The rapid adoption of generative AI tools in legal education has sparked debates on establishing norms for AI use. These tools assist in assignments, translating legal documents, and research. Smart classrooms, with intelligent tutoring and emotion recognition technology, enhance teaching and learning but also pose risks like system errors, algorithmic discrimination, and decision opacity. This article examines the construction and benefits of smart classrooms, real-world integration challenges, and the effectiveness and risks of facial recognition technology, especially for diverse learning styles. It concludes best practices and recommendations to mitigate risks and promote a secure, effective educational environment.
Andrejevic, M., & Selwyn, N. (2022). Facial Recognition . Polity Press.
Bala, N. (2020). The Danger of Facial Recognition in Our Children’s Classrooms. Duke Law & Technology Review, 18 , 249-267.
Bidwell, J., & Fuchs, H. (2011). Classroom Analytics: Measuring Student Engagement with Automated Gaze Tracking. Behavior Research Methods , 49, 113.
Bousquet, A. (2018). The Eye of War : Military Perception from the Telescope to the Drone . University of Minnesota Press. https://doi.org/10.5749/j.ctv6hp332
Chen, S., & Jin, Q. (2015). Multi-Modal Dimensional Emotion Recognition Using Recurrent Neural Networks. In Proceedings of the 5th International Workshop on Audio/Visual Emotion Challenge (pp. 49-56). ACM. https://doi.org/10.1145/2808196.2811638
Feferbaum, M., & Klafke, G. F. (2021). Prova na frente das câmeras? É hora de mudar o foco! | Estratégias para avaliação de estudantes em cursos mediados por tecnologia. In M. Murashima (Ed.), Experiências na educação mediada por tecnologias (pp. 364-383). FGV Editora.
Feferbaum, M., & Radomysler, C. N. (2021). Entre conexões e desconexões. Metodologias ativas e humanização como pilares de um ensino mediado por tecnologia. In M. Murashima (Ed.), Experiências na educação mediada por tecnologias (pp. 147-163). FGV Editora.
Ferguson, R. (2012). Learning Analytics: Drivers, Developments and Challenges. International Journal of Technology Enhanced Learning, 4, 304-317. https://doi.org/10.1504/ijtel.2012.051816
Gasser, U., & Mayer-Schönberger, V. (2024). Guardrails: Guiding Human Decisions in the Age of AI . Princeton University Press.
Gligoric, N., Uzelac, A., Krco, S., Kovacevic, I., & Nikodijevic, A. (2015). Smart Classroom System for Detecting Level of Interest a Lecture Creates in a Classroom. Journal of Ambient Intelligence and Smart Environments, 7, 271-284. https://doi.org/10.3233/ais-150303
Gu, Y. et al. (2016). Speech Emotion Recognition Using Voiced Segment Selection Algorithm. In Proceedings of the 22 nd European Conference on Artificial Intelligence (pp. 1682-1683). The Association for Computing Machinery.
Hartzog, W., & Selinger, E. (2018). Facial Recognition Is the Perfect Tool for Oppression . Medium. https://medium.com/@hartzog/facial-recognition-is-the-perfect-tool-for-oppression-bc2a08f0fe66
Kaur, A., Bhatia, M., & Stea, G. (2022). A Survey of Smart Classroom Literature. Education Sciences, 12, Article No. 86. https://doi.org/10.3390/educsci12020086
Kerkeni, L., Serrestou, Y., Mbarki, M., Raoof, K., & Mahjoub, M. A. (2017). A Review on Speech Emotion Recognition: Case of Pedagogical Interaction in Classroom. In 2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP) (pp. 1-7). IEEE. https://doi.org/10.1109/atsip.2017.8075575
Kim, Y., Soyata, T., & Behnagh, R. F. (2018). Towards Emotionally Aware AI Smart Classroom: Current Issues and Directions for Engineering and Education. IEEE Access, 6, 5308-5331. https://doi.org/10.1109/access.2018.2791861
Madiega, T., & Mildebrath, H. (2021). Regulating Facial Recognition in the EU . European Parliamentary Research Service, European Union. https://www.europarl.europa.eu/RegData/etudes/IDAN/2021/698021/EPRS_IDA(2021)698021_EN.pdf
Papamitsiou, Z., & Economides, A. A. (2016). Learning Analytics for Smart Learning Environments: A Meta-Analysis of Empirical Research Results from 2009 to 2015. In Learning, Design, and Technology (pp. 1-23). Springer International Publishing. https://doi.org/10.1007/978-3-319-17727-4_15-1
Patel, U. A., & Priya, S. (2014). Development of a Student Attendance Management System Using RFID and Face Recognition: A Review. International Journal of Advance Research in Computer Science and Management Studies , 2, 109-119.
Romero, C., & Ventura, S. (2013). Data Mining in Education. WIREs Data Mining and Knowledge Discovery, 3, 12-27. https://doi.org/10.1002/widm.1075
Saini, M. K., & Goel, N. (2021). How Smart Are Smart Classrooms? A Review of Smart Classroom Technologies. ACM Computing Surveys, 52, Article No. 130. https://doi.org/10.1145/3365757
Saltman, K. (2016). Scripted Bodies . Routledge.
Stark, L. (2019). Facial Recognition Is the Plutonium of AI. XRDS: Crossroads, the ACM Magazine for Students, 25, 50-55. https://doi.org/10.1145/3313129
Williamson, B. (2017). Big Data in Education . Sage.
Yang, S., & Chen, L. (2011). A Face and Eye Detection Based Feedback System for Smart Classroom. In Proceedings of 2011 International Conference on Electronic & Mechani cal Engineering and Information Technology (pp. 571-574). IEEE. https://doi.org/10.1109/emeit.2011.6023166
Yu, Y.-C., You, S.-C. D., & Tsai, D.-R. (2012). Social Interaction Feedback System for the Smart Classroom. In Proceedings of the 2012 IEEE International Conference on Consumer Electronics (ICCE) (pp. 500-501). IEEE.
Yuan, Q. (2022). Research on Classroom Emotion Recognition Algorithm Based on Visual Emotion Classification. Computational Intelligence and Neuroscience, 2022, Article ID: 6453499. https://doi.org/10.1155/2022/6453499
Zapalska, A. M., & Dabb, H. (2002). Learning Styles. Journal of Teaching in International Business, 13, 77-97. https://doi.org/10.1300/j066v13n03_06