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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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Huang, Xudong; Craig, Scotty D.; Xie, Jun; Graesser, Arthur C.; Okwumabua, Theresa; Cheney, Kyle R.; Hu, Xiangen – Society for Research on Educational Effectiveness, 2013
The gap among ethnicities and gender in mathematics achievement is a well-known problem. While the gap has been shrinking over the past three decades, it has not completely diminished (Jencks & Phillips, 1998; McGraw, Lubienski, & Strutchens, 2006). The ALEKS, Assessment and LEarning in Knowledge Spaces, tutoring system is one promising…
Descriptors: Gender Differences, Racial Differences, Ethnic Groups, Technology Uses in Education
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What Works Clearinghouse, 2013
The study reviewed in this paper examined the effects of a web-based tutoring program, "Intelligent Tutoring of the Structure Strategy" ("ITSS"), on the reading comprehension of fourth-grade students in language arts classrooms. The analysis included 1,875 to 2,371 fourth-grade students from 100 to 117 classrooms in…
Descriptors: Program Evaluation, Program Effectiveness, Intelligent Tutoring Systems, Web Based Instruction
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Scandura, Joseph M. – Technology, Instruction, Cognition and Learning, 2011
More and more things that humans used to do can be automated on computer. In each case, complex tasks have been automated -- not to the extent that they can be done as well as humans, but better. I will draw and develop parallels to education -- showing how and why advances in the Structural Learning Theory (SLT) and the AuthorIT development and…
Descriptors: Intelligent Tutoring Systems, Automation, Tutors, Learning Theories
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Boyer, Kristy Elizabeth; Phillips, Robert; Ingram, Amy; Ha, Eun Young; Wallis, Michael; Vouk, Mladen; Lester, James – International Journal of Artificial Intelligence in Education, 2011
Identifying effective tutorial dialogue strategies is a key issue for intelligent tutoring systems research. Human-human tutoring offers a valuable model for identifying effective tutorial strategies, but extracting them is a challenge because of the richness of human dialogue. This article addresses that challenge through a machine learning…
Descriptors: Markov Processes, Intelligent Tutoring Systems, Tutoring, Program Effectiveness
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Amaral, Luiz; Meurers, Detmar; Ziai, Ramon – Computer Assisted Language Learning, 2011
Intelligent language tutoring systems (ILTS) typically analyze learner input to diagnose learner language properties and provide individualized feedback. Despite a long history of ILTS research, such systems are virtually absent from real-life foreign language teaching (FLT). Taking a step toward more closely linking ILTS research to real-life…
Descriptors: Feedback (Response), Second Language Learning, Intelligent Tutoring Systems, Information Management
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