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Psychomotor abilities are typically taught in a physical learning environment since they require focused practice and techniques to be learned. However, the lack of feedback modalities in remote psychomotor training makes learning processes ineffective and inefficient and can impede the learner’s progress. In this paper, we propose an immersive learning system to facilitate direct multimodal feedback for psychomotor skills training. Moreover, survey data to measure the perceived effectiveness of each used feedback modality was collected and analyzed. We offer a theoretical feedback model and its practical implementation. Initial study results show promising effectiveness of the employed instruction and feedback modalities. This solution could facilitate the multimodal training of psychomotor skills in a time-efficient manner. More research needs to be conducted in order to further test the system.

Psychomotor abilities are typically taught in a physical learning environment since they require focusedpractice and techniques to be learned. However, the lack of feedback modalities in remote psychomotortraining makes learning processes ineffective and inefficient and can impede the learner’s progress.In this paper, we propose an immersive learning system to facilitate direct multimodal feedback forpsychomotor skills training. Moreover, survey data to measure the perceived effectiveness of each usedfeedback modality was collected and analyzed. We offer a theoretical feedback model and its practicalimplementation. Initial study results show promising effectiveness of the employed instruction andfeedback modalities. This solution could facilitate the multimodal training of psychomotor skills in atime-efficient manner. More research needs to be conducted in order to further test the system.

Some psychomotor tasks require students to perform a specific sequence of poses and motions. A natural teaching scheme for such tasks is to contrast a student’s execution to a teacher demonstration. However, this requires strategies to match the teacher demonstration of each motion to the student’s attempts and to identify differences between demonstration and attempt. In this paper, we investigate methods to automatically detect student attempts for poses with only a single correct teacher demonstration. We investigate relevance learning, prototype networks, and attention mechanisms to achieve a robust few-shot approach which generalizes across students. In an experiment with one teacher and 27 students performing a sequence of motion elements from the field of fitness and dance, we show that prototype networks combined with an attention mechanism perform best.

Learning psychomotor skills requires constant deliberate practice, typically hands-on training, which necessitates constant feedback from the mentor. This is, however, uncommon and typically ineffective in a remote setting. Modern immersive learning technologies enable the learners to completely get immersed in various learning situations in a way that feels like experiencing an authentic learning environment and thus, can be applicable in the psychomotor domain. In this paper, we present two students’ prototype examples, namely ”Yu and Mi” and ”Flowmotion”; immersive learning environments which are designed to help learners improve their psychomotor skills in the domains of humanrobotic interaction and sports.