Piloting Multimodal Learning Analytics using Mobile Mixed Reality in Health Education

© 2019 IEEE. Mobile mixed reality has been shown to increase higher achievement and lower cognitive load within spatial disciplines. However, traditional methods of assessment restrict examiners ability to holistically assess spatial understanding. Multimodal learning analytics seeks to investigate how combinations of data types such as spatial data and traditional assessment can be combined to better understand both the learner and learning environment. This paper explores the pedagogical possibilities of a smartphone enabled mixed reality multimodal learning analytics case study for health education, focused on learning the anatomy of the heart. The context for this study is the first loop of a design based research study exploring the acquisition and retention of knowledge by piloting the proposed system with practicing health experts. Outcomes from the pilot study showed engagement and enthusiasm of the method among the experts, but also demonstrated problems to overcome in the pedagogical method before deployment with learners

Falls prevention advice and visual feedback to those at risk of falling : study protocol for a pilot randomized controlled trial

Studies have shown that functional strength and balance exercises can reduce the risk of falling in older people if they are done on a regular basis. However, the repetitive nature of these exercises; combined with the inherent lack of feedback of progress may discourage seniors from exercising in the home, thereby rendering such an intervention ineffective. This study hypothesizes that the use of visual feedback and multimodal games will be more effective in encouraging adherence to home rehabilitation than standard care; thereby promoting independence and improving the quality of life in older adults at risk of falling