Developing STEAM Using KINECT: A Case Study on Motion-Capture Functions

  • Hyung-Sook KimEmail author
  • Seong-Hee Chung
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 528)


The purpose of this study is to develop a science & art convergence STEAM program that can be experienced through the KINECT interactive activities integration of art based on knowledge of science & technology. The program is structured based on the educational content and textbooks from the current curricula for elementary, middle-, and high-school students. Based on this, we developed the four KINECT program using the motion capture function. By using STEAM with KINECT to promote interest in science, and by providing an entertaining way to learn about science, it is possible for students to be more creative and well-rounded. It is also expected that, because the program combines art with science in a novel way, it has the potential to be widely distributed in the 2016 semester.


STEAM KINECT Interactive arts Science Arts fusion program 


  1. 1.
    Joe, H.S., Kim, H., Heo, J.Y.: Understanding of fusion talent training(STEAM) through field application case. Korea Foundation for the Advancement of Science & Creativity, Issue Paper OR 2012-02-02 (2012)Google Scholar
  2. 2.
    Kim, H. S.: 2014 Fusion talent education(STEAM) program development result report. Inha University (2014)Google Scholar
  3. 3.
    Kim, J.H., Hong, S.Y.: A development of SMART teaching and learning model for ICT gifted education. J. Korean Soc. Gifted Talent. 12(2), 29–47 (2013)Google Scholar
  4. 4.
    Lim, H.S.: Smart education: Teach Smart. Human Science (2012)Google Scholar
  5. 5.
    Yakman, G.: STEAM education: an overview of creating a model of integrative education. In: Proceeding of PATT, pp. 335–358 (2008)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Department of Human Art and TechnologyInha UniversityIncheonKorea

Personalised recommendations