Abstract
Today’s emerging technologies are moving in the direction of the human age. As technologies emerge in the educational setting, humans can evolve in the way they learn because of technology; and machines can evolve in the way they learn because of humans. Technology can be used to effectively observe and assesses human behaviors to better understand and respond to them. Whether the behaviors need to be adjusted or the behaviors are worth modeling, technology can provide support such as tools to track and collect data, assess performance, and provide meaningful feedback to the learner. In the human age of machine learning, the focus is less on technology and more on being human. To adapt to changing educational contexts, more effective applications of emerging technologies are needed. This paper explores the following novel applications of human-centered approaches to using technology in education: the quantified self, affective computing, emotional design, and pedagogical agents.
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Bacos, C.A. (2020). Machine Learning and Education in the Human Age: A Review of Emerging Technologies. In: Arai, K., Kapoor, S. (eds) Advances in Computer Vision. CVC 2019. Advances in Intelligent Systems and Computing, vol 944. Springer, Cham. https://doi.org/10.1007/978-3-030-17798-0_43
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