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Feng Hsu Wang – IEEE Transactions on Learning Technologies, 2024
Due to the development of deep learning technology, its application in education has received increasing attention from researchers. Intelligent agents based on deep learning technology can perform higher order intellectual tasks than ever. However, the high deployment cost of deep learning models has hindered their widespread application in…
Descriptors: Learning Processes, Models, Man Machine Systems, Cooperative Learning
Crowston, Kevin; Østerlund, Carsten; Lee, Tae Kyoung; Jackson, Corey; Harandi, Mahboobeh; Allen, Sarah; Bahaadini, Sara; Coughlin, Scott; Katsaggelos, Aggelos K.; Larson, Shane L.; Rohani, Neda; Smith, Joshua R.; Trouille, Laura; Zevin, Michael – IEEE Transactions on Learning Technologies, 2020
We present the design of a citizen science system that uses machine learning to guide the presentation of image classification tasks to newcomers to help them more quickly learn how to do the task while still contributing to the work of the project. A Bayesian model for tracking volunteer learning for training with tasks with uncertain outcomes is…
Descriptors: Citizen Participation, Scientific Research, Man Machine Systems, Training
Yang, Zongkai; Yang, Juan; Rice, Kerry; Hung, Jui-Long; Du, Xu – IEEE Transactions on Learning Technologies, 2020
This article proposes two innovative approaches, the one-channel learning image recognition and the three-channel learning image recognition, to convert student's course involvements into images for early warning predictive analysis. Multiple experiments with 5235 students and 576 absolute/1728 relative input variables were conducted to verify…
Descriptors: Distance Education, At Risk Students, Artificial Intelligence, Man Machine Systems

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