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Jionghao Lin; Wei Tan; Lan Du; Wray Buntine; David Lang; Dragan Gasevic; Guanliang Chen – IEEE Transactions on Learning Technologies, 2024
Automating the classification of instructional strategies from a large-scale online tutorial dialogue corpus is indispensable to the design of dialogue-based intelligent tutoring systems. Despite many existing studies employing supervised machine learning (ML) models to automate the classification process, they concluded that building a…
Descriptors: Classification, Dialogs (Language), Teaching Methods, Computer Assisted Instruction
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Yishen Song; Qianta Zhu; Huaibo Wang; Qinhua Zheng – IEEE Transactions on Learning Technologies, 2024
Manually scoring and revising student essays has long been a time-consuming task for educators. With the rise of natural language processing techniques, automated essay scoring (AES) and automated essay revising (AER) have emerged to alleviate this burden. However, current AES and AER models require large amounts of training data and lack…
Descriptors: Scoring, Essays, Writing Evaluation, Computer Software
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Liu, Ming; Rus, Vasile; Liu, Li – IEEE Transactions on Learning Technologies, 2018
Automatic question generation can help teachers to save the time necessary for constructing examination papers. Several approaches were proposed to automatically generate multiple-choice questions for vocabulary assessment or grammar exercises. However, most of these studies focused on generating questions in English with a certain similarity…
Descriptors: Multiple Choice Tests, Regression (Statistics), Test Items, Natural Language Processing
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Chen, Mei-Hua; Huang, Chung-Chi; Huang, Shih-Ting; Chang, Jason S.; Liou, Hsien-Chin – IEEE Transactions on Learning Technologies, 2014
Formulaic language is important to language acquisition; however, English language learners are often reported to have problems with formulaic expressions. Several lists of formulaic sequences have been proposed, mainly for developing teaching and testing materials. However, their limited numbers and insufficient usage information seem unable to…
Descriptors: Brain Hemisphere Functions, Chinese, College Freshmen, Language Usage
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Liu, Ming; Calvo, R. A.; Aditomo, A.; Pizzato, L. A. – IEEE Transactions on Learning Technologies, 2012
In this paper, we present a novel approach for semiautomatic question generation to support academic writing. Our system first extracts key phrases from students' literature review papers. Each key phrase is matched with a Wikipedia article and classified into one of five abstract concept categories: Research Field, Technology, System, Term, and…
Descriptors: Foreign Countries, Computer Assisted Instruction, Web 2.0 Technologies, Automation