LLMs
KW - Virtual reality
UR - http://www.scopus.com/inward/record.url?scp=85213525613&partnerID=8YFLogxK
U2 - 10.1109/ISMAR62088.2024.00026
DO - 10.1109/ISMAR62088.2024.00026
M3 - Conference contribution
AN - SCOPUS:85213525613
T3 - Proceedings - 2024 IEEE International Symposium on Mixed and Augmented Reality, ISMAR 2024
SP - 120
EP - 129
BT - Proceedings - 2024 IEEE International Symposium on Mixed and Augmented Reality, ISMAR 2024
A2 - Eck, Ulrich
A2 - Sra, Misha
A2 - Stefanucci, Jeanine
A2 - Sugimoto, Maki
A2 - Tatzgern, Markus
A2 - Williams, Ian
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 21 October 2024 through 25 October 2024
ER -