TY - GEN
T1 - Enhancing VR Training
T2 - 2023 IEEE International Symposium on Mixed and Augmented Reality Adjunct, ISMAR-Adjunct 2023
AU - Rettinger, Maximilian
AU - Hug, Michael
AU - Kamel, Hassan
AU - Saxena, Yashita
AU - Rigoll, Gerhard
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Virtual reality holds significant potential for training applications, enabling users to access various training content easily, flexibly, and independently. However, the optimal approach for presenting training instructions and explanations within virtual reality remains an open question. Therefore, our research examines the effectiveness of different methods for transferring essential training information, such as instructions and explanations, to the user. In a study, we compared the following four information transfer modalities: 1) Audio (speech only), 2) Tablet (text-based information displayed on a tablet), 3) Mix (text on a tablet with supplementary speech), and 4) Overlay (text overlaid on the user's field of view). We conducted a within-subjects study as it yields more accurate results and allows the detection of weaker effects. Based on 44 participants, our findings demonstrate that the Mix method is significantly more effective compared to the three alternatives and is also rated as the preferred information transfer method. The knowledge gained from this research can be used to improve the effectiveness of future virtual reality training applications.
AB - Virtual reality holds significant potential for training applications, enabling users to access various training content easily, flexibly, and independently. However, the optimal approach for presenting training instructions and explanations within virtual reality remains an open question. Therefore, our research examines the effectiveness of different methods for transferring essential training information, such as instructions and explanations, to the user. In a study, we compared the following four information transfer modalities: 1) Audio (speech only), 2) Tablet (text-based information displayed on a tablet), 3) Mix (text on a tablet with supplementary speech), and 4) Overlay (text overlaid on the user's field of view). We conducted a within-subjects study as it yields more accurate results and allows the detection of weaker effects. Based on 44 participants, our findings demonstrate that the Mix method is significantly more effective compared to the three alternatives and is also rated as the preferred information transfer method. The knowledge gained from this research can be used to improve the effectiveness of future virtual reality training applications.
KW - Applied computing
KW - Education
KW - Human computer interaction (HCI)
KW - Human-centered computing
KW - Interaction paradigms
KW - Interactive learning
KW - Virtual reality
UR - http://www.scopus.com/inward/record.url?scp=85180367565&partnerID=8YFLogxK
U2 - 10.1109/ISMAR-Adjunct60411.2023.00111
DO - 10.1109/ISMAR-Adjunct60411.2023.00111
M3 - Conference contribution
AN - SCOPUS:85180367565
T3 - Proceedings - 2023 IEEE International Symposium on Mixed and Augmented Reality Adjunct, ISMAR-Adjunct 2023
SP - 513
EP - 518
BT - Proceedings - 2023 IEEE International Symposium on Mixed and Augmented Reality Adjunct, ISMAR-Adjunct 2023
A2 - Bruder, Gerd
A2 - Olivier, Anne-Helene
A2 - Cunningham, Andrew
A2 - Peng, Evan Yifan
A2 - Grubert, Jens
A2 - Williams, Ian
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 16 October 2023 through 20 October 2023
ER -