Abstract
Modern education stands to greatly benefit from technological advances, especially in Artificial Intelligence (AI), that aim to enable effective and personalized learning for all students. However, to improve learning for the majority of students, AI solutions may exclude those who are under-represented due to unique differences in their demographic background or cognitive abilities. Towards combating this issue, we propose a workshop that will initiate conversations about equity, diversity, and inclusion in educational technology research and development. The workshop invites papers from the AIED community about equitable and inclusive educational technology that supports diverse populations, with selected authors being invited to present their work. The workshop is structured around three stages of learning engineering - system design, experimental study, and data analysis - with informational presentations, guest speakers, paper presentations, and group discussions relevant to each stage. Through the participation of community members from multiple disciplines, we seek to formulate a framework for developing and assessing equitable and inclusive educational technology.
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Smolansky, A., Nguyen, H.A., Kizilcec, R.F., McLaren, B.M. (2023). Equity, Diversity, and Inclusion in Educational Technology Research and Development. In: Wang, N., Rebolledo-Mendez, G., Dimitrova, V., Matsuda, N., Santos, O.C. (eds) Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium and Blue Sky. AIED 2023. Communications in Computer and Information Science, vol 1831. Springer, Cham. https://doi.org/10.1007/978-3-031-36336-8_8
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DOI: https://doi.org/10.1007/978-3-031-36336-8_8
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