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Direct linkLi, Chenglu; Xing, Wanli; Leite, Walter – Grantee Submission, 2021
To support online learners at a large scale, extensive studies have adopted machine learning (ML) techniques to analyze students' artifacts and predict their learning outcomes automatically. However, limited attention has been paid to the fairness of prediction with ML in educational settings. This study intends to fill the gap by introducing a…
Descriptors: Learning Analytics, Prediction, Models, Electronic Learning
Ghallabi, Sameh; Essalmi, Fathi; Jemni, Mohamed; Kinshuk – Education and Information Technologies, 2020
With the emergence of technology, the personalization of e-learning systems is enhanced. These systems use a set of parameters for personalizing courses. However, in literature, these parameters are not based on classification and optimization algorithms to implement them in the cloud. Cloud computing is a new model of computing where standard and…
Descriptors: Electronic Learning, Internet, Information Storage, Models
Ifenthaler, Dirk, Ed.; Sampson, Demetrios G., Ed.; Isaías, Pedro, Ed. – Cognition and Exploratory Learning in the Digital Age, 2022
This book is about inclusivity and open education in the digital age. It reports the latest data on this topic from the 2021 Cognition and Exploratory Learning in the Digital Age (CELDA) conference. This annual conference focuses on challenges pertaining to the evolution of the learning process, the role of pedagogical approaches and the progress…
Descriptors: Teaching Methods, Educational Innovation, Educational Technology, Technology Uses in Education
