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Chen, Xieling; Zou, Di; Xie, Haoran; Cheng, Gary; Liu, Caixia – Educational Technology & Society, 2022
With the increasing use of Artificial Intelligence (AI) technologies in education, the number of published studies in the field has increased. However, no large-scale reviews have been conducted to comprehensively investigate the various aspects of this field. Based on 4,519 publications from 2000 to 2019, we attempt to fill this gap and identify…
Descriptors: Artificial Intelligence, Educational Trends, Educational Technology, Bibliometrics
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Ramanarayanan, Vikram; Lange, Patrick; Evanini, Keelan; Molloy, Hillary; Tsuprun, Eugene; Qian, Yao; Suendermann-Oeft, David – ETS Research Report Series, 2017
Predicting and analyzing multimodal dialog user experience (UX) metrics, such as overall call experience, caller engagement, and latency, among other metrics, in an ongoing manner is important for evaluating such systems. We investigate automated prediction of multiple such metrics collected from crowdsourced interactions with an open-source,…
Descriptors: Automation, Prediction, Man Machine Systems, Open Source Technology
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Mu, Tong; Jetten, Andrea; Brunskill, Emma – International Educational Data Mining Society, 2020
In some computerized educational systems, there is evidence of students "wheel-spinning," where a student tries and repeatedly fails at an educational task for learning a skill. This may be particularly concerning in low resource settings. Prior research has focused on predicting and modeling wheel-spinning, but there has been little…
Descriptors: Computer Uses in Education, Artificial Intelligence, Academic Failure, Automation
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Valdés Aguirre, Benjamín; Ramírez Uresti, Jorge A.; du Boulay, Benedict – International Journal of Artificial Intelligence in Education, 2016
Sharing user information between systems is an area of interest for every field involving personalization. Recommender Systems are more advanced in this aspect than Intelligent Tutoring Systems (ITSs) and Intelligent Learning Environments (ILEs). A reason for this is that the user models of Intelligent Tutoring Systems and Intelligent Learning…
Descriptors: Intelligent Tutoring Systems, Models, Open Source Technology, Computers
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Wu, Pai-Hsing; Wu, Hsin-Kai; Kuo, Che-Yu; Hsu, Ying-Shao – Interactive Learning Environments, 2015
Computer-based learning tools include design features to enhance learning but learners may not always perceive the existence of these features and use them in desirable ways. There might be a gap between what the tool features are designed to offer (intended affordance) and what they are actually used (actual affordance). This study thus aims at…
Descriptors: Science Instruction, Computer Uses in Education, Educational Technology, High School Students
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Casselman, Brock L.; Atwood, Charles H. – Journal of Chemical Education, 2017
In a first-semester general chemistry course, metacognitive training was implemented as part of an online homework system. Students completed weekly quizzes and multiple practice tests to regularly assess their abilities on the chemistry principles. Before taking these assessments, students predicted their score, receiving feedback after…
Descriptors: Chemistry, Science Instruction, College Science, Undergraduate Study
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Sadaf, Ayesha; Newby, Timothy J.; Ertmer, Peggy A. – Journal of Research on Technology in Education, 2013
This study investigated factors that predict preservice teachers' intentions to use Web 2.0 technologies in their future classrooms. The researchers used a mixed-methods research design and collected qualitative interview data (n = 7) to triangulate quantitative survey data (n = 286). Results indicate that positive attitudes and perceptions of…
Descriptors: Interviews, Qualitative Research, Web Sites, Electronic Publishing
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Kreijns, Karel; Vermeulen, Marjan; Kirschner, Paul A.; van Buuren, Hans; Van Acker, Frederik – Technology, Pedagogy and Education, 2013
Information and communication technology (ICT) can enable, support, and reinforce the introduction of new pedagogical practices that comply with the educational demands of the twenty-first-century knowledge society. However, despite this potential and despite the delivering of skills-based professional development and the increase in the level of…
Descriptors: Educational Technology, Self Efficacy, Prediction, Teaching Methods
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Aypay, Ayse; Celik, Halil Coskun; Aypay, Ahmet; Sever, Mustafa – Turkish Online Journal of Educational Technology - TOJET, 2012
The purpose of this study is to test a model that predicts the level of technology acceptance across pre-service teachers at the faculties of education in Turkey. The relationship among the factors that have influence on technology acceptance was investigated. Adopting a questionnaire developed by Timothy (2009) data was collected from 754…
Descriptors: Factor Analysis, Self Efficacy, Preservice Teacher Education, Foreign Countries
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Mezei, Peter J.; Heller, Kathryn Wolff – Physical Disabilities: Education and Related Services, 2012
Many students with physical disabilities have difficulty with writing fluency due to motor limitations. One type of assistive technology that has been developed to improve writing speed and accuracy is word prediction software, although there is a paucity of research supporting its use for individuals with physical disabilities. This study used an…
Descriptors: Educational Technology, Assistive Technology, Prediction, Physical Disabilities
D'Mello, S. K., Ed.; Calvo, R. A., Ed.; Olney, A., Ed. – International Educational Data Mining Society, 2013
Since its inception in 2008, the Educational Data Mining (EDM) conference series has featured some of the most innovative and fascinating basic and applied research centered on data mining, education, and learning technologies. This tradition of exemplary interdisciplinary research has been kept alive in 2013 as evident through an imaginative,…
Descriptors: Data Analysis, Educational Research, Educational Technology, Interdisciplinary Approach
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Sang, Guoyuan; Valcke, Martin; van Braak, Johan; Tondeur, Jo – Computers & Education, 2010
Student teachers should be prepared to integrate information and communication technology (ICT) into their future teaching and learning practices. Despite the increased availability and support for ICT integration, relatively few teachers intend to integrate ICT into their teaching activities (e.g., Ertmer, 2005). The available research has thus…
Descriptors: Constructivism (Learning), Preservice Teachers, Self Efficacy, Path Analysis
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Ward, Lorrae; Parr, Judy M. – Computers & Education, 2010
This paper investigates the use of ICT by teachers in selected secondary schools. It considers both the extent and type of use and the factors that may influence such use through the statistical analysis of data from a 30-section survey containing 185 items. First, exploratory maximum-likelihood factor analysis was used to identify five distinct…
Descriptors: Factor Analysis, Statistical Analysis, Teacher Attitudes, Professional Development
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Buckley, Patrick; Garvey, John; McGrath, Fergal – Computers & Education, 2011
In this paper, prediction markets are presented as an innovative pedagogical tool which can be used to create a Rich Environment for Active Learning (REAL). Prediction markets are designed to make forecasts about specific future events by using a market mechanism to aggregate the information held by a large group of traders about that event into a…
Descriptors: Prediction, Active Learning, Educational Technology, Teaching Methods
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Pattanasri, N.; Mukunoki, M.; Minoh, M. – IEEE Transactions on Learning Technologies, 2012
Comprehension assessment is an essential tool in classroom learning. However, the judgment often relies on experience of an instructor who makes observation of students' behavior during the lessons. We argue that students should report their own comprehension explicitly in a classroom. With students' comprehension made available at the slide…
Descriptors: Foreign Countries, Comprehension, Visual Aids, Prediction
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