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Showing all 15 results Save | Export
Ying Fang; Tong Li; Linh Huynh; Katerina Christhilf; Rod D. Roscoe; Danielle S. McNamara – Grantee Submission, 2023
Literacy assessment is essential for effective literacy instruction and training. However, traditional paper-based literacy assessments are typically decontextualized and may cause stress and anxiety for test takers. In contrast, serious games and game environments allow for the assessment of literacy in more authentic and engaging ways, which has…
Descriptors: Literacy, Student Evaluation, Educational Games, Literacy Education
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Westera, Wim; Prada, Rui; Mascarenhas, Samuel; Santos, Pedro A.; Dias, João; Guimarães, Manuel; Georgiadis, Konstantinos; Nyamsuren, Enkhbold; Bahreini, Kiavash; Yumak, Zerrin; Christyowidiasmoro, Chris; Dascalu, Mihai; Gutu-Robu, Gabriel; Ruseti, Stefan – Education and Information Technologies, 2020
This article provides a comprehensive overview of artificial intelligence (AI) for serious games. Reporting about the work of a European flagship project on serious game technologies, it presents a set of advanced game AI components that enable pedagogical affordances and that can be easily reused across a wide diversity of game engines and game…
Descriptors: Artificial Intelligence, Educational Games, Educational Technology, Computer Software
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Jackson, Tanner; Boonthum-Denecke, Chutima; McNamara, Danielle – Journal of Interactive Learning Research, 2015
Intelligent Tutoring Systems (ITSs) are situated in a potential struggle between effective pedagogy and system enjoyment and engagement. iSTART (Interactive Strategy Training for Active Reading and Thinking), a reading strategy tutoring system in which students practice generating self-explanations and using reading strategies, employs two devices…
Descriptors: Intelligent Tutoring Systems, Educational Technology, Reading Strategies, Tutoring
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Jackson, G. Tanner; Boonthum-Denecke, Chutima; McNamara, Danielle S. – Grantee Submission, 2015
Intelligent Tutoring Systems (ITSs) are situated in a potential struggle between effective pedagogy and system enjoyment and engagement. iSTART, a reading strategy tutoring system in which students practice generating self-explanations and using reading strategies, employs two devices to engage the user. The first is natural language processing…
Descriptors: Natural Language Processing, Feedback (Response), Intelligent Tutoring Systems, Reading Strategies
Graesser, Arthur; Li, Haiying; Forsyth, Carol – Grantee Submission, 2014
Learning is facilitated by conversational interactions both with human tutors and with computer agents that simulate human tutoring and ideal pedagogical strategies. In this article, we describe some intelligent tutoring systems (e.g., AutoTutor) in which agents interact with students in natural language while being sensitive to their cognitive…
Descriptors: Intelligent Tutoring Systems, Teaching Methods, Computer Simulation, Dialogs (Language)
Rus, Vasile; Moldovan, Cristian; Niraula, Nobal; Graesser, Arthur C. – International Educational Data Mining Society, 2012
In this paper we address the important task of automated discovery of speech act categories in dialogue-based, multi-party educational games. Speech acts are important in dialogue-based educational systems because they help infer the student speaker's intentions (the task of speech act classification) which in turn is crucial to providing adequate…
Descriptors: Educational Games, Feedback (Response), Classification, Expertise
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Cope, Bill; Kalantzis, Mary – Open Review of Educational Research, 2015
This article sets out to explore a shift in the sources of evidence-of-learning in the era of networked computing. One of the key features of recent developments has been popularly characterized as "big data". We begin by examining, in general terms, the frame of reference of contemporary debates on machine intelligence and the role of…
Descriptors: Data Analysis, Evidence, Computer Uses in Education, Artificial Intelligence
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Crossley, Scott A.; Varner, Laura K.; Roscoe, Rod D.; McNamara, Danielle S. – Grantee Submission, 2013
We present an evaluation of the Writing Pal (W-Pal) intelligent tutoring system (ITS) and the W-Pal automated writing evaluation (AWE) system through the use of computational indices related to text cohesion. Sixty-four students participated in this study. Each student was assigned to either the W-Pal ITS condition or the W-Pal AWE condition. The…
Descriptors: Intelligent Tutoring Systems, Automation, Writing Evaluation, Writing Assignments
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Kumar, R.; Rose, C. P. – IEEE Transactions on Learning Technologies, 2011
Tutorial Dialog Systems that employ Conversational Agents (CAs) to deliver instructional content to learners in one-on-one tutoring settings have been shown to be effective in multiple learning domains by multiple research groups. Our work focuses on extending this successful learning technology to collaborative learning settings involving two or…
Descriptors: Educational Technology, Computer Software, Computer Software Evaluation, Programming
Durlach, Paula J., Ed; Lesgold, Alan M., Ed. – Cambridge University Press, 2012
This edited volume provides an overview of the latest advancements in adaptive training technology. Intelligent tutoring has been deployed for well-defined and relatively static educational domains such as algebra and geometry. However, this adaptive approach to computer-based training has yet to come into wider usage for domains that are less…
Descriptors: Expertise, Educational Strategies, Semantics, Intelligent Tutoring Systems
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Boyer, Kristy Elizabeth, Ed.; Yudelson, Michael, Ed. – International Educational Data Mining Society, 2018
The 11th International Conference on Educational Data Mining (EDM 2018) is held under the auspices of the International Educational Data Mining Society at the Templeton Landing in Buffalo, New York. This year's EDM conference was highly competitive, with 145 long and short paper submissions. Of these, 23 were accepted as full papers and 37…
Descriptors: Data Collection, Data Analysis, Computer Science Education, Program Proposals
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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
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection