Paper Info
Title
Effects of correctness and suggestive feedback on learning with an autonomous virtual trainer
Abstract
In this paper we investigate interaction strategies for autonomous virtual trainers. Fourteen participants were immersed in our VR system to learn relative areas of countries by sorting virtual cubes. We evaluated two different feedback strategies used by the virtual trainer assisting participants. One provided Correctness Feedback at the end of each task, while the other provided Suggestive Feedback during the task. Correctness feedback was the most effective given that it received higher preference and led to shorter task completion time with equivalent performance outcomes.
Year
DOI
Venue
2019
10.1145/3308557.3308675
Proceedings of the 24th International Conference on Intelligent User Interfaces: Companion
Keywords
Field
DocType
feedback strategies, virtual agents, virtual reality
Trainer,Virtual reality,Computer science,Correctness,Sorting,Human–computer interaction,Task completion,Multimedia
Conference
ISBN
Citations 
PageRank 
978-1-4503-6673-1
0
0.34
References 
Authors
2
3
Name
Order
Citations
PageRank
Xiumin Shang100.34
Marcelo Kallmann263959.35
Ahmed Sabbir Arif39412.75