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Showing 1 to 15 of 19 results Save | Export
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Huang, Tao; Hu, Shengze; Yang, Huali; Geng, Jing; Liu, Sannyuya; Zhang, Hao; Yang, Zongkai – IEEE Transactions on Learning Technologies, 2023
The global outbreak of the new coronavirus epidemic has promoted the development of intelligent education and the utilization of online learning systems. In order to provide students with intelligent services, such as cognitive diagnosis and personalized exercises recommendation, a fundamental task is the concept tagging for exercises, which…
Descriptors: Educational Technology, Prediction, Electronic Learning, Intelligent Tutoring Systems
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Yujie Han; Sumin Hong; Zhenyan Li; Cheolil Lim – TechTrends: Linking Research and Practice to Improve Learning, 2025
This scoping review investigates the roles of intelligent learning companion systems (LCS) within educational settings, as well as the presences artificial intelligence (AI) embodies within these roles, and their application in education. Employing the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines for…
Descriptors: Artificial Intelligence, Definitions, Classification, Technology Uses in Education
Jia Tracy Shen; Michiharu Yamashita; Ethan Prihar; Neil Heffernan; Xintao Wu; Sean McGrew; Dongwon Lee – Grantee Submission, 2021
Educational content labeled with proper knowledge components (KCs) are particularly useful to teachers or content organizers. However, manually labeling educational content is labor intensive and error-prone. To address this challenge, prior research proposed machine learning based solutions to auto-label educational content with limited success.…
Descriptors: Mathematics Education, Knowledge Level, Video Technology, Educational Technology
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Heeg, Dagmar Mercedes; Avraamidou, Lucy – Educational Media International, 2023
Artificial Intelligence is widely used across contexts and for different purposes, including the field of education. However, a review of the literature showcases that while there exist various review studies on the use of AI in education, missing remains a review focusing on science education. To address this gap, we carried out a systematic…
Descriptors: Artificial Intelligence, Science Instruction, Educational Technology, Program Effectiveness
Steven Moore; John Stamper; Norman Bier; Mary Jean Blink – Grantee Submission, 2020
In this paper we show how we can utilize human-guided machine learning techniques coupled with a learning science practitioner interface (DataShop) to identify potential improvements to existing educational technology. Specifically, we provide an interface for the classification of underlying Knowledge Components (KCs) to better model student…
Descriptors: Learning Analytics, Educational Improvement, Classification, Learning Processes
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Liu, Ming; Rus, Vasile; Liu, Li – IEEE Transactions on Learning Technologies, 2017
Question generation is an emerging research area of artificial intelligence in education. Question authoring tools are important in educational technologies, e.g., intelligent tutoring systems, as well as in dialogue systems. Approaches to generate factual questions, i.e., questions that have concrete answers, mainly make use of the syntactical…
Descriptors: Chinese, Questioning Techniques, Automation, Natural Language Processing
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Janning, Ruth; Schatten, Carlotta; Schmidt-Thieme, Lars – International Journal of Artificial Intelligence in Education, 2016
Recognising students' emotion, affect or cognition is a relatively young field and still a challenging task in the area of intelligent tutoring systems. There are several ways to use the output of these recognition tasks within the system. The approach most often mentioned in the literature is using it for giving feedback to the students. The…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Technology Uses in Education, Educational Technology
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Troussas, Christos; Espinosa, Kurt Junshean; Virvou, Maria – Informatics in Education, 2016
Social networks are progressively being considered as an intense thought for learning. Particularly in the research area of Intelligent Tutoring Systems, they can create intuitive, versatile and customized e-learning systems which can advance the learning process by revealing the capacities and shortcomings of every learner and by customizing the…
Descriptors: Social Media, Educational Technology, Technology Uses in Education, Computer Software
Harsley, Rachel – International Association for Development of the Information Society, 2014
This paper presents a novel classification scheme for Collaborative Intelligent Tutoring Systems (CITS), an emergent research field. The three emergent classifications of CITS are unstructured, semi-structured, and fully structured. While all three types of CITS offer opportunities to improve student learning gains, the full extent to which these…
Descriptors: Intelligent Tutoring Systems, Classification, Instructional Effectiveness, Educational Technology
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Hwang, Gwo-Haur; Chen, Beyin; Huang, Cin-Wei – Educational Technology & Society, 2016
In recent years, with the gradual increase in the importance of professional certificates, improvement in certification tutoring systems has become more important. In this study, we have developed a personalized ubiquitous multi-device certification tutoring system (PUMDCTS) based on "Bloom's Taxonomy of Educational Objectives," and…
Descriptors: Electronic Learning, Educational Technology, Individualized Instruction, Certification
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Wolff, Annika; Mulholland, Paul; Zdrahal, Zdenek – Interactive Learning Environments, 2014
This paper describes an approach for supporting inquiry learning from source materials, realised and tested through a tool-kit. The approach is optimised for tasks that require a student to make interpretations across sets of resources, where opinions and justifications may be hard to articulate. We adopt a dialogue-based approach to learning…
Descriptors: Inquiry, Dialogs (Language), Feedback (Response), Web 2.0 Technologies
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Deliyska, Boryana; Manoilov, Peter – International Journal of Distance Education Technologies, 2010
The intelligent learning systems provide direct customized instruction to the learners without the intervention of human tutors on the basis of Semantic Web resources. Principal roles use ontologies as instruments for modeling learning processes, learners, learning disciplines and resources. This paper examines the variety, relationships, and…
Descriptors: Learning Processes, Intelligent Tutoring Systems, Curriculum Development, Lesson Plans
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Lavoue, Elise; George, Sebastien; Prevot, Patrick – Behaviour & Information Technology, 2012
In this article, we present a co-adaptive design approach named TE-Cap (Tutoring Experience Capitalisation) that we applied for the development of an assistance environment for tutors. Since tasks assigned to tutors in educational contexts are not well defined, we are developing an environment which responds to needs which are not precisely…
Descriptors: Foreign Countries, Tutors, Tutoring, College Faculty
Pontes, Elvis, Ed.; Silva, Anderson, Ed.; Guelfi, Adilson, Ed.; Kofuji, Sergio Takeo, Ed. – InTech, 2012
With the resources provided by communication technologies, E-learning has been employed in multiple universities, as well as in wide range of training centers and schools. This book presents a structured collection of chapters, dealing with the subject and stressing the importance of E-learning. It shows the evolution of E-learning, with…
Descriptors: Foreign Countries, Educational Technology, Virtual Classrooms, Program Effectiveness
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Hu, Xiangen, Ed.; Barnes, Tiffany, Ed.; Hershkovitz, Arnon, Ed.; Paquette, Luc, Ed. – International Educational Data Mining Society, 2017
The 10th International Conference on Educational Data Mining (EDM 2017) is held under the auspices of the International Educational Data Mining Society at the Optics Velley Kingdom Plaza Hotel, Wuhan, Hubei Province, in China. This years conference features two invited talks by: Dr. Jie Tang, Associate Professor with the Department of Computer…
Descriptors: Data Analysis, Data Collection, Graphs, Data Use
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