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Showing 1 to 15 of 25 results Save | Export
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Hanxiang Du; Wanli Xing; Bo Pei – Interactive Learning Environments, 2023
Participating in online communities has significant benefits to students learning in terms of students' motivation, persistence, and learning outcomes. However, maintaining and supporting online learning communities is very challenging and requires tremendous work. Automatic support is desirable in this situation. The purpose of this work is to…
Descriptors: Electronic Learning, Communities of Practice, Automation, Artificial Intelligence
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Chenglu Li; Wanli Xing; Walter Leite – Interactive Learning Environments, 2024
As instruction shifts away from traditional approaches, online learning has grown in popularity in K-12 and higher education. Artificial intelligence (AI) and learning analytics methods such as machine learning have been used by educational scholars to support online learners on a large scale. However, the fairness of AI prediction in educational…
Descriptors: Artificial Intelligence, Prediction, Mathematics Achievement, Algorithms
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Soomaiya Hamid; Narmeen Zakaria Bawany – Interactive Learning Environments, 2024
E-learning is the process of sharing knowledge out of the traditional classrooms through different online tools using internet. The availability and use of these tools are not easy for every student. Many institutions gather e-learning feedback to know the problems of students to improve their systems. In e-learning systems, typically a high…
Descriptors: Feedback (Response), Electronic Learning, Automation, Classification
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Desheng Yan; Guangming Li – Interactive Learning Environments, 2024
Smart education, with its intelligent, individualized, and technologized content, represents people's lofty expectations for future education. It provides a good learning platform for teaching and an important environment in which students' digital learning power can be developed in the context of the information technology era. Digital learning…
Descriptors: Electronic Learning, Information Technology, Artificial Intelligence, Educational Environment
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Rosmansyah, Yusep; Putro, Budi Laksono; Putri, Atina; Utomo, Nur Budi; Suhardi – Interactive Learning Environments, 2023
In this article, smart learning environment (SLE) is defined as a hybrid learning system that provides learners and other stakeholders with a joyful learning process while achieving learning outcomes as a result of the employed intelligent tools and techniques. From literature study, existing SLE models and frameworks are difficult to understand…
Descriptors: Electronic Learning, Artificial Intelligence, Educational Technology, Technology Uses in Education
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Tayebeh Sargazi Moghadam; Ali Darejeh; Mansoureh Delaramifar; Sara Mashayekh – Interactive Learning Environments, 2024
Learners' emotional states might change during the learning process, and unpredictable variations of a person's emotions raise the demand for regular assessment of feelings during learning. In this paper, an AI-based decision framework is proposed and implemented for e-learning systems that identify suitable micro-brake activities based on the…
Descriptors: Artificial Intelligence, Decision Making, Electronic Learning, Psychological Patterns
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Çelikbilek, Yakup; Adigüzel Tüylü, Ayse Nur – Interactive Learning Environments, 2022
Institutions and universities have started using e-learning systems to reach the potential students from all over the world by decreasing costs of investments. The speed of technological developments increases the importance of e-learning systems and their technology-based components. E-learning systems also decrease the costs of both institutions…
Descriptors: Electronic Learning, Technology Uses in Education, Distance Education, Artificial Intelligence
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S. Sageengrana; S. Selvakumar; S. Srinivasan – Interactive Learning Environments, 2024
Students are termed "multitaskers," and it is likely that they easily fall prey to other subjects or topics that most interest them. They occasionally took heed or gave close and thoughtful attention to the lectures they were on. In the current educational system, our young generations receive materials from their leftovers, and their…
Descriptors: Electronic Learning, Dropouts, Student Behavior, Student Interests
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Shaofeng Wang; Huanhuan Wang; Yanshuang Jiang; Ping Li; Wancheng Yang – Interactive Learning Environments, 2023
The new era of technologies represented by artificial intelligence is profoundly reconstructing the field of education. The integration of emerging technologies in intelligent teaching provides new approaches for improving teaching effectiveness and enriching learning experiences. Today, we know little about students' participation in intelligent…
Descriptors: Artificial Intelligence, Student Centered Learning, Student Satisfaction, Student Participation
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Shruti Priya; Shubhankar Bhadra; Sridhar Chimalakonda; Akhila Sri Manasa Venigalla – Interactive Learning Environments, 2024
Owing to the predominant role of Machine Learning(ML) across domains, it is being introduced at multiple levels of education, including K-12. Researchers have leveraged games, augmented reality and other ways to make learning ML concepts interesting. However, most of the existing games to teach ML concepts either focus on use-cases and…
Descriptors: Artificial Intelligence, Secondary School Students, Video Games, Visual Aids
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Yun-Fang Tu; Gwo-Jen Hwang – Interactive Learning Environments, 2024
The present study employed the draw-a-picture technique and epistemic network analysis (ENA) to reveal university students' viewpoints on ChatGPT-supported learning, as well as the conceptions, roles, and educational objectives of ChatGPT-supported learning among university students with different learning attitudes. The results showed that…
Descriptors: College Students, Student Attitudes, Knowledge Level, Artificial Intelligence
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Mnasri, Sami; Habbash, Manssour – Interactive Learning Environments, 2023
Accent recognition refers to the problem of inferring the native language of a speaker from his foreign-accented speech. Differences in accent are due to both articulation and prosodic characteristics. The automatic identification of foreign accents is valuable for different speech systems, such as speech recognition, speaker identification or…
Descriptors: Arabic, Blended Learning, Artificial Intelligence, English (Second Language)
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Tang, Kai-Yu; Chang, Ching-Yi; Hwang, Gwo-Jen – Interactive Learning Environments, 2023
Artificial intelligence (AI) has been widely explored across the world over the past decades. A particularly emerging topic is the application of AI in e-learning (AIeL) to improve the effectiveness of teaching and learning in precision education. This study aims to systematically review publication patterns for AIeL research with a focus on…
Descriptors: Educational Trends, Trend Analysis, Artificial Intelligence, Technology Uses in Education
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Wan, Haipeng; Yu, Shengquan – Interactive Learning Environments, 2023
Most online learning researchers use resource recommendation and retrieve based on learning performance and learning style to provide accurate learning resources, but it is a closed and passive adaptive way. Learners always do not know the recommendation rationale and just receive the result-oriented recommended resources without having a chance…
Descriptors: Electronic Learning, Intelligent Tutoring Systems, Artificial Intelligence, Cognitive Mapping
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Laeeq, Kashif; Memon, Zulfiqar Ali – Interactive Learning Environments, 2021
The existing Learning Management Systems (LMSs) are profoundly effective in empowering the organization of e-learning, however, lacking in usability and learnability. The complex navigation and an immature search system are catalysing the issues that needs vigorous improvement. This paper aims to enhance the usability of LMSs by introducing an…
Descriptors: Integrated Learning Systems, Artificial Intelligence, Natural Language Processing, Information Retrieval
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