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Jialun Pan; Zhanzhan Zhao; Dongkun Han – IEEE Transactions on Learning Technologies, 2025
Properly predicting students' academic performance is crucial for elevating educational outcomes in various disciplines. Through precise performance prediction, schools can quickly pinpoint students facing challenges and provide customized educational materials suited to their specific learning needs. The reliance on teachers' experience to…
Descriptors: Prediction, Academic Achievement, At Risk Students, Artificial Intelligence
Thi Thuy An Ngo; Thanh Tu Tran; Gia Khuong An; Phuong Thy Nguyen – IEEE Transactions on Learning Technologies, 2024
The growing prevalence of advanced generative artificial intelligence chatbots, such as ChatGPT, in the educational sector has raised considerable interest in understanding their impact on student knowledge and exploring effective and sustainable implementation strategies. This research investigates the influence of knowledge management factors on…
Descriptors: Artificial Intelligence, Educational Environment, Knowledge Management, Student Satisfaction
Hsu, Hao-Hsuan; Huang, Nen-Fu – IEEE Transactions on Learning Technologies, 2022
This article introduces Xiao-Shih, the first intelligent question answering bot on Chinese-based massive open online courses (MOOCs). Question answering is critical for solving individual problems. However, instructors on MOOCs must respond to many questions, and learners must wait a long time for answers. To address this issue, Xiao-Shih…
Descriptors: Foreign Countries, Artificial Intelligence, Online Courses, Natural Language Processing
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
Xuefan Li; Tingsong Li; Minjuan Wang; Sining Tao; Xiaoxu Zhou; Xiaoqing Wei; Naiqing Guan – IEEE Transactions on Learning Technologies, 2025
With the rapid advancement of generative artificial intelligence (GAI), its application in educational settings has increasingly become a focal point, particularly in enhancing students' analytical capabilities. This study examines the effectiveness of the ChatGPT prompt framework in improving text analysis skills among students, specifically…
Descriptors: Artificial Intelligence, Technology Uses in Education, High School Students, Foreign Countries
Jijian Lu; Ruxin Zheng; Zikun Gong; Huifen Xu – IEEE Transactions on Learning Technologies, 2024
Generative artificial intelligence (AI) has emerged as a noteworthy milestone and a consequential advancement in the annals of major disciplines within the domains of human science and technology. This study aims to explore the effects of generative AI-assisted preservice teaching skills training on preservice teachers' self-efficacy and higher…
Descriptors: Professional Development, Artificial Intelligence, Thinking Skills, Self Efficacy
Elizabeth Koh; Lishan Zhang; Alwyn Vwen Yen Lee; Hongye Wang – IEEE Transactions on Learning Technologies, 2024
Generative artificial intelligence (AI) has the potential to revolutionize teaching and learning applications. This article examines the word cloud, a toolkit often used to scaffold teaching and learning for reflection, critical thinking, and content learning. Addressing the issues in traditional word clouds, semantic word clouds have been…
Descriptors: Vocabulary, Visual Aids, Electronic Publishing, Word Frequency
Hu, Jie; Peng, Yi; Chen, Xiao – IEEE Transactions on Learning Technologies, 2023
The prevalence of information and communication technologies (ICTs) has brought about profound changes in the field of reading, resulting in a large and rapidly growing number of young digital readers. The article intends to identify key contextual factors that synergistically differentiate high and low performers, high and average performers, and…
Descriptors: Decoding (Reading), Educational Technology, Information Technology, Reading Skills
Holmes, Mike; Latham, Annabel; Crockett, Keeley; O'Shea, James D. – IEEE Transactions on Learning Technologies, 2018
Comprehension is an important cognitive state for learning. Human tutors recognize comprehension and non-comprehension states by interpreting learner non-verbal behavior (NVB). Experienced tutors adapt pedagogy, materials, and instruction to provide additional learning scaffold in the context of perceived learner comprehension. Near real-time…
Descriptors: Comprehension, Classification, Artificial Intelligence, Networks
Auerbach, Joshua E.; Concordel, Alice; Kornatowski, Przemyslaw M.; Floreano, Dario – IEEE Transactions on Learning Technologies, 2019
It has often been found that students appreciate hands-on work, and find that they learn more with courses that include a project than those relying solely on conventional lectures and tests. This type of project driven learning is a key component of "Inquiry-based learning" (IBL), which aims at teaching methodology as well as content by…
Descriptors: Active Learning, Inquiry, Robotics, Artificial Intelligence

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