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Umut Zeki; Tolgay Karanfiller; Kamil Yurtkan – Education and Information Technologies, 2024
The developmental, characteristics and educational competencies of students who need special education are developing slowly in compared to their agemates. This is because their expressive language is different. In order to overcome these challenges, assistive technologies can be used under the supervision of the teachers. In this paper, a person…
Descriptors: Special Education, Expressive Language, Assistive Technology, Artificial Intelligence
Emerling, Christopher R.; Yang, Sohyun; Carter, Richard A.; Zhang, Ling; Hunt, Tiffany – TEACHING Exceptional Children, 2020
In response to the COVID-19 pandemic, school closures across the country have altered the way educators teach and provide services to students. Engaging technologies in learning environments have become the primary mechanism delivering curriculum and maintaining the intellectual wellbeing of students. With the accelerated expansion of technologies…
Descriptors: Technology Uses in Education, Artificial Intelligence, Distance Education, COVID-19
Gregory J. Heathco – Communication Teacher, 2025
University classrooms are increasingly populated by students with diverse nationalities and native languages (L1). The growing number of students in English-led classrooms who speak English as a second or lower language (L2) may face added difficulties in understanding the specific task objectives or directions, as explained by native-…
Descriptors: English (Second Language), Second Language Learning, Comparative Analysis, Language Processing
Crowston, Kevin; Ă˜sterlund, 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
What to Expect from Neural Machine Translation: A Practical In-Class Translation Evaluation Exercise
Moorkens, Joss – Interpreter and Translator Trainer, 2018
Machine translation is currently undergoing a paradigm shift from statistical to neural network models. Neural machine translation (NMT) is difficult to conceptualise for translation students, especially without context. This article describes a short in-class evaluation exercise to compare statistical and neural MT, including details of student…
Descriptors: Translation, Teaching Methods, Computational Linguistics, Quality Assurance
Goldstein, Ira P.; Miller, Mark L. – 1976
A unified theory of planning and debugging is explored by designing a problem solving program called PATN. PATN uses an augmented transition network (ATN) to represent a broad range of planning techniques, including identification, decomposition, and reformulation. (The ATN is a simple yet powerful formalism which has been effectively utilized in…
Descriptors: Artificial Intelligence, Computer Graphics, Computer Programs, Diagrams
Peer reviewedDuchastel, Philippe – Instructional Science, 1992
Examines the processes involved in building instructional systems that are based on artificial intelligence and hypermedia technologies. Traditional instructional systems design methodology is discussed; design issues including system architecture and learning strategies are addressed; and a new methodology for building knowledge-based…
Descriptors: Artificial Intelligence, Computer Assisted Instruction, Computer Software Development, Computer System Design

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