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Showing 1 to 15 of 36 results Save | Export
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Abdullah Al-Abri – Education and Information Technologies, 2025
This study explores the impact of ChatGPT, an advanced Large Language Model (LLM), as a virtual tutor in online education across five key dimensions: answering questions, writing assistance, study resources, exam preparation, and availability. Utilizing an experimental design, 68 undergraduate students from a public university interacted with…
Descriptors: Artificial Intelligence, Natural Language Processing, Man Machine Systems, Intelligent Tutoring Systems
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Jionghao Lin; Eason Chen; Zifei Han; Ashish Gurung; Danielle R. Thomas; Wei Tan; Ngoc Dang Nguyen; Kenneth R. Koedinger – International Educational Data Mining Society, 2024
Automated explanatory feedback systems play a crucial role in facilitating learning for a large cohort of learners by offering feedback that incorporates explanations, significantly enhancing the learning process. However, delivering such explanatory feedback in real-time poses challenges, particularly when high classification accuracy for…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Feedback (Response)
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Lianghai Chu – Education and Information Technologies, 2025
The rapid advancement of artificial intelligence (AI) technology has enabled the creation of digital human instructors with human-like visual and verbal characteristics. This study investigates the impact of human likeness on learner satisfaction within e-learning environments, drawing on the "Uncanny Valley" theory and the Experience…
Descriptors: Student Satisfaction, Computer Assisted Instruction, Electronic Learning, Artificial Intelligence
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Yuan Shen; Luzhen Tang; Huixiao Le; Shufang Tan; Yueying Zhao; Kejie Shen; Xinyu Li; Torsten Juelich; Qiong Wang; Dragan Gaševic; Yizhou Fan – British Journal of Educational Technology, 2025
Ethical considerations have become a central topic in education since artificial intelligence (AI) brought both great innovation and challenges to educational practices and systems. Values influence what we believe is morally right and guide how we behave ethically in different situations. However, there is limited empirical research on improving…
Descriptors: Artificial Intelligence, Man Machine Systems, Facilitators (Individuals), Ethics
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Promethi Das Deep; Yixin Chen – Higher Education Studies, 2025
The COVID-19 pandemic significantly disrupted higher education. The sudden and profound transformations it necessitated had a direct and negative impact on higher education students, as evidenced by the widely reported instances of academic disengagement, decreased motivation, and lower performance. This was often due to student burnout caused by…
Descriptors: COVID-19, Pandemics, Electronic Learning, Fatigue (Biology)
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Jin Mao; Baiyun Chen; Juhong Christie Liu – TechTrends: Linking Research and Practice to Improve Learning, 2024
The abrupt emergence and rapid advancement of generative artificial intelligence (AI) technologies, transitioning from research labs to potentially all aspects of social life, has brought a profound impact on education, science, arts, journalism, and every facet of human life and communication. The purpose of this paper is to recapitulate the use…
Descriptors: Artificial Intelligence, Technology Uses in Education, Educational Technology, Electronic Learning
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Aras Bozkurt; Ramesh C. Sharma – Asian Journal of Distance Education, 2024
This study explores the transformative potential of Generative AI (GenAI) and ChatBots in educational interaction, communication, and the broader implications of human-GenAI collaboration. By examining the related literature through data mining and analytical methods, the paper identifies three main research themes: the revolutionary role of…
Descriptors: Algorithms, Artificial Intelligence, Man Machine Systems, Technology Uses in Education
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Huixiao Le; Yuan Shen; Zijian Li; Mengyu Xia; Luzhen Tang; Xinyu Li; Jiyou Jia; Qiong Wang; Dragan Gaševic; Yizhou Fan – British Journal of Educational Technology, 2025
Understanding learners' preferences in educational settings is crucial for optimizing learning outcomes and experience. As artificial intelligence (AI) becomes increasingly integrated into educational contexts, it is crucial to understand learners' preferences between AI and human tutors to support their learning. While AI demonstrates growing…
Descriptors: Student Attitudes, Preferences, Electronic Learning, Artificial Intelligence
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Mehdi Darban – Education and Information Technologies, 2024
This study advances the understanding of Artificial Intelligence (AI)'s role, particularly that of conversational agents like ChatGPT, in augmenting team-based knowledge acquisition in virtual learning settings. Drawing on human-AI teams and anthropomorphism theories and addressing the gap in the literature on human-AI collaboration within virtual…
Descriptors: Artificial Intelligence, Influence of Technology, Group Instruction, Electronic Learning
Suarez, Susan R. – ProQuest LLC, 2022
This action research study's primary purpose was to explore student and instructor experiences of chatbot use in online and hybrid undergraduate English composition courses. This qualitative study used structured and open-ended survey questions, interviews, and chat transcripts to collect data. The collaboration process among researcher and…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Electronic Learning
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Wu, Jiun-Yu; Yang, Christopher C. Y.; Liao, Chen-Hsuan; Nian, Mei-Wen – Educational Technology & Society, 2021
This methodological-theoretical synergy provides an integrative framework of learning analytics through the development of the human-and-machine symbiotic reinforcement learning. The framework intends to address the challenges of the current learning analytics model, including a lack of internal validity, generalizability, immediacy,…
Descriptors: Learning Analytics, Electronic Learning, Man Machine Systems, Artificial Intelligence
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Philip Slobodsky; Mariana Durcheva – International Journal of Mathematical Education in Science and Technology, 2025
AI-based bots (ChatGPT) are capable of solving mathematics problems, and students often use them for homework preparation, self-learning, etc. This raises a number of didactical and technical questions: How can students submit assignments containing complex mathematical expressions using only a keyboard? How should mathematics errors in ChatGPT's…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Mathematics Instruction
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Tahir, Sidra; Hafeez, Yaser; Abbas, Muhammad Azeem; Nawaz, Asif; Hamid, Bushra – Education and Information Technologies, 2022
With the increase in Technology Enhanced Learning (TEL), the effective retrieval and availability of Learning Objects (LOs) for course designers is a significant concern. Text-based LOs can be accessed from structured LO repositories (LORs) and unstructured sources. Different LOR structures and semantically diversified LOs hinder the process of…
Descriptors: Man Machine Systems, Artificial Intelligence, Technology Uses in Education, Online Courses
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Héctor J. Pijeira-Díaz; Shashank Subramanya; Janneke van de Pol; Anique de Bruin – Journal of Computer Assisted Learning, 2024
Background: When learning causal relations, completing causal diagrams enhances students' comprehension judgements to some extent. To potentially boost this effect, advances in natural language processing (NLP) enable real-time formative feedback based on the automated assessment of students' diagrams, which can involve the correctness of both the…
Descriptors: Learning Analytics, Automation, Student Evaluation, Causal Models
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Khanyisile Twabu – Discover Education, 2025
This article proposes a novel conceptual framework that integrates Artificial Intelligence (AI) with Cognitive Load Theory (CLT) and the Cognitive Theory of Multimedia Learning (CTML) to enhance Open Distance eLearning (ODeL) systems. By bridging the gap between traditional cognitive theories and cutting-edge AI technologies, this framework…
Descriptors: Cognitive Processes, Difficulty Level, Multimedia Instruction, Artificial Intelligence
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