Technology-Based Embodied Learning (TBEL) is a hotspot in learning science. Several of these technologies are still in their infancy and their potential for impacting guitar learning and teaching may still to be fully harnessed and explored. These technologies include, but are not limited to online archives and communities, social media, apps and software, subscription-based services, augmented reality, virtual worlds, and digital games. Starting in the late 1990s, technological advancements and the diffusion of high-speed internet brought about technologies and social spaces that contributed to innovating guitar pedagogies and disrupting traditional approaches to teaching and learning the guitar. Specifically, the article discusses how learning to play guitar has evolved from formal teacher-student lessons in private and academic settings, to informal and self-guided forms of learning through books, magazines, and DVDs. This article offers a bird's-eye view of the evolution of guitar learning and pedagogy in the XX and XXI centuries, supported, and often propelled by emerging popular musical styles and new technologies. Finally, we discuss the positive effects of ChordAR on children’s learning and creativity and make suggestions for future AR games.
Minor pentatonic scale full#
The test results showed that children can master the method of playing the game through simple learning, ultimately correctly imitating C, G, and E chords, and experience full immersion in the game. We invited 12 children to participate in user experiments to test usability of ChordAR. Chord knowledge in music theory is presented to children through multichannels (kinesthetic, visual, auditory, etc.) situationally, to improve children’s learning efficiency and experience.
Meanwhile, multisource fusion perception of audio and touch is used, and the AI algorithm model is used to monitor physical events (cloud AI training and edge execution) and effectively realize intelligent services such as chord combination, melody perception, and control. In this paper, we improve the high-precision position and low delay interaction of AR recognition area through edge calculation, so as to enhance the immersion of children’s chord knowledge learning. In addressing these two goals, this work lays the foundation as well as plans for the future of human‐autonomy teams that augment team interactions using coordination‐based measures.Īugmented reality (AR) technology, with its unique immersive interactive experience of virtual reality integration, can show children abstract concepts and theories in an intuitive way. The second goal is to collate extant work on feedback and advance ideas for adaptive feedback systems that have potential to influence coordination in a way that can enhance the effectiveness of team interactions. Therefore, the first goal of the paper is to review approaches to coordination dynamics, identify current research gaps, and draw insights from other areas, such as social interaction, relationship science, and psychotherapy. A critical requirement to reach this potential is having the theoretical and empirical foundation from which to do so. Having the capacity to measure coordination in real time is quite promising as it provides the opportunity to provide adaptive feedback that may influence and regulate teams’ coordination patterns and, ultimately, drive effective team performance. However, while significant advancements have been made to better model and understand the dynamics of team interaction and its relationship with task performance, appropriate measures of team coordination and computational methods to detect changes in coordination have not yet been widely investigated. To support such complex interactions, recent efforts have worked toward the design of adaptive human‐autonomy teaming systems that can provide feedback in or near real time to achieve the desired individual or team results. Complex work in teams requires coordination across team members and their technology as well as the ability to change and adapt over time to achieve effective performance.
0 kommentar(er)
