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50 Years of ERIC
50 Years of ERIC
The Education Resources Information Center (ERIC) is celebrating its 50th Birthday! First opened on May 15th, 1964 ERIC continues the long tradition of ongoing innovation and enhancement.

Learn more about the history of ERIC here. PDF icon

Showing all 13 results
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Lenat, Douglas B.; Durlach, Paula J. – International Journal of Artificial Intelligence in Education, 2014
We often understand something only after we've had to teach or explain it to someone else. Learning-by-teaching (LBT) systems exploit this phenomenon by playing the role of "tutee." BELLA, our sixth-grade mathematics LBT systems, departs from other LTB systems in several ways: (1) It was built not from scratch but by very slightly…
Descriptors: Artificial Intelligence, Knowledge Level, Mathematics Instruction, Teaching Methods
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Khachatryan, George A.; Romashov, Andrey V.; Khachatryan, Alexander R.; Gaudino, Steven J.; Khachatryan, Julia M.; Guarian, Konstantin R.; Yufa, Nataliya V. – International Journal of Artificial Intelligence in Education, 2014
Effective mathematics teachers have a large body of professional knowledge, which is largely undocumented and shared by teachers working in a given country's education system. The volume and cultural nature of this knowledge make it particularly challenging to share curricula and instructional methods between countries. Thus, approaches based…
Descriptors: Intelligent Tutoring Systems, Mathematics Instruction, Teaching Methods, Technology Transfer
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Nye, Benjamin D.; Graesser, Arthur C.; Hu, Xiangen – 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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Käser, Tanja; Busetto, Alberto Giovanni; Solenthaler, Barbara; Baschera, Gian-Marco; Kohn, Juliane; Kucian, Karin; von Aster, Michael; Gross, Markus – International Journal of Artificial Intelligence in Education, 2013
This study introduces a student model and control algorithm, optimizing mathematics learning in children. The adaptive system is integrated into a computer-based training system for enhancing numerical cognition aimed at children with developmental dyscalculia or difficulties in learning mathematics. The student model consists of a dynamic…
Descriptors: Mathematics Instruction, Children, Computer Assisted Instruction, Educational Technology
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Li, Nan; Cohen, William W.; Koedinger, Kenneth R. – International Journal of Artificial Intelligence in Education, 2013
The order of problems presented to students is an important variable that affects learning effectiveness. Previous studies have shown that solving problems in a blocked order, in which all problems of one type are completed before the student is switched to the next problem type, results in less effective performance than does solving the problems…
Descriptors: Teaching Methods, Teacher Effectiveness, Problem Solving, Problem Based Learning
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Matsuda, Noboru; Yarzebinski, Evelyn; Keiser, Victoria; Raizada, Rohan; Stylianides, Gabriel J.; Koedinger, Kenneth R. – International Journal of Artificial Intelligence in Education, 2013
In this paper we investigate how competition among tutees in the context of learning by teaching affects tutors' engagement as well as tutor learning. We conducted this investigation by incorporating a competitive Game Show feature into an online learning environment where students learn to solve algebraic equations by teaching a synthetic…
Descriptors: Teaching Methods, Competition, Educational Games, Equations (Mathematics)
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Chi, Min; VanLehn, Kurt; Litman, Diane; Jordan, Pamela – International Journal of Artificial Intelligence in Education, 2011
Pedagogical strategies are policies for a tutor to decide the next action when there are multiple actions available. When the content is controlled to be the same across experimental conditions, there has been little evidence that tutorial decisions have an impact on students' learning. In this paper, we applied Reinforcement Learning (RL) to…
Descriptors: Classroom Communication, Interaction, Reinforcement, Natural Language Processing
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Stamper, John; Barnes, Tiffany; Croy, Marvin – International Journal of Artificial Intelligence in Education, 2011
The Hint Factory is an implementation of our novel method to automatically generate hints using past student data for a logic tutor. One disadvantage of the Hint Factory is the time needed to gather enough data on new problems in order to provide hints. In this paper we describe the use of expert sample solutions to "seed" the hint generation…
Descriptors: Cues, Prompting, Learning Strategies, Teaching Methods
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Arroyo, Ivon; Royer, James M.; Woolf, Beverly P. – International Journal of Artificial Intelligence in Education, 2011
This article integrates research in intelligent tutors with psychology studies of memory and math fluency (the speed to retrieve or calculate answers to basic math operations). It describes the impact of computer software designed to improve either strategic behavior or math fluency. Both competencies are key to improved performance and both…
Descriptors: Computer Software, Short Term Memory, Tutors, Mathematics Instruction
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McLaren, Bruce M.; Scheuer, Oliver; Miksatko, Jan – International Journal of Artificial Intelligence in Education, 2010
An emerging trend in classrooms is the use of networked visual argumentation tools that allow students to discuss, debate, and argue with one another in a synchronous fashion about topics presented by a teacher. These tools are aimed at teaching students how to discuss and argue, important skills not often taught in traditional classrooms. But how…
Descriptors: Artificial Intelligence, Cooperative Learning, Computer Mediated Communication, Discussion (Teaching Technique)
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Heilman, Michael; Collins-Thompson, Kevyn; Callan, Jamie; Eskenazi, Maxine; Juffs, Alan; Wilson, Lois – International Journal of Artificial Intelligence in Education, 2010
The REAP tutoring system provides individualized and adaptive English as a Second Language vocabulary practice. REAP can automatically personalize instruction by providing practice readings about topics that match interests as well as domain-based, cognitive objectives. While most previous research on motivation in intelligent tutoring…
Descriptors: Incentives, Cognitive Objectives, Intelligent Tutoring Systems, Motivation
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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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Hayashi, Yusuke; Bourdeau, Jacqueline; Mizoguchi, Riichiro – International Journal of Artificial Intelligence in Education, 2009
This paper describes the achievements of an innovative eight-year research program first introduced in Mizoguchi and Bourdeau (2000), which was aimed at building a theory-aware authoring system by using ontological engineering. To date, we have proposed OMNIBUS, an ontology that comprehensively covers different learning/instructional theories and…
Descriptors: Foreign Countries, Theory Practice Relationship, Engineering, Teaching Methods