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Showing 1 to 15 of 68 results Save | Export
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Xiang Feng; Keyi Yuan; Xiu Guan; Longhui Qiu – Interactive Learning Environments, 2024
Datasets are critical for emotion analysis in the machine learning field. This study aims to explore emotion analysis datasets and related benchmarks in online learning, since, currently, there are very few studies that explore the same. We have scientifically labeled the topic and nine-category emotion of 4715 comment texts in online learning…
Descriptors: MOOCs, Psychological Patterns, Artificial Intelligence, Prediction
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Gwo-Jen Hwang; Kai-Yu Tang; Yun-Fang Tu – Interactive Learning Environments, 2024
This study provides research-based evidence to profile: (1) the roles of artificial intelligence in nursing; (2) its research applications; and (3) the research trends for future study. On the basis of the PRISMA statement, a series of AI and nursing education related keywords from the literature were used to retrieve high-quality journal articles…
Descriptors: Foreign Countries, Nursing Education, Nursing, Nursing Research
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Andrew Kwok-Fai Lui; Sin-Chun Ng; Stella Wing-Nga Cheung – Interactive Learning Environments, 2024
The technology of automated short answer grading (ASAG) can efficiently process answers according to human-prepared grading examples. Computer-assisted acquisition of grading examples uses a computer algorithm to sample real student responses for potentially good examples. The process is critical for optimizing the grading accuracy of machine…
Descriptors: Grading, Computer Uses in Education, Educational Technology, Artificial Intelligence
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Mostafa Al-Emran – Interactive Learning Environments, 2024
The rapidly evolving digital landscape, punctuated by the emergence of artificial intelligence (AI) and immersive technologies, is poised to reshape learning environments dramatically. This study explores the potential use of ChatGPT, a state-of-the-art language model developed by OpenAI, in Metaverse learning environments. It sheds light on…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Opportunities
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Xiao Wen; Hu Juan – Interactive Learning Environments, 2024
To address three issues identified in previous research this study proposes a clustering-based MOOC dropout identification method and an early prediction model based on deep learning. The MOOC learning behavior of self-paced students was analyzed, and two well-known MOOC datasets were used for analysis and validation. The findings are as follows:…
Descriptors: MOOCs, Dropouts, Dropout Characteristics, Dropout Research
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Yingjie Liu; Qinglong Zhan; Wenping Zhao – Interactive Learning Environments, 2024
This paper presents a systematic review of the application models, affects, and performance outcomes of VR/AR in vocational education. The analysis is based on journal articles retrieved from renowned databases such as Web of Science, Scopus, and EBSCO, spanning from January 2000 to January 2022. It highlights the pedagogical value of VR/AR in…
Descriptors: Computer Simulation, Artificial Intelligence, Vocational Education, Technology Uses in Education
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Deneil D. Christian; Kenny A. Hendrickson; Ameeta Jadav – Interactive Learning Environments, 2024
Cameras may be viewed as an essential tool in online synchronous classes. They may give a sense of connectedness between the students and faculty. In fact, social presence is considered a vital factor in distance education. In our study, we examine faculty's perception of accepted reasons for students to turn off their cameras and perceived…
Descriptors: Video Technology, Electronic Learning, Synchronous Communication, College Faculty
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Mark Johnson; Rafiq Saleh – Interactive Learning Environments, 2024
Educational assessment is inherently uncertain, where physiological, psychological and social factors play an important role in establishing judgements which are assumed to be "absolute". AI and other algorithmic approaches to grading of student work strip-out uncertainty, leading to a lack of inspectability in machine judgement and…
Descriptors: Artificial Intelligence, Evaluation Methods, Technology Uses in Education, Man Machine Systems
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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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Jing Chen; Bei Fang; Hao Zhang; Xia Xue – Interactive Learning Environments, 2024
High dropout rate exists universally in massive open online courses (MOOCs) due to the separation of teachers and learners in space and time. Dropout prediction using the machine learning method is an extremely important prerequisite to identify potential at-risk learners to improve learning. It has attracted much attention and there have emerged…
Descriptors: MOOCs, Potential Dropouts, Prediction, Artificial Intelligence
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Kanwal Zahoor; Narmeen Zakaria Bawany – Interactive Learning Environments, 2024
Mobile application developers rely largely on user reviews for identifying issues in mobile applications and meeting the users' expectations. User reviews are unstructured, unorganized and very informal. Identifying and classifying issues by extracting required information from reviews is difficult due to a large number of reviews. To automate the…
Descriptors: Artificial Intelligence, Computer Oriented Programs, Courseware, Learning Processes
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Jaeho Jeon; Seongyong Lee; Seongyune Choi – Interactive Learning Environments, 2024
Chatbot research has received growing attention due to the rapid diversification of chatbot technology, as demonstrated by the emergence of large language models (LLMs) and their integration with automatic speech recognition. However, among various chatbot types, speech-recognition chatbots have received limited attention in relevant research…
Descriptors: Literature Reviews, Content Analysis, Second Language Learning, Artificial Intelligence
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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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Jiahong Su; Weipeng Yang – Interactive Learning Environments, 2024
The issue of Artificial Intelligence (AI) literacy is gaining popularity in the field of education. Most research on AI literacy has focused on primary, secondary, and higher education, and there has been limited examination of AI literacy programs in early childhood education. This study aimed to evaluate the impact of an eight-week AI literacy…
Descriptors: Foreign Countries, Artificial Intelligence, Technological Literacy, Early Childhood Education
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Zhongling Pi; Renjia Liu; Hongjuan Ling; Xingyu Zhang; Shuo Wang; Xiying Li – Interactive Learning Environments, 2024
A video lecture instructor exhibiting positive emotion has been shown to induce similar emotions in students, improving the students' motivation and increasing their attention, thus improving their learning performance. However, little systematic research exists on which specific design features with regards to the instructor can induce such…
Descriptors: Foreign Countries, Undergraduate Students, Nonverbal Communication, Affective Behavior
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