Acceptance of dance training system based on augmented reality and technology acceptance model (TAM)

Abstract

The advancement in Computer Vision (CV) has evolved drastically from image processing to object recognition, tracking video, restoration of images, three-dimensional (3D) pose recognition, and emotion analysis. These advancements have eventually led to the birth of Augmented Reality (AR) technology, which means embedding virtual objects into the real-world environment. The primary focus of this research was to solve the long-term learning retention and poor learning efficiency for mastering a dance skill through the AR technology based on constructivism learning theory, Dreyfus model and Technology Acceptance Model (TAM). The problem analysis carried out in this research had major research findings, in which the retention and learning efficiency of a dance training system were predominantly determined through the type of learning theory adopted, learning environment, training tools, skill acquisition technology and type of AR technique. Therefore, the influential factors for the user acceptance of AR-based dance training system (ARDTS) were based on quantitative analysis. These influential factors were determined to address the problem of knowledge gap on acceptance of AR-based systems for dance education through self-learning. The evaluation and testing were conducted to validate the developed and implemented ARDTS system. The Technology Acceptance Model (TAM) as the evaluation model and quantitative analysis was done with a research instrument that encompassed external and internal variables. TAM consisted of 37 items, in which six factors were used to assess the new developed ARDTS by the authors and its acceptability among 86 subjects. The current study had investigated the potential use of AR-based dance training system to promote a particular dance skill among a sample population with various backgrounds and interests. The obtained results support a general acceptance towards ARDTS among the users who are interested in exploring the cutting-edge technology of AR for gaining expertise in a dance skill.