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Bihao Hu; Longwei Zheng; Jiayi Zhu; Lishan Ding; Yilei Wang; Xiaoqing Gu – IEEE Transactions on Learning Technologies, 2024
This study explores and analyzes the specific performance of large language models (LLMs) in instructional design, aiming to unveil their potential strengths and possible weaknesses. Recently, the influence of LLMs has gradually increased in multiple fields, yet exploratory research on their application in education remains relatively scarce. In…
Descriptors: Artificial Intelligence, Natural Language Processing, Instructional Design, Prompting
Areej ElSayary – Journal of Computer Assisted Learning, 2024
Background: The widespread use of information and communication technology (ICT) has led to significant changes in societal aspects, resulting in the emergence of a "knowledge society." However, students and teachers have faced challenges in adapting to this digitalization. In the United Arab Emirates (UAE), transitioning to a…
Descriptors: Teacher Attitudes, Artificial Intelligence, Information Technology, Barriers
Burstein, Jill; Shore, Jane; Sabatini, John; Moulder, Brad; Holtzman, Steven; Pedersen, Ted – ETS Research Report Series, 2012
In the United States, English learners (EL) often do not have the academic language proficiency, literacy skills, cultural background, and content knowledge necessary to succeed in kindergarten through 12th grade classrooms. This leads to large achievement gaps. Also, classroom texts are often riddled with linguistically unfamiliar elements,…
Descriptors: English Language Learners, Scaffolding (Teaching Technique), Educational Technology, Computer Oriented Programs