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Showing 1 to 15 of 75 results Save | Export
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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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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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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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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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Patrick Bowers; Kelley Graydon; Tracii Ryan; Jey Han Lau; Dani Tomlin – Australasian Journal of Educational Technology, 2024
This study presents a scoping review of research on artificial intelligence (AI)- driven virtual patients (VPs) for communication skills training of healthcare students. We aimed to establish what is known about these emergent learning tools, to characterise their design and implementation into training programmes. The preferred reporting items…
Descriptors: Allied Health Occupations Education, Artificial Intelligence, Computer Simulation, College Students
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Benjamin Motz; Harmony Jankowski; Jennifer Lopatin; Waverly Tseng; Tamara Tate – Grantee Submission, 2024
Platform-enabled research services will control, manage, and measure learner experiences within that platform. In this paper, we consider the need for research services that examine learner experiences "outside" the platform. For example, we describe an effort to conduct an experiment on peer assessment in a college writing course, where…
Descriptors: Educational Technology, Learning Management Systems, Electronic Learning, Peer Evaluation
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Kuadey, Noble Arden; Mahama, Francois; Ankora, Carlos; Bensah, Lily; Maale, Gerald Tietaa; Agbesi, Victor Kwaku; Kuadey, Anthony Mawuena; Adjei, Laurene – Interactive Technology and Smart Education, 2023
Purpose: This study aims to investigate factors that could predict the continued usage of e-learning systems, such as the learning management systems (LMS) at a Technical University in Ghana using machine learning algorithms. Design/methodology/approach: The proposed model for this study adopted a unified theory of acceptance and use of technology…
Descriptors: Foreign Countries, College Students, Learning Management Systems, Student Behavior
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Gerd Kortemeyer; Wolfgang Bauer – Physical Review Physics Education Research, 2024
As a result of the pandemic, many physics courses moved online. Alongside, the popularity of Internet-based problem-solving sites and forums rose. With the emergence of large language models, another shift occurred. One year into the public availability of these models, how has online help-seeking behavior among introductory physics students…
Descriptors: Web Sites, Cheating, Artificial Intelligence, Electronic Learning
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Torres, José Saavedra; Heath, C. Edward – Marketing Education Review, 2023
This article investigates the usage of an AI bot app called RNMKRS PitchPerfector to teach the sales skills necessary to deliver a successful elevator pitch. In particular, we wanted to know if the use of this app could increase student self-efficacy toward this critical selling skill. To analyze if RNMKRS had a real impact on students' elevator…
Descriptors: Artificial Intelligence, Self Efficacy, Public Speaking, Speech Skills
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Roland Kiraly; Sandor Kiraly; Martin Palotai – Education and Information Technologies, 2024
Deep learning is a very popular topic in computer sciences courses despite the fact that it is often challenging for beginners to take their first step due to the complexity of understanding and applying Artificial Neural Networks (ANN). Thus, the need to both understand and use neural networks is appearing at an ever-increasing rate across all…
Descriptors: Artificial Intelligence, Computer Science Education, Problem Solving, College Faculty
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Qurtubi, Ahmad – Education Quarterly Reviews, 2022
A Smart Campus is a new educational paradigm developed in this study, and numerous changes are achieved in the sectors of technology, environment, management, education, mobility, life, security, and the university's economy. A smart campus is a way for institutions to compete in the industrial era 4.0. The smart campus system assists colleges in…
Descriptors: Foreign Countries, Educational Technology, Electronic Learning, Higher Education
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Jorge Carlos Sanabria-Zepeda; Pamela Geraldine Olivo-Montaño; Inna Artemova; Amadeo José Argüelles-Cruz – Journal of Technology and Science Education, 2024
This study proposes a narrative pedagogical model for creating and developing case studies that highlight the challenges and issues surrounding the megatrends of the Fourth Industrial Revolution, specifically "People and the Internet." This proposal, framed in an online learning environment, represents the second stage of an educational…
Descriptors: Educational Trends, Trend Analysis, Artificial Intelligence, Technology Uses in Education
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Yiwen Lin; Nia Nixon – International Journal of Artificial Intelligence in Education, 2024
The COVID-19 pandemic disrupted teaching and learning activities in higher education around the world. As universities shifted to remote instruction in response to the pandemic, it is important to learn how students engaged in learning during this challenging period. In this paper, we examined the changes in learners' social and cognitive presence…
Descriptors: COVID-19, Pandemics, Electronic Learning, Student Attitudes
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Jasin, Jamil; Ng, He Tong; Atmosukarto, Indriyati; Iyer, Prasad; Osman, Faiezin; Wong, Peng Yu Kelly; Pua, Ching Yee; Cheow, Wean Sin – Education and Information Technologies, 2023
Low student engagement and motivation in online classes are well-known issues many universities face, especially with distance education during the COVID-19 pandemic. The online environment makes it even harder for teachers to connect with their students through traditional verbal and nonverbal behaviours, further decreasing engagement. Yet,…
Descriptors: Artificial Intelligence, Synchronous Communication, Electronic Learning, Chemistry
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