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Showing 1 to 15 of 205 results Save | Export
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Jiahui Du; Khe Foon Hew; Long Zhang – Education and Information Technologies, 2025
Self-regulated learning (SRL) is a prerequisite for successful learning. However, studies have reported that many students struggle with self-regulation in online learning, indicating the need to provide students with additional support for SRL. This study adopted a design-based research methodology to iteratively design, implement, and evaluate…
Descriptors: Independent Study, Artificial Intelligence, Electronic Learning, Graduate Students
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Lanqin Zheng; Yunchao Fan; Bodong Chen; Zichen Huang; LeiGao; Miaolang Long – Education and Information Technologies, 2024
Online collaborative learning has been broadly applied in higher education. However, learners face many challenges in collaborating with one another and coregulating their learning, leading to low group performance. To address the gaps, this study proposed an artificial intelligence (AI)-enabled feedback and feedforward approach that not only…
Descriptors: Artificial Intelligence, Feedback (Response), Electronic Learning, Cooperative Learning
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Jinglei Yu; Shengquan Yu; Ling Chen – British Journal of Educational Technology, 2025
Video-based teacher online learning enables teachers to engage in reflective practice by watching others' classroom videos, providing peer feedback (PF) and reviewing others' work. However, the quality and reliability of PF often suffer due to variations in teaching proficiency among providers, which limits its usefulness for reviewers. To improve…
Descriptors: Artificial Intelligence, Peer Evaluation, Feedback (Response), Reflection
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Denchai Panket; Panita Wannapiroon; Prachyanun Nilsook – Higher Education Studies, 2024
This research aims to design an intelligent platform architecture for electronic asset supply chains for digital higher education and to evaluate the architecture of the intelligent platform for electronic asset supply chains for digital higher education. The sample group consists of evaluations of the intelligent platform architecture for the…
Descriptors: Supply and Demand, Information Management, Artificial Intelligence, Higher Education
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Yongyan Zhao; Jian Li – International Journal of Web-Based Learning and Teaching Technologies, 2024
The attention time of students studying in MOOC (Massive Open Online Courses) classroom was analyzed to optimize and further improve their performance. On this basis, a student class model based on convolutional neural networks (CNN) feature extraction was proposed. Through Pr (Adobe Premiere) technology, students' class videos were processed by…
Descriptors: Higher Education, MOOCs, Artificial Intelligence, Networks
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Waqas Khan; Saira Sohail; Muhammad Azam Roomi; Qasim Ali Nisar; Muhammad Rafiq – Education and Information Technologies, 2024
This study highlighted the role played by digitalization elements, such as information and communication technology (ICT) adoption, the social internet of things (IoT), and artificial intelligence (AI), in e-learning systems. It also examined the mediating role of digital literacy (DL) and pedagogical digital competence (PDC) and the potential…
Descriptors: Foreign Countries, Educational Technology, Artificial Intelligence, Technology Integration
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Milos Ilic; Goran Kekovic; Vladimir Mikic; Katerina Mangaroska; Lazar Kopanja; Boban Vesin – IEEE Transactions on Learning Technologies, 2024
In recent years, there has been an increasing trend of utilizing artificial intelligence (AI) methodologies over traditional statistical methods for predicting student performance in e-learning contexts. Notably, many researchers have adopted AI techniques without conducting a comprehensive investigation into the most appropriate and accurate…
Descriptors: Artificial Intelligence, Academic Achievement, Prediction, Programming
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Özbey, Muhammed; Kayri, Murat – Education and Information Technologies, 2023
In this study, the factors affecting the transactional distance levels of university students who continue their courses with distance education in the 2020-2021 academic years due to the COVID pandemic process were examined. Factors that affect transactional distance are modeled with Artificial Neural Networks, one of the data mining methods.…
Descriptors: College Students, Distance Education, Electronic Learning, Anxiety
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Ho Young Yoon; Seokmin Kang; Sungyeun Kim – Journal of Computer Assisted Learning, 2024
Background: Research into enhancing the effectiveness of information delivery in asynchronous video lectures remains sparse. This study analyzes the nonverbal teaching behaviours in asynchronous online videos, drawing comparisons between pre-service and in-service teachers (ITs). Objectives: This research primarily aims to juxtapose the nonverbal…
Descriptors: Asynchronous Communication, Video Technology, Lecture Method, Nonverbal Communication
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Amjad Islam Amjad; Sarfraz Aslam; Umaira Tabassum – European Journal of Education, 2024
Mobile learning (M-learning), ChatGPT and social media are integral to university education, improving accessibility, personalization and interactive engagement in the learning process. This paper aimed to investigate the role of M-learning, ChatGPT and social media in university students' academic performance. It was a cross-sectional…
Descriptors: Telecommunications, Handheld Devices, Electronic Learning, Social Media
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Nudrat Saleem; Tabish Mufti; Shahab Saquib Sohail; Dag Øivind Madsen – Cogent Education, 2024
In this study, we aim to investigate the potential advantages of integrating the new generative artificial intelligence (AI) technology, ChatGPT, into higher education, specifically within the field of medical education. The focus is on exploring ChatGPT's applications in personalized learning, assessment, and content creation while also…
Descriptors: Technology Uses in Education, Artificial Intelligence, Teaching Methods, Medical Education
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Orji, Fidelia A.; Vassileva, Julita – Journal of Educational Computing Research, 2023
There is a dearth of knowledge on how persuasiveness of influence strategies affects students' behaviours when using online educational systems. Persuasiveness is a term used in describing a system's capability to motivate desired behaviour. Most existing approaches for assessing the persuasiveness of a system are based on subjective measures…
Descriptors: Influences, Student Behavior, Artificial Intelligence, Electronic Learning
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Kgabo Bridget Maphoto; Kershnee Sevnarayan; Ntshimane Elphas Mohale; Zuleika Suliman; Tumelo Jacquiline Ntsopi; Douglas Mokoena – Open Praxis, 2024
This qualitative study explores the potential of generative artificial intelligence (AI) to improve the academic writing skills of a large student cohort within the context of a distance learning institution. Utilising qualitative methods, the research explores diverse approaches and applications of generative AI to elevate teaching and learning…
Descriptors: Foreign Countries, Distance Education, Electronic Learning, Artificial Intelligence
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Semih Sait Yilmaz; Ayse Collins; Seyid Amjad Ali – European Journal of Education, 2024
In response to the COVID-19 pandemic, an abrupt wave of digitisation and online migration swept the higher education institutions around the globe. In the aftermath of this digital transformation which endures as the legacy of the pandemic, what lacks in knowledge is how effective the anti-COVID measures were in maintaining quality education.…
Descriptors: Foreign Countries, Artificial Intelligence, Higher Education, COVID-19
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Natalie Patterson Mohr; Laura McNeill – International Journal on E-Learning, 2024
This multiple case analysis examines how AI ethics education's unique characteristics transform traditional e-learning approaches in synchronous and asynchronous environments. Through analysis of two contrasting cases -- Loyola Marymount University's synchronous workshops and Usher and Barak's asynchronous module -- the study investigates how…
Descriptors: Electronic Learning, Artificial Intelligence, Ethics, Values Education
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