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Showing 1 to 15 of 114 results Save | Export
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Guomin Chen; Pengrun Chen; Ying Wang; Nan Zhu – Interactive Learning Environments, 2024
The paper describes the research of causal relationships between the factors of technological, organizational, environmental, and personal contexts and their influence on the development of learning intentions in potential students. Its purpose was to develop a mechanism for designing a public online educational resource platform based on the…
Descriptors: MOOCs, Electronic Learning, Design, Technology Uses in Education
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Razieh Safarifard; Masoud Gholamali Lavasani; Elaheh Hejazi; Fatemeh Narenji Thani – Knowledge Management & E-Learning, 2024
The pedagogy aspect of education has been the key factor influencing the effectiveness and quality of e-learning platforms. However, there is a lack of systematic review with an emphasis on the pedagogical aspect when it comes to e-learning in higher education. This research aims to systematically review seven major databases to identify the…
Descriptors: Electronic Learning, Higher Education, Journal Articles, Constructivism (Learning)
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Abdessamad Chanaa; Nour-eddine El Faddouli – Smart Learning Environments, 2024
The recommendation is an active area of scientific research; it is also a challenging and fundamental problem in online education. However, classical recommender systems usually suffer from item cold-start issues. Besides, unlike other fields like e-commerce or entertainment, e-learning recommendations must ensure that learners have the adequate…
Descriptors: Artificial Intelligence, Prerequisites, Metadata, Electronic Learning
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Safa Ridha Albo Abdullah; Ahmed Al-Azawei – International Review of Research in Open and Distributed Learning, 2025
This systematic review sheds light on the role of ontologies in predicting achievement among online learners, in order to promote their academic success. In particular, it looks at the available literature on predicting online learners' performance through ontological machine-learning techniques and, using a systematic approach, identifies the…
Descriptors: Electronic Learning, Academic Achievement, Grade Prediction, Data Analysis
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Nabila Khodeir; Fatma Elghannam – Education and Information Technologies, 2025
MOOC platforms provide a means of communication through forums, allowing learners to express their difficulties and challenges while studying various courses. Within these forums, some posts require urgent attention from instructors. Failing to respond promptly to these posts can contribute to higher dropout rates and lower course completion…
Descriptors: MOOCs, Computer Mediated Communication, Conferences (Gatherings), Models
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Kajal Mahawar; Punam Rattan – Education and Information Technologies, 2025
Higher education institutions have consistently strived to provide students with top-notch education. To achieve better outcomes, machine learning (ML) algorithms greatly simplify the prediction process. ML can be utilized by academicians to obtain insight into student data and mine data for forecasting the performance. In this paper, the authors…
Descriptors: Electronic Learning, Artificial Intelligence, Academic Achievement, Prediction
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Ahmed A. Alsayer; Jonathan Templin; Chris Niileksela; Bruce B. Frey – Education and Information Technologies, 2025
Prior research on the "Community of Inquiry" (CoI) framework has a limited amount of work which uses structural techniques to confirm the factorial structure of the CoI. The current study investigates the structural relationships among the three elements of the CoI framework (cognitive presence, teaching presence, and social presence),…
Descriptors: Communities of Practice, Inquiry, Online Courses, Educational Experience
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Danielle Kearns-Sixsmith – Mentoring & Tutoring: Partnership in Learning, 2024
Tutoring promotes student achievement, academic independence, and the reduction of anxiety. While ample studies support tutoring for enhancing student success, few address how to evaluate tutoring. This quandary led to research in building and testing a meta-model that identified the hallmarks of one-on-one high-quality online tutoring.…
Descriptors: Electronic Learning, Tutoring, Higher Education, Educational Quality
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Adil Boughida; Mohamed Nadjib Kouahla; Yacine Lafifi – Education and Information Technologies, 2024
In e-learning environments, most adaptive systems do not consider the learner's emotional state when recommending activities for learning difficulties, blockages, or demotivation. In this paper, we propose a new approach of emotion-based adaptation in e-learning environments. The system will allow recommendation resources/activities to motivate…
Descriptors: Psychological Patterns, Electronic Learning, Educational Environment, Models
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Ishfaq Majid; Y. Vijaya Lakshmi – Online Submission, 2024
The models of E-learning Readiness (ELR) are basically designed to understand the process of obtaining the basic information necessary for measuring ELR among participants. They help organizations to identify the requirements for designing, developing and implementing E-learning. These models not only help the organizations to identify the degree…
Descriptors: Electronic Learning, Models, Readiness, Content Analysis
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Irena Puji Luritawaty; Tatang Herman; Sufyani Prabawanto – Mathematics Teaching Research Journal, 2024
Critical thinking is a key transversal competency of the 21st century, but some students have difficulty, especially during the transition to online learning due to the COVID-19 pandemic. This study aims to identify epistemological obstacles in critical thinking related to proof, generalization, alternative answers, and problem-solving. This…
Descriptors: Critical Thinking, Electronic Learning, Epistemology, Mathematical Models
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Yujie Zhou; Ge Cao; Xiao-Liang Shen – Education and Information Technologies, 2024
Online learning communities play a crucial role in delivering high-quality courses to a large number of learners. However, to maintain an economically sustainable and constantly evolving online learning ecosystem, it is essential to create a virtuous cycle from knowledge production to knowledge consumption by charging learners to incentivize…
Descriptors: Electronic Learning, Economics, Sustainability, Models
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Shuanghong Shen; Qi Liu; Zhenya Huang; Yonghe Zheng; Minghao Yin; Minjuan Wang; Enhong Chen – IEEE Transactions on Learning Technologies, 2024
Modern online education has the capacity to provide intelligent educational services by automatically analyzing substantial amounts of student behavioral data. Knowledge tracing (KT) is one of the fundamental tasks for student behavioral data analysis, aiming to monitor students' evolving knowledge state during their problem-solving process. In…
Descriptors: Student Behavior, Electronic Learning, Data Analysis, Models
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Gamze Türkmen – Journal of Educational Computing Research, 2025
Explainable Artificial Intelligence (XAI) refers to systems that make AI models more transparent, helping users understand how outputs are generated. XAI algorithms are considered valuable in educational research, supporting outcomes like student success, trust, and motivation. Their potential to enhance transparency and reliability in online…
Descriptors: Artificial Intelligence, Natural Language Processing, Trust (Psychology), Electronic Learning
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Amine Hatun Atas; Zahide Yildirim – Educational Technology Research and Development, 2025
This study advances the emerging research on shared metacognition through the lens of the community of inquiry framework. It seeks components and utterances of the community of inquiry and shared metacognition in online collaborative learning environments to bring an instructional design model to the fore. A three-cycle design-based research…
Descriptors: Metacognition, Instructional Design, Models, Electronic Learning
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