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Ahmad Chaddad; Yuchen Jiang – IEEE Transactions on Learning Technologies, 2025
The concept of the Metaverse, viewed as the ultimate manifestation of the Internet, has gained significant attention due to rapid advances in technologies such as the Internet of Things (IoT) and blockchain. Acting as a bridge between the physical and virtual worlds, the Metaverse has the potential to offer remarkable experiences to its users.…
Descriptors: Internet, Medical Education, Instructional Effectiveness, Artificial Intelligence
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
Gyeong-Geon Lee; Xiaoming Zhai – IEEE Transactions on Learning Technologies, 2024
While ongoing efforts have continuously emphasized the integration of ChatGPT with science teaching and learning, there are limited empirical studies exploring its actual utility in the classroom. This study aims to fill this gap by analyzing the lesson plans developed by 29 pre-service elementary teachers and assessing how they integrated ChatGPT…
Descriptors: Artificial Intelligence, Natural Language Processing, Science Education, Preservice Teachers
Yu Bai; Jun Li; Jun Shen; Liang Zhao – IEEE Transactions on Learning Technologies, 2024
The potential of artificial intelligence (AI) in transforming education has received considerable attention. This study aims to explore the potential of large language models (LLMs) in assisting students with studying and passing standardized exams, while many people think it is a hype situation. Using primary education as an example, this…
Descriptors: Instructional Effectiveness, Artificial Intelligence, Technology Uses in Education, Natural Language Processing
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
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
Martinez-Garcia, A.; Morris, S.; Tscholl, M.; Tracy, F.; Carmichael, P. – IEEE Transactions on Learning Technologies, 2012
This paper explores the potential of Semantic Web technologies to support teaching and learning in a variety of higher education settings in which some form of case-based learning is the pedagogy of choice. It draws on the empirical work of a major three year research and development project in the United Kingdom: "Ensemble: Semantic…
Descriptors: Foreign Countries, Program Descriptions, Teaching Methods, Instructional Innovation