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Erschienen in:
2017 | Supplement | Buchkapitel
Better Later Than Ever: Comparative Analysis of Feedback Strategies in a Dynamic Intelligent Virtual Reality Training Environment for Child Pedestrians
verfasst von : Yecheng Gu, Sergey Sosnovsky
Erschienen in: Data Driven Approaches in Digital Education
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Abstract
Children require practical roadside training to learn safe pedestrian behaviour. However, problems associated with exercising on real roads greatly restrict the opportunities to provide such training. This paper presents the results of a study on an alternative approach for practical safety training using a combination of Intelligent Tutoring and Virtual Reality. In a classroom experiment, children of second and third grades worked on virtual road crossing exercises. They received instructions and feedback according to several different strategies. We have observed a high general acceptance for this form of training and compared effects of different feedback strategies on children’s’ performance. The delayed feedback strategy has been the most successful; its impact has been especially notable on more advanced pedestrian safety skills that are the most challenging for the children of the target age.