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FATE in MMLA: A Student-Centred Exploration of Fairness, Accountability, Transparency, and Ethics in Multimodal Learning Analytics
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Yueqiao Jin; Vanessa Echeverria; Lixiang Yan; Linxuan Zhao; Riordan Alfredo; Yi-Shan Tsai; Dragan Gasevic; Roberto Martinez-Maldonado – Journal of Learning Analytics, 2024
Multimodal learning analytics (MMLA) integrates novel sensing technologies and artificial intelligence algorithms, providing opportunities to enhance student reflection during complex, collaborative learning experiences. Although recent advancements in MMLA have shown its capability to generate insights into diverse learning behaviours across…
Descriptors: Learning Analytics, Accountability, Ethics, Artificial Intelligence
Artificial Intelligence for Supporting Human Cognition and Exploratory Learning in the Digital Age. Cognition and Exploratory Learning in the Digital Age
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Pedro Isaias, Editor; Demetrios G. Sampson, Editor; Dirk Ifenthaler, Editor – Cognition and Exploratory Learning in the Digital Age, 2024
The Cognition and Exploratory Learning in the Digital Age (CELDA) conference focuses on discussing and addressing the challenges pertaining to the evolution of the learning process, the role of pedagogical approaches and the progress of technological innovation, in the context of the digital age. In each edition, CELDA, gathers researchers and…
Descriptors: Artificial Intelligence, Cognitive Processes, Discovery Learning, Teaching Methods
Analytics of Learning Tactics and Strategies in an Online Learnersourcing Environment
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Lahza, Hatim; Khosravi, Hassan; Demartini, Gianluca – Journal of Computer Assisted Learning, 2023
Background: The use of crowdsourcing in a pedagogically supported form to partner with learners in developing novel content is emerging as a viable approach for engaging students in higher-order learning at scale. However, how students behave in this form of crowdsourcing, referred to as learnersourcing, is still insufficiently explored.…
Descriptors: Learning Analytics, Learning Strategies, Electronic Learning, Independent Study
Integration of Artificial Intelligence Performance Prediction and Learning Analytics to Improve Student Learning in Online Engineering Course
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Ouyang, Fan; Wu, Mian; Zheng, Luyi; Zhang, Liyin; Jiao, Pengcheng – International Journal of Educational Technology in Higher Education, 2023
As a cutting-edge field of artificial intelligence in education (AIEd) that depends on advanced computing technologies, AI performance prediction model is widely used to identify at-risk students that tend to fail, establish student-centered learning pathways, and optimize instructional design and development. A majority of the existing AI…
Descriptors: Technology Integration, Artificial Intelligence, Performance, Prediction
Towards the Future of Education: Cyber-Physical Learning
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Nachamma Sockalingam; Kenneth Lo; Judy Teo; Cheah Chin Wei; Danny Chow Jiun Jiet; Dorien Herremans; Melvin Lee Ming Jun; Oka Kurniawan; Yixiao Wang; Pey Kin Leong – Discover Education, 2025
Singapore University of Technology and Design (SUTD) is embarking on an educational innovation program called SUTD campusX to support its future of education. SUTD campusX aims to innovate new educational models, technology tools, and pedagogies for a new form of learning called "Cyber-Physical Learning", where the concept is that both…
Descriptors: Educational Trends, Educational Innovation, Educational Practices, Teaching Methods
Ethical and Pedagogical Challenges in the Integration of Artificial Intelligence into Lifelong Learning
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Amjad Almusaed; Asaad Almssad; Ammar K. Albaaj – International Society for Technology, Education, and Science, 2024
The impact of artificial intelligence (AI) on education and lifelong learning is a topic of significant importance as AI continues to change numerous sectors. This paper aims to critically examine AI's profound effect in these domains. The present research explores the ethical dilemmas and pedagogical approaches relevant to incorporating…
Descriptors: Ethics, Lifelong Learning, Artificial Intelligence, Computer Software