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Yucheng Chu; Hang Li; Kaiqi Yang; Harry Shomer; Yasemin Copur-Gencturk; Leonora Kaldaras; Kevin Haudek; Joseph Krajcik; Namsoo Shin; Hui Liu; Jiliang Tang – International Educational Data Mining Society, 2025
Open-text responses provide researchers and educators with rich, nuanced insights that multiple-choice questions cannot capture. When reliably assessed, such responses have the potential to enhance teaching and learning. However, scaling and consistently capturing these nuances remain significant challenges, limiting the widespread use of…
Descriptors: Grading, Automation, Artificial Intelligence, Natural Language Processing
Dodigovic, Marina – International Journal of Artificial Intelligence in Education, 2013
This article focuses on the use of natural language processing (NLP) to facilitate second language learning within the context of academic English. It describes a full cycle of educational software development, from needs analysis to software testing. Two studies are included: 1) the needs analysis conducted to develop the Intelligent Sentence…
Descriptors: Intelligent Tutoring Systems, Natural Language Processing, Second Language Learning, English (Second Language)
Blanchard, Alexia; Kraif, Olivier; Ponton, Claude – CALICO Journal, 2009
This paper presents a "didactic triangulation" strategy to cope with the problem of reliability of NLP applications for computer-assisted language learning (CALL) systems. It is based on the implementation of basic but well mastered NLP techniques and puts the emphasis on an adapted gearing between computable linguistic clues and didactic features…
Descriptors: Spelling, Educational Technology, Natural Language Processing, Computer Assisted Instruction

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