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Jun Kataoka – ProQuest LLC, 2024
This dissertation proposes novel Domain Adaptation (DA) methods in real-world industrial settings, where the availability of labeled data is limited and test data can significantly differ from training data. Particularly, our research addresses key challenges in DA, including the applicability of DA methods in industrial settings, strategies to…
Descriptors: Industry, Authentic Learning, Data, Training Methods
Coughlan, Tim – Educational Technology Research and Development, 2020
Open data has potential value as a material for use in learning activities. However, approaches to harnessing this are not well understood or in mainstream use in education. In this research, early adopters from a diverse range of educational projects and teaching settings were interviewed to explore their rationale for using open data in…
Descriptors: Data, Inquiry, Active Learning, Authentic Learning
Alastair D. Smith – Science & Education, 2025
Immersive virtual reality (VR) carries important potential, both for the creation of scientific knowledge and also for its communication. This is particularly important for studies of human spatial cognition, where psychologists now possess the power to combine the scale and fidelity of the real world with the malleability and control of the…
Descriptors: Computer Simulation, Spatial Ability, Cognitive Processes, Influence of Technology
Bowen, G. Michael; Bartley, Anthony – Science Activities: Projects and Curriculum Ideas in STEM Classrooms, 2020
School science is often very different from "real world" science. One important difference, and possibly the main one, is that in school science the relationships between variables have often been sanitized -- essentially "cleaned up" -- so that there is very little (and often no) variation in the data from the relationship…
Descriptors: Science Instruction, Data, Science Activities, Authentic Learning