Design of Socioenactive Systems Based on Physiological Sensors and Robot Behavior in Educational Environments

Authors

  • Diego Addan Gonçalves Universidade Estadual de Campinas
  • Ricardo Edgard Caceffo Universidade Estadual de Campinas
  • José Armando Valente Universidade Estadual de Campinas
  • M. Cecilia C. Baranauskas Universidade Estadual de Campinas

DOI:

https://doi.org/10.5753/rbie.2021.2104

Keywords:

Pervasive systems, Educational Technology, Enactivism, Children Interaction, Socioenactive

Abstract

Computational systems based on ubiquitous and pervasive technology present several challenges related to the interaction of people with scenarios constituted by sensors and actuators, changing the mindset of what we used to understand as interaction with a computer.  This also has influence in the ways of considering the design of systems based on contemporary technology for the educational context. To cope with the challenges of ubiquitous computing, the concept of socioenactive system is being constructed as a system in which human and technological aspects are coupled together in a cycle of perceptually guided actions of people interacting with elements of the physical environment and with other people in the same scenario. In this work we address the design of a socioenactive system as an evolution of two previous systems designed and experimented with 5-year-old children in an educational context.   The contribution of this paper is twofold: 1. We present an analysis of two different systems tested in educational scenarios, pointing out the lack of elements that should be present in a complete cycle of socioenactive systems, suggesting requirements for a third system; 2. We present an architecture for the third system and a simulation of its usage. Results of the third system and its simulation inform the next activities of bringing it to real life in a practice proposed for the same audience and context as the previous systems. 

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Referências

Adams-Labonte, S. K. (2012). Daytime impairment due to college students’ technology use during sleep: Similarities to sleep apnea. [Poster presentation]. Meeting of the American Psychological Association, Orlando, FL. [GS Search]

Baranauskas, M. C. C. (2015). Socio-enactive systems: Investigating New Dimensions in the Design of Interaction Mediated by Information and Communication Technologies, FAPESP Thematic Research Project #2015/16528-0. [GS Search]

Baranauskas, M. C. C., Martins, M., & Valente, J. A. (2013). Codesign de redes digitais: tecnologia e educação a serviço da inclusão social. Porto Alegre: Penso, 2013. 304 p. ISBN 9788565848633. Número de chamada: 371.3078 C669. [GS Search]

Baranauskas, M. C. C., Mendoza, Y. L. M., & Duarte, E. F. (2021). Designing for a socioenactive experience: A case study in an educational workshop on deep time. International Journal of Child-Computer Interaction, 29, 100287. doi: 10.1016/j.ijcci.2021.100287 [GS Search]

Brady, K., Gwon, Y., Khorrami, P., Godoy, E., Campbell, Dagli, W. C., & Huang, T. S. (2016). Multi-Modal Audio, Video and Physiological Sensor Learning for Continuous Emotion Prediction. In Proceedings of the 6th International Workshop on Audio/Visual Emotion Challenge (AVEC’16) (pp. 97–104). ACM: New York, NY, USA. doi: 10.1145/2988257.2988264 [GS Search]

Brochado, R. A., & Carvalho, M. A. G. (2021). Revisão sistemática de estudos e aplicações de modelos pedagógicos diversificados. Revista Brasileira de Informática na Educação, 29, 718-745. ISSN 2317-6121. doi: 10.5753/rbie.2021.29.0.718 [GS Search]

Caceffo, R. Alves, E., Bonacin, R., dos Reis, J., Carbajal, M., D’Abreu, J. V., Brennand, C., Lombello, L., Valente, J. A., & Baranauskas, M. C. C. (2019). Collaborative Meaning Construction in socioenactive systems: Study with the mBot. In P. Zaphiris, A. Ioannou (eds.), Learning and Collaboration Technologies. Designing Learning Experiences. HCII 2019. Lecture Notes in Computer Science, vol 11590. Springer, Cham. doi: 10.1007/978-3-030-21814-0_18 [GS Search]

De Ruyter, B., & Van Dantzig, S. (2019). Ambient Lighting Atmospheres for Influencing Emotional Expressiveness and Cognitive Performance. In: I. Chatzigiannakis, B. De Ruyter, I. Mavrommati (eds.), Ambient Intelligence. AmI 2019. Lecture Notes in Computer Science, vol 11912. Springer, Cham. doi: 10.1007/978-3-030-34255-5_1 [GS Search]

Fortenbacher, A., Niels P., & Haeseon Y. (2017). [LISA] learning analytics for sensor-based adaptive learning. In Proceedings of the Seventh International Learning Analytics & Knowledge Conference (LAK’17) (pp. 592-593). ACM: New York, NY, USA. doi: 10.1145/3027385.3029476 [GS Search]

Gonçalves, D. A., Todt, E., & Cláudio, D. P. (2017). Landmark-based Facial Expression Parametrization for Sign Languages Avatar Animation. In Proceedings of the XVI Brazilian Symposium on Human Factors in Computing systems (IHC 2017) (pp. 1–6), Article 34. ACM: New York, NY, USA. doi: 10.1145/3160504.3160507 [GS Search]

Imamura, R. E. M., & Baranauskas, M. C. C. (2019). A framework for socio-enactive educational systems: linking learning, design, and technology. In Proceedings of the 18th Brazilian Symposium on Human Factors in Computing systems (IHC’19) (pp. 1-11), Article 1. ACM: New York, NY, USA. doi: 10.1145/3357155.3358443 [GS Search]

Jiménez, R., María, R., & Merino, S. (2017). Enactive and Embodied Learning In Higher Education. Functional Neurology, Rehabilitation, and Ergonomics, 7(45). [GS Search]

Kaipainen, M., Normak, P., Niglas, K., Kippar, J., & Laanpere, M. (2008). Soft ontologies, spatial representations and multi-perspective explorability. Expert systems, 25(5), 474–483. [GS Search]

Kaipainen, M., Ravaja, N., Tikka, P., Vuori, R., Pugliese, R., Rapino, M., & Takala, T. (2011). Enactive systems and enactive media: Embodied human-machine coupling beyond interfaces. Leonardo, 44(5), 433–438. [GS Search]

Larradet, F., Niewiadomski, R., Barresi, G., & Mattos, L. (2019). Appraisal theory-based mobile app for physiological data collection and labelling in the wild. In Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers (UbiComp/ISWC ’19 Adjunct) (pp. 752–756). ACM: New York, NY, USA. doi: 10.1145/3341162.3345595 [GS Search]

Lazar, J. et al. (2017). Research Methods in Human Computer Interaction, Morgan Kaufmann, 2017. [GS Search]

Lugmayr, A., & Stuart B. (2016). Free UX Testing Tool: The LudoVico UX Machine for Physiological Sensor Data Recording, Analysis, and Visualization for User Experience Design Experiments. In Proceedings of the SEACHI 2016 on Smart Cities for Better Living with HCI and UX (SEACHI 2016) (pp. 36-41). ACM: New York, NY, USA. doi: 10.1145/2898365.2899801 [GS Search]

Maturana, H. R., & Varela, F. J. (1992). "Afterword". The tree of knowledge: the biological roots of human understanding (Revised ed.). Shambhala Publications Inc. p. 255. ISBN 978-0877736424. [GS Search]

Rahim, A., Sagheer, A., Nadeem, K., Dar, M. N., Rahim, A., & Akram, U. (2019). Emotion Charting Using Real-time Monitoring of Physiological Signals. In 2019 International Conference on Robotics and Automation in Industry (ICRAI) (pp. 1-5), Rawalpindi, Pakistan, 2019. doi: 10.1109/ICRAI47710.2019.8967398 [GS Search]

Rodríguez, A., López, P. G., & Rossi., G. (2014). Sketching for designing enactive interactions. In Proceedings of the XV International Conference on Human Computer Interaction (Interacción’14) (pp. 1–2), Article 39. ACM: New York, NY, USA. doi: 10.1145/2662253.2662292 [GS Search]

Röggla, T., Najereh S., Zhiyuan Z., Alice P., & Pablo C. (2017). Enhancing Music Events Using Physiological Sensor Data. In Proceedings of the 25th ACM international conference on Multimedia (MM’17) (pp. 1239–1240). ACM: New York, NY, USA. doi: 10.1145/3123266.3127919 [GS Search]

Sichao, S., & Seiji, Y. (2018). Designing Expressive Lights and In-Situ Motions for Robots to Express Emotions. In Proceedings of the 6th International Conference on Human-Agent Interaction (HAI’18) (pp. 222–228). ACM: New York, NY, USA. doi: 10.1145/3284432.3284458 [GS Search]

Stamper, R., Liu K., Hafkamp, M., & Ades, Y. (2000). Understanding the roles of signs and norms in organizations-a semiotic approach to information systems design, Behaviour & Information Technology, 19(1), 15-27. doi: 10.1080/014492900118768 [GS Search]

Sun, M., Leite, I., Lehman, J. F., & Li, B. (2017). Collaborative storytelling between robot and child: A feasibility study. In Proceedings of the 2017 Conference on Interaction Design and Children (IDC’17) (pp. 205–214). ACM: New York, NY, USA. doi: 10.1145/3078072.3079714 [GS Search]

Valente, J. A., Caceffo, R., Bonacin, R., Gonçalves, D. A., Reis, J. C., & Baranauskas, M. C. C. (2021). Embodied-based Environment for Kindergarten Children: revisiting constructionist ideas. Accepted for publication in British Journal of Educational Technology, 52, 3. [GS Search]

Valente J. A., Caceffo, R., Moreira, E. A., Bonacin, R., Reis, J. C., Carbajal, M. L., D’abreu, J. V. V., Gonçalves, F. M., Brennand, C. V. L. T., & Baranauskas, M. C. C. (2020). A Robot-based Activity for Kindergarten Children: an embodied exercise. In Proceedings of Constructionism Conference 2020 (pp. 137-146), Dublin. ISBN: 978-1-911566-09-0. [GS Search]

Varela, F. J., Thompson, E., & Rosch, E. (1992). The embodied mind: Cognitive science and human experience. MIT Press. p. 9. ISBN 978-0262261234. [GS Search]

Wang, C., Röggla, T., & César, P. C. (2015). Analysing Audience Response to Performing Events: A Web Platform for Interactive Exploration of Physiological Sensor Data. In Proceedings of the 23rd ACM international conference on Multimedia (MM ’15) (pp. 749–750). ACM: New York, NY, USA. doi: 10.1145/2733373.2807976 [GS Search]

Weiser, M. (1999). The computer for the 21st century. SIGMOBILE Mob. Comput. Commun. Rev. 3(3), 3–11. doi: 10.1145/329124.329126 [GS Search]

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Published

2021-12-10

Como Citar

GONÇALVES, D. A.; CACEFFO, R. E.; VALENTE, J. A.; BARANAUSKAS, M. C. C. Design of Socioenactive Systems Based on Physiological Sensors and Robot Behavior in Educational Environments. Revista Brasileira de Informática na Educação, [S. l.], v. 29, p. 1356–1376, 2021. DOI: 10.5753/rbie.2021.2104. Disponível em: https://journals-sol.sbc.org.br/index.php/rbie/article/view/2104. Acesso em: 8 nov. 2024.

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