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Perikos, Isidoros; Grivokostopoulou, Foteini; Hatzilygeroudis, Ioannis – International Journal of Artificial Intelligence in Education, 2017
Logic as a knowledge representation and reasoning language is a fundamental topic of an Artificial Intelligence (AI) course and includes a number of sub-topics. One of them, which brings difficulties to students to deal with, is converting natural language (NL) sentences into first-order logic (FOL) formulas. To assist students to overcome those…
Descriptors: Intelligent Tutoring Systems, Feedback (Response), Natural Language Processing, Logical Thinking
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Johnson, Amy M.; McCarthy, Kathryn S.; Kopp, Kristopher J.; Perret, Cecile A.; McNamara, Danielle S. – Grantee Submission, 2017
Intelligent tutoring systems for ill-defined domains, such as reading and writing, are critically needed, yet uncommon. Two such systems, the Interactive Strategy Training for Active Reading and Thinking (iSTART) and Writing Pal (W-Pal) use natural language processing (NLP) to assess learners' written (i.e., typed) responses and provide immediate,…
Descriptors: Reading Instruction, Writing Instruction, Intelligent Tutoring Systems, Reading Strategies
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Suleman, Raja M.; Mizoguchi, Riichiro; Ikeda, Mitsuru – International Journal of Artificial Intelligence in Education, 2016
Negotiation mechanism using conversational agents (chatbots) has been used in Open Learner Models (OLM) to enhance learner model accuracy and provide opportunities for learner reflection. Using chatbots that allow for natural language discussions has shown positive learning gains in students. Traditional OLMs assume a learner to be able to manage…
Descriptors: Metacognition, Intelligent Tutoring Systems, Natural Language Processing, Models
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Lintean, Mihai; Rus, Vasile; Azevedo, Roger – International Journal of Artificial Intelligence in Education, 2012
This article describes the problem of detecting the student mental models, i.e. students' knowledge states, during the self-regulatory activity of prior knowledge activation in MetaTutor, an intelligent tutoring system that teaches students self-regulation skills while learning complex science topics. The article presents several approaches to…
Descriptors: Semantics, Intelligent Tutoring Systems, Prior Learning, Mathematics
Benjamin D. Nye; Arthur C. Graesser; Xiangen Hu – Grantee Submission, 2014
AutoTutor is a natural language tutoring system that has produced learning gains across multiple domains (e.g., computer literacy, physics, critical thinking). In this paper, we review the development, key research findings, and systems that have evolved from AutoTutor. First, the rationale for developing AutoTutor is outlined and the advantages…
Descriptors: Intelligent Tutoring Systems, Natural Language Processing, Computer Software, Artificial Intelligence
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Benjamin D. Nye; Arthur C. Graesser; Xiangen Hu – International Journal of Artificial Intelligence in Education, 2014
AutoTutor is a natural language tutoring system that has produced learning gains across multiple domains (e.g., computer literacy, physics, critical thinking). In this paper, we review the development, key research findings, and systems that have evolved from AutoTutor. First, the rationale for developing AutoTutor is outlined and the advantages…
Descriptors: Intelligent Tutoring Systems, Natural Language Processing, Computer Software, Artificial Intelligence
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Graesser, Arthur; McNamara, Danielle – Educational Psychologist, 2010
This article discusses the occurrence and measurement of self-regulated learning (SRL) both in human tutoring and in computer tutors with agents that hold conversations with students in natural language and help them learn at deeper levels. One challenge in building these computer tutors is to accommodate, encourage, and scaffold SRL because these…
Descriptors: Intelligent Tutoring Systems, Metacognition, Tutors, Natural Language Processing
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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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Lynch, Collin F., Ed.; Merceron, Agathe, Ed.; Desmarais, Michel, Ed.; Nkambou, Roger, Ed. – International Educational Data Mining Society, 2019
The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…
Descriptors: Data Collection, Data Analysis, Information Retrieval, Content Analysis
Kommers, Piet, Ed.; Issa, Tomayess, Ed.; Issa, Theodora, Ed.; McKay, Elspeth, Ed.; Isias, Pedro, Ed. – International Association for Development of the Information Society, 2016
These proceedings contain the papers and posters of the International Conferences on Internet Technologies & Society (ITS 2016), Educational Technologies (ICEduTech 2016) and Sustainability, Technology and Education (STE 2016), which have been organised by the International Association for Development of the Information Society and…
Descriptors: Conferences (Gatherings), Foreign Countries, Internet, Educational Technology