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Sabourin, Jennifer L.; Rowe, Jonathan P.; Mott, Bradford W.; Lester, James C. – Journal of Educational Data Mining, 2013
Over the past decade, there has been growing interest in real-time assessment of student engagement and motivation during interactions with educational software. Detecting symptoms of disengagement, such as off-task behavior, has shown considerable promise for understanding students' motivational characteristics during learning. In this paper, we…
Descriptors: Student Behavior, Classification, Learner Engagement, Data Analysis
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Ward, Wayne; Cole, Ron; Bolaños, Daniel; Buchenroth-Martin, Cindy; Svirsky, Edward; Weston, Tim – Journal of Educational Psychology, 2013
My Science Tutor (MyST) is an intelligent tutoring system designed to improve science learning by elementary school students through conversational dialogs with a virtual science tutor in an interactive multimedia environment. Marni, a lifelike 3-D character, engages individual students in spoken dialogs following classroom investigations using…
Descriptors: Intelligent Tutoring Systems, Elementary School Science, Multimedia Instruction, Interaction
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Baker, Ryan S. J. d.; Corbett, Albert T.; Gowda, Sujith M. – Journal of Educational Psychology, 2013
Recently, there has been growing emphasis on supporting robust learning within intelligent tutoring systems, assessed by measures such as transfer to related skills, preparation for future learning, and longer term retention. It has been shown that different pedagogical strategies promote robust learning to different degrees. However, the student…
Descriptors: Intelligent Tutoring Systems, Educational Technology, Genetics, Science Instruction
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Segedy, James R.; Kinnebrew, John S.; Biswas, Gautam – Educational Technology Research and Development, 2013
Betty's Brain is an open-ended learning environment in which students learn about science topics by teaching a virtual agent named Betty through the construction of a visual causal map that represents the relevant science phenomena. The task is complex, and success requires the use of metacognitive strategies that support knowledge acquisition,…
Descriptors: Artificial Intelligence, Computer Simulation, Computer Mediated Communication, Intelligent Tutoring Systems
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Strayer, Jeremy F. – Learning Environments Research, 2012
Recent technological developments have given rise to blended learning classrooms. An inverted (or flipped) classroom is a specific type of blended learning design that uses technology to move lectures outside the classroom and uses learning activities to move practice with concepts inside the classroom. This article compares the learning…
Descriptors: Blended Learning, Cooperative Learning, Statistics, Classroom Environment
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Demski, Jennifer – T.H.E. Journal, 2012
During what might have in the distant past been called "quiet time" in Arlene Anderson's fourth-grade classroom, many of her students are glued to their netbooks. The intense, enthusiastic focus and the hushed chatter amongst the students are all about high scores and strategy. Students are revising and editing their writing assignments within a…
Descriptors: Writing Achievement, Educational Technology, Writing Skills, Writing Processes
Abbas, Safia; Sawamura, Hajime – International Working Group on Educational Data Mining, 2009
This paper presents an agent-based educational environment to teach argument analysis (ALES). The idea is based on the Argumentation Interchange Format Ontology (AIF)using "Walton Theory". ALES uses different mining techniques to manage a highly structured arguments repertoire. This repertoire was designed, developed and implemented by us. Our aim…
Descriptors: Data Analysis, Persuasive Discourse, Intelligent Tutoring Systems, Models
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Lajoie, Susanne P. – Technology, Instruction, Cognition and Learning, 2010
A primary driver for pursuing the development of technology based adaptive tutoring is an attempt to replicate the effects of one-to-one tutoring with human tutors (Bloom, 1984). This paper situates the discussion of adaptive tutoring in the context of a theory-driven approach to the design of specific cognitive tools. Different methods exist to…
Descriptors: Intelligent Tutoring Systems, Medical Education, Problem Solving, Medical Students
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Hollister, James; Richie, Sam; Weeks, Arthur – Contemporary Issues in Education Research, 2010
This study investigated the various methods involved in creating an intelligent tutor for the University of Central Florida Web Applets (UCF Web Applets), an online environment where student can perform and/or practice experiments. After conducting research into various methods, two major models emerged. These models include: 1) solving the…
Descriptors: Intelligent Tutoring Systems, Computer Simulation, Simulated Environment, Experiments
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Seal, Kala Chand; Przasnyski, Zbigniew H.; Leon, Linda A. – Decision Sciences Journal of Innovative Education, 2010
Do students learn to model OR/MS problems better by using computer-based interactive tutorials and, if so, does increased interactivity in the tutorials lead to better learning? In order to determine the effect of different levels of interactivity on student learning, we used screen capture technology to design interactive support materials for…
Descriptors: Spreadsheets, Intelligent Tutoring Systems, Learning Processes, Interaction
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Suraweera, Pramuditha; Mitrovic, Antonija; Martin, Brent – International Journal of Artificial Intelligence in Education, 2010
Intelligent Tutoring Systems (ITS) are effective tools for education. However, developing them is a labour-intensive and time-consuming process. A major share of the effort is devoted to acquiring the domain knowledge that underlies the system's intelligence. The goal of this research is to reduce this knowledge acquisition bottleneck and better…
Descriptors: Intelligent Tutoring Systems, Programming, Engineering, Tutoring
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van Seters, J. R.; Ossevoort, M. A.; Tramper, J.; Goedhart, M. J. – Computers & Education, 2012
Adaptive e-learning materials can help teachers to educate heterogeneous student groups. This study provides empirical data about the way academic students differ in their learning when using adaptive e-learning materials. Ninety-four students participated in the study. We determined characteristics in a heterogeneous student group by collecting…
Descriptors: Foreign Countries, Electronic Learning, Learning Strategies, Computer Assisted Instruction
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Pavlik, Philip I., Jr. – Journal of Educational Data Mining, 2013
This paper describes the development of a dynamical systems model of motivation and metacognition during learning, which explains some of the practically and theoretically important relationships among three student engagement constructs and performance metrics during learning. In order to better calibrate and understand the model, the model was…
Descriptors: Vocabulary Development, Learning Strategies, Predictor Variables, Scores
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Gobert, Janice D.; Sao Pedro, Michael; Raziuddin, Juelaila; Baker, Ryan S. – Journal of the Learning Sciences, 2013
We present a method for assessing science inquiry performance, specifically for the inquiry skill of designing and conducting experiments, using educational data mining on students' log data from online microworlds in the Inq-ITS system (Inquiry Intelligent Tutoring System; www.inq-its.org). In our approach, we use a 2-step process: First we use…
Descriptors: Intelligent Tutoring Systems, Science Education, Inquiry, Science Process Skills
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Khawaja, M. Asif; Prusty, Gangadhara B.; Ford, Robin A. J.; Marcus, Nadine; Russell, Carol – European Journal of Engineering Education, 2013
Online interactive systems offer the beguiling prospect of an improved environment for learning at minimum extra cost. We have developed online interactive tutorials that adapt the learning environment to the current learning status of each individual student. These Adaptive Tutorials (ATs) modify the tasks given to each student according to their…
Descriptors: Foreign Countries, Engineering, Engineering Education, Feedback (Response)
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