Approach of immersive adaptive learning for Virtual Reality simulator
Resumo
The need to improve teaching-learning processes promotes the development of Virtual Reality applications with adaptive learning approaches. Adaptive learning considers the premise that each person learns differently, at their own pace, considering the characteristics of the student. This paper describes the main components of an immersive adaptive learning approach for Virtual Reality simulators.
Palavras-chave:
Immersive adaptive learning, Virtual Reality, Simulator
Referências
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Chen, S., & Zhang, J. (2008). The Adaptive Learning System based on Learning Style and Cognitive State. Proceedings - 2008 International Symposium on Knowledge Acquisition and Modeling, KAM 2008. https://doi.org/10.1109/KAM.2008.60
Comas-González, Z., Echeverri-Ocampo, I., Zamora-Musa, R., Velez, J., Sarmiento, R., & Orellana, M. (2017). Tendencias recientes de la educación virtual y su fuerte conexión con los entornos inmersivos. Espacios.
Csikszentmihalyi, M., & Csikzentmihaly, M. (1990). Flow: The psychology of optimal experience (Vol. 1990). Harper & Row New York.
De Troyer, O., Kleinermann, F., & Ewais, A. (2010). Enhancing Virtual Reality Learning Environments with Adaptivity: Lessons Learned. https://doi.org/10.1007/978-3-642-16607-5_16
Drugan, M. M. (2019). Reinforcement learning versus evolutionary computation: A survey on hybrid algorithms. Swarm and Evolutionary Computation, 44, 228–246. https://doi.org/10.1016/j.swevo.2018.03.011
Kara, N., & Sevim, N. (2020). Adaptive Learning Systems: Beyond Teaching Machines. Contemporary Educational Technology. https://doi.org/10.30935/cedtech/6095
Lele, A. (2013). Virtual reality and its military utility. Journal of Ambient Intelligence and Humanized Computing. https://doi.org/10.1007/s12652-011-0052-4
Lemke, C. (2013). Intelligent Adaptive Learning: An Essential Element of 21st Century Teaching and Learning.
Li, G., Gomez, R., Nakamura, K., & He, B. (2019). Human-Centered Reinforcement Learning: A Survey. IEEE Transactions on Human-Machine Systems, 49(4), 337– 349. https://doi.org/10.1109/THMS.2019.2912447
Loch, F., Fahimipirehgalin, M., Czerniak, J. N., Mertens, A., Villani, V., Sabattini, L., … Vogel-Heuser, B. (2019). An Adaptive Virtual Training System Based on Universal Design. IFAC-PapersOnLine, 51(34), 335–340. https://doi.org/10.1016/j.ifacol.2019.01.023
Paramythis, A., & Loidl-Reisinger, S. (2004). Adaptive Learning Environments and e-Learning Standards. Electronic Journal of E-Learning.
Pfandler, M., Lazarovici, M., Stefan, P., Wucherer, P., & Weigl, M. (2017, September 1). Virtual reality-based simulators for spine surgery: a systematic review. Spine Journal, Vol. 17, pp. 1352–1363. https://doi.org/10.1016/j.spinee.2017.05.016
Real-Fernández, A., Molina-Carmona, R., Pertegal-Felices, M. L., & Llorens-Largo, F. (2019). Definition of a feature vector to characterise learners in adaptive learning systems. Springer Proceedings in Complexity, 75–89. https://doi.org/10.1007/978-3-030-30809-4_8
Rovira, A., & Slater, M. (2017). Reinforcement Learning as a tool to make people move to a specific location in Immersive Virtual Reality. International Journal of Human Computer Studies, 98, 89–94. https://doi.org/10.1016/j.ijhcs.2016.10.007
Sutton, R. S., & Barto, A. G. (2015). Reinforcement Learning: An Introduction Second edition, in progress.
Vaughan, N., Gabrys, B., & Dubey, V. N. (2016, November 1). An overview of self-adaptive technologies within virtual reality training. Computer Science Review, Vol. 22, pp. 65–87. https://doi.org/10.1016/j.cosrev.2016.09.001
Weber, G. (2012). Adaptive Learning Systems. In Encyclopedia of the Sciences of Learning (pp. 113–115). https://doi.org/10.1007/978-1-4419-1428-6_534
Wojtok, A. J., Bab, S., & Hirsch Martin. (2018, June). Adaptive learning in Virtual Reality: Current state and new approach. Retrieved from [link].
Zahabi, M., & Abdul Razak, A. M. (2020). Adaptive virtual reality-based training: a systematic literature review and framework. Virtual Reality, 1–28. https://doi.org/10.1007/s10055-020-00434-w
Chen, S., & Zhang, J. (2008). The Adaptive Learning System based on Learning Style and Cognitive State. Proceedings - 2008 International Symposium on Knowledge Acquisition and Modeling, KAM 2008. https://doi.org/10.1109/KAM.2008.60
Comas-González, Z., Echeverri-Ocampo, I., Zamora-Musa, R., Velez, J., Sarmiento, R., & Orellana, M. (2017). Tendencias recientes de la educación virtual y su fuerte conexión con los entornos inmersivos. Espacios.
Csikszentmihalyi, M., & Csikzentmihaly, M. (1990). Flow: The psychology of optimal experience (Vol. 1990). Harper & Row New York.
De Troyer, O., Kleinermann, F., & Ewais, A. (2010). Enhancing Virtual Reality Learning Environments with Adaptivity: Lessons Learned. https://doi.org/10.1007/978-3-642-16607-5_16
Drugan, M. M. (2019). Reinforcement learning versus evolutionary computation: A survey on hybrid algorithms. Swarm and Evolutionary Computation, 44, 228–246. https://doi.org/10.1016/j.swevo.2018.03.011
Kara, N., & Sevim, N. (2020). Adaptive Learning Systems: Beyond Teaching Machines. Contemporary Educational Technology. https://doi.org/10.30935/cedtech/6095
Lele, A. (2013). Virtual reality and its military utility. Journal of Ambient Intelligence and Humanized Computing. https://doi.org/10.1007/s12652-011-0052-4
Lemke, C. (2013). Intelligent Adaptive Learning: An Essential Element of 21st Century Teaching and Learning.
Li, G., Gomez, R., Nakamura, K., & He, B. (2019). Human-Centered Reinforcement Learning: A Survey. IEEE Transactions on Human-Machine Systems, 49(4), 337– 349. https://doi.org/10.1109/THMS.2019.2912447
Loch, F., Fahimipirehgalin, M., Czerniak, J. N., Mertens, A., Villani, V., Sabattini, L., … Vogel-Heuser, B. (2019). An Adaptive Virtual Training System Based on Universal Design. IFAC-PapersOnLine, 51(34), 335–340. https://doi.org/10.1016/j.ifacol.2019.01.023
Paramythis, A., & Loidl-Reisinger, S. (2004). Adaptive Learning Environments and e-Learning Standards. Electronic Journal of E-Learning.
Pfandler, M., Lazarovici, M., Stefan, P., Wucherer, P., & Weigl, M. (2017, September 1). Virtual reality-based simulators for spine surgery: a systematic review. Spine Journal, Vol. 17, pp. 1352–1363. https://doi.org/10.1016/j.spinee.2017.05.016
Real-Fernández, A., Molina-Carmona, R., Pertegal-Felices, M. L., & Llorens-Largo, F. (2019). Definition of a feature vector to characterise learners in adaptive learning systems. Springer Proceedings in Complexity, 75–89. https://doi.org/10.1007/978-3-030-30809-4_8
Rovira, A., & Slater, M. (2017). Reinforcement Learning as a tool to make people move to a specific location in Immersive Virtual Reality. International Journal of Human Computer Studies, 98, 89–94. https://doi.org/10.1016/j.ijhcs.2016.10.007
Sutton, R. S., & Barto, A. G. (2015). Reinforcement Learning: An Introduction Second edition, in progress.
Vaughan, N., Gabrys, B., & Dubey, V. N. (2016, November 1). An overview of self-adaptive technologies within virtual reality training. Computer Science Review, Vol. 22, pp. 65–87. https://doi.org/10.1016/j.cosrev.2016.09.001
Weber, G. (2012). Adaptive Learning Systems. In Encyclopedia of the Sciences of Learning (pp. 113–115). https://doi.org/10.1007/978-1-4419-1428-6_534
Wojtok, A. J., Bab, S., & Hirsch Martin. (2018, June). Adaptive learning in Virtual Reality: Current state and new approach. Retrieved from [link].
Zahabi, M., & Abdul Razak, A. M. (2020). Adaptive virtual reality-based training: a systematic literature review and framework. Virtual Reality, 1–28. https://doi.org/10.1007/s10055-020-00434-w
Publicado
21/03/2021
Como Citar
VEGA, Alieski Véliz; MADRIGAL, Omar Correa; KUGURAKOVA, Vlada.
Approach of immersive adaptive learning for Virtual Reality simulator. In: WORKSHOP ON ADVANCED VIRTUAL ENVIRONMENTS AND EDUCATION (WAVE), 3. , 2020, Fortaleza.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2021
.
p. 1-8.
DOI: https://doi.org/10.5753/wave.2020.211635.
