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Misato Hiraga – ProQuest LLC, 2024
This dissertation developed a new learner corpus of Japanese and introduced an error and linguistic annotation scheme specifically designed for Japanese particles. The corpus contains texts written by learners who are in the first year to fourth year university level Japanese courses. The texts in the corpus were tagged with part-of-speech and…
Descriptors: Japanese, Computational Linguistics, Form Classes (Languages), Error Analysis (Language)
Arifi Waked; Muhammad W. Ashraf; Hanadi AbdelSalam; Khadija El Alaoui; Maura Pilotti – International Society for Technology, Education, and Science, 2024
Questions exist as to whether AI tools, such as ChatGPT, can aid learning. This study examined whether in-class exercises involving error detection in text generated by ChatGPT can aid students' foreign language writing. Participants were Arabic-English speakers who were classified as ranging from modest to competent English users according to…
Descriptors: Artificial Intelligence, Computer Software, Second Language Learning, Second Language Instruction
Mughaz, Dror; Cohen, Michael; Mejahez, Sagit; Ades, Tal; Bouhnik, Dan – Interdisciplinary Journal of e-Skills and Lifelong Learning, 2020
Aim/Purpose: Using Artificial Intelligence with Deep Learning (DL) techniques, which mimic the action of the brain, to improve a student's grammar learning process. Finding the subject of a sentence using DL, and learning, by way of this computer field, to analyze human learning processes and mistakes. In addition, showing Artificial Intelligence…
Descriptors: Artificial Intelligence, Teaching Methods, Brain Hemisphere Functions, Grammar