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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
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
R. K. Kapila Vani; P. Jayashree – Education and Information Technologies, 2025
Emotions of learners are fundamental and significant in e-learning as they encourage learning. Machine learning models are presented in the literature to look at how emotions may affect e-learning results that are improved and optimized. Nevertheless, the models that have been suggested so far are appropriate for offline mode, whereby data for…
Descriptors: Electronic Learning, Psychological Patterns, Artificial Intelligence, Models
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
Monsalve-Pulido, Julian; Aguilar, Jose; Montoya, Edwin – Education and Information Technologies, 2023
The adaptation of traditional systems to service-oriented architectures is very frequent, due to the increase in technologies for this type of architecture. This has led to the construction of frameworks or methodologies for adapting computational projects to service-oriented architecture (SOA) technology. In this work, a framework for adaptation…
Descriptors: Artificial Intelligence, Information Technology, Design, Governance
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
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
Remsh Nasser Alqahtani; Ahmad Zaid Almassaad – Education and Information Technologies, 2025
The aim of research is to reveal the effect of a training program based on the TAWOCK model for teaching computational thinking skills on teaching self-efficacy among computer teachers. It used the quasi-experimental approach, with a pre-test and post-test design with a control group. An electronic training program based on the TAWOCK model was…
Descriptors: Models, Teaching Methods, Computation, Thinking Skills
Robin Junker; Jennifer Janeczko; Alena Lehmkuhl; Verena Zucker; Manfred Holodynski; Nicola Meschede – Education and Information Technologies, 2025
The adoption of virtual learning environments (VLEs) in education has grown significantly due to their potential to enhance learning. Effective learning in VLEs depends on managing cognitive load and sustaining motivation, particularly for complex tasks like developing teachers' professional vision -- the ability to notice and interpret classroom…
Descriptors: Models, Prompting, Electronic Learning, Computer Simulation
Laila El-Hamamsy; Emilie-Charlotte Monnier; Sunny Avry; Morgane Chevalier; Barbara Bruno; Jessica Dehler Zufferey; Francesco Mondada – Education and Information Technologies, 2024
Sustaining changes in teachers' practices is a challenge that determines the success of curricular reforms, from which Digital Education (DE) is not exempt. As the literature on sustainability is considered "scarce" and "scattered", long-term studies modelling the factors impacting teachers' sustained uptake of DE pedagogical…
Descriptors: Faculty Development, Sustainability, Curriculum Development, Electronic Learning
Bellarhmouch, Youssra; Jeghal, Adil; Tairi, Hamid; Benjelloun, Nadia – Education and Information Technologies, 2023
Nowadays, the need for e-learning is amplified, especially after the COVID-19 pandemic. E-learning platforms present a solution for the continuity of the learning process. Learners are using different platforms and tools for learning. For this, it is necessary to model the learner for the personalization of the learning environment according to…
Descriptors: Electronic Learning, Educational Environment, Models, Individualized Instruction
Maha Salem; Khaled Shaalan – Education and Information Technologies, 2025
The proliferation of digital learning platforms has revolutionized the generation, accessibility, and dissemination of educational resources, fostered collaborative learning environments and producing vast amounts of interaction data. Machine learning (ML) algorithms have emerged as powerful tools for analyzing these complex datasets, uncovering…
Descriptors: Electronic Learning, Prediction, Models, Educational Technology
Xundiao Ma; Yueguang Xie; Xin Yang; Hanxi Wang; Jia Lu – Education and Information Technologies, 2024
Teacher-student interaction (TSI) is the core element and important teaching method of smart classroom. Improving the quality of smart classroom teaching and developing higher-order thinking (HOT) among students requires strengthening research on the TSI structure in smart classroom. At present, the structure model of TSI in smart classroom mainly…
Descriptors: Teacher Student Relationship, Interaction, Virtual Classrooms, Electronic Learning
Chen, Jihe; Zhou, Ying; Lv, Litian – Education and Information Technologies, 2023
This study aims to explore the significant variables affecting online knowledge-sharing and the hierarchical structure, from the perspective of online learners. To comprehensively discuss the relationship between these variables, binary logit regression and interpretative structural model (ISM) was used. Based on literature analysis, the data of…
Descriptors: Students, Electronic Learning, Sharing Behavior, Knowledge Level
Badal, Yudish Teshal; Sungkur, Roopesh Kevin – Education and Information Technologies, 2023
The outbreak of COVID-19 has caused significant disruption in all sectors and industries around the world. To tackle the spread of the novel coronavirus, the learning process and the modes of delivery had to be altered. Most courses are delivered traditionally with face-to-face or a blended approach through online learning platforms. In addition,…
Descriptors: Prediction, Models, Learning Analytics, Grades (Scholastic)

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