Learning selection-based augmented reality interactions across different training modalities: uncovering sex-specific...

Area of Science:

• Human-Computer Interaction
• Neuroscience
• Educational Technology

Background:

• Augmented reality (AR) offers new possibilities for various industries.
• Psychomotor learning is crucial for skill acquisition in many fields.
• Traditional training methods like video-based learning have limitations.

Purpose of the Study:

• To compare the effectiveness of psychomotor learning in augmented reality (AR) versus video-based training.
• To evaluate differences in performance, subjective workload, and neural efficiency between AR and video training groups.

Main Methods:

• Thirty-three participants were divided into two groups: AR training and video-based training.
• Participants learned four selection-based AR interactions.
• Performance was evaluated by executing learned interactions in AR, with brain activity measured using functional near-infrared spectroscopy (fNIRS).

Main Results:

• The AR group experienced higher subjective workload during training but achieved significantly faster evaluation completion times.
• fNIRS analysis revealed more efficient brain networks in participants trained with AR, indicating improved neural efficiency.
• Sex-based differences in brain activation and connectivity were observed, suggesting varied neural strategies.

Conclusions:

• AR-based training can lead to enhanced psychomotor learning and improved neural efficiency compared to traditional video methods.
• AR training may offer a more effective approach for skill acquisition, despite potentially higher initial cognitive load.
• Future research should explore demographic influences on AR training effectiveness and user experience.