Augmented Reality for Personalized Learning Technique: Climbing Gym Case Study

Gurieva, Natalia; Guryev, Igor; Pacheco Sánchez, Rosalba; Salazar Martínez, Elías

Center for Open Access in Science (COAS)
OPEN JOURNAL FOR INFORMATION TECHNOLOGY (OJIT)
ISSN (Online) 2620-0627 * ojit@centerprode.com

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2019 - Volume 2 - Number 2

Augmented Reality for Personalized Learning Technique: 'Climbing Gym' Case Study

Natalia Gurieva * n.gurieva@ugto.mx * ORCID: 0000-0002-1366-1292 * ResearcherID: AAF-8254-2019
University of Guanajuato, MEXICO

Igor Guryev
University of Guanajuato, MEXICO

Rosalba Pacheco Sánchez * r.pacheco.sanchez@ugto.mx * ORCID: 0000-0002-6337-673X
University of Guanajuato, MEXICO

Elías Salazar Martínez * e.salazarmartinez@ugto.mx * ORCID: 0000-0002-4491-8871
University of Guanajuato, MEXICO

Open Journal for Information Technology, 2019, 2(2), 21-34 * https://doi.org/10.32591/coas.ojit.0202.01021g
Online Published Date: 10 December 2019

LICENCE: Creative Commons Attribution 4.0 International License.

ARTICLE (Full Text - PDF)Augmented Reality for Personalized Learning Technique: Climbing Gym Case Study

KEY WORDS: personalized learning strategies, augmented reality, Kinect, educational applications, climbing.

ABSTRACT:
Augmented Reality is a technology that allows to expand the traditional learning techniques complementing the perception and interaction with the real world that allows the student to be in real environment with additional information generated by the computational algorithm. However, the knowledge and applicability of this technology in the field of personalized education is not a common practice. In this article, personalized education strategies are applied in the process of developing the application for indoor climbing teaching techniques. The application allows the trainer or climber to select the climbing holds that make up a route and display it by visualization on a projector to customize the training program. The system has the detection algorithm and recognition of climbing holds in real time and visualization of the route to climb. This kind of applications using emergent technologies oriented to personalized training has enormous potential for efficient education.

CORRESPONDING AUTHOR:
Natalia Gurieva, University of Guanajuato, Guanajuato, MEXICO. E-mail: n.gurieva@ugto.mx.

REFERENCES:

Ausubel, D. P., Novak, J. D., & Hanesian, H. (1983). Psicología educativa: un punto de vista cognoscitivo. México, Editorial Trillas.

Arnseth, H. Ch., & Silseth, K. (2013). Tracing learning and identity across sites: Tensions, connections and transformations in and between every day and institutional practices.

hapter of O. Erstad & J. Seftin-Green (Eds.): Identity, community, and learning lives in the digital age (pp. 23-38). Cambridge: Cambridge University Press.

Benson S. (2013). What is personalized learning? A working draft. Retrieved 1 October 2019, from https://scottebenson.wordpress.com/2013/08/06/what-is-personalized-learning/.

Boulanger, J., Seifert, L., Herault, R., & Coeurjolly, J.-F. (2016). Automatic sensor-based detection and classification of climbing activities. IEEE Sensors Journal, 16(3), 742-749.

Daiber, F., Kosmalla, F., & Krüger, A. (2013). BouldAR: Using augmented reality to support collaborative boulder training. CHI’13 Extended Abstracts on Human Factors in Computing Systems, pp. 949-954.

Chen, L., & Yang, Q. (2014). A group division method based on collaborative learning elements. In: The 26th Chinese control and decision conference (pp. 1701-1705). Changsha.

Collins, A., & Halverson, R. (2010). Rethinking education in the age of technology. The digital revolution and schooling in America. New York: Teachers College.

Kajastila, R. A., & Hämäläinen P. (2015). Motion games in real sports environments. Interactions, 22(2), 44-47.

Keefe, J. (1988). Aprendiendo Perfiles de Aprendizaje: manual de examinador, Reston, VA: Asociacion Nacional de Principal de Escuela de Secundaria.

Kim, J., & Chung, D. (2017). A climbing motion recognition method using anatomical information for screen climbing games. Human-centric Computing and Information Sciences, 7(1), p. 25.

Klopfer, E. (2008). Augmented learning: Research and design of mobile educational games. Cambridge, MA: MIT Press.

Kosmalla, F., Daiber, F., & Krüger, A. (2015). ClimbSense: Automatic climbing route recognition using wrist-worn inertia measurement units. In: Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, pp. 2033-2042.

Liljedahl, M., Lindberg, S., & Berg, J. (2005). Digiwall: An interactive climbing wall. Proceedings of the 2005 ACM SIGCHI International Conference on Advances in Computer Entertainment Technology, 2005, pp. 225-228.

Nitta, Y., & Murayama, Y. (2018). Software support for skeleton recognition and monitoring people with privacy. HICSS.

Phillips, C., Becker, L., & Bradley E., (2012). Strange beta: An assistance system for indoor rock climbing route setting. Chaos: An Interdisciplinary Journal of Nonlinear Science, 22(1).

Redondo, E., Fonseca, D., Sánchez, A., & Navarro, I. (2014). Mobile learning en el ámbito de la arquitectura y la edificación. Análi- sis de casos de estudio. Revista de Universidad y Sociedad del Conocimiento (RUSC), 11(1), 152-174.

Reinoso, R. (2012). Posibilidades de la realidad aumentada en educación. En J. Hernández, M. Pennesi, D. Sobrino & A. Vázquez (Coordinadores). Tendencias emergentes en educación con TIC (pp. 175-195). Barcelona: Editorial espiral.

Suzuki, S. et al. (1985). Topological structural analysis of digitized binary images by border following. Computer Vision, Graphics, and Image Processing, 30(1), 32-46.

Zamora-Musa, R., Vélez, J., & Villa, J. (2016). Contributions of collaborative and immersive environments in development a remote access laboratory: From point of view of effectiveness in learning. In: F. Mendes, R. de Souza & A. Sandro (Eds.), Handbook of Research on 3-D Virtual Environments and Hypermedia for Ubiquitous Learning, 1st ed. (pp. 1-28). Pennsylvania, USA: IGI Global.