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Rau, M. A.; Aleven, V.; Rummel, N.; Pardos, Z. – International Journal of Artificial Intelligence in Education, 2014
Providing learners with multiple representations of learning content has been shown to enhance learning outcomes. When multiple representations are presented across consecutive problems, we have to decide in what sequence to present them. Prior research has demonstrated that interleaving "tasks types" (as opposed to blocking them) can…
Descriptors: Intelligent Tutoring Systems, Visual Aids, Mathematics, Mixed Methods Research
Pareto, Lena – International Journal of Artificial Intelligence in Education, 2014
In this paper we will describe a learning environment designed to foster conceptual understanding and reasoning in mathematics among younger school children. The learning environment consists of 48 2-player game variants based on a graphical model of arithmetic where the mathematical content is intrinsically interwoven with the game idea. The…
Descriptors: Concept Formation, Mathematical Concepts, Mathematics Instruction, Educational Games
Arroyo, Ivon; Woolf, Beverly Park; Burelson, Winslow; Muldner, Kasia; Rai, Dovan; Tai, Minghui – International Journal of Artificial Intelligence in Education, 2014
This article describes research results based on multiple years of experimentation and real-world experience with an adaptive tutoring system named Wayang Outpost. The system represents a novel adaptive learning technology that has shown successful outcomes with thousands of students, and provided teachers with valuable information about…
Descriptors: Intelligent Tutoring Systems, Multimedia Instruction, Mathematics Instruction, Learner Engagement
Heffernan, Neil T.; Heffernan, Cristina Lindquist – International Journal of Artificial Intelligence in Education, 2014
The ASSISTments project is an ecosystem of a few hundred teachers, a platform, and researchers working together. Development professionals help train teachers and get teachers to participate in studies. The platform and these teachers help researchers (sometimes explicitly and sometimes implicitly) simply by using content the teacher selects. The…
Descriptors: Intelligent Tutoring Systems, Educational Research, Formative Evaluation, Artificial Intelligence
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)
Baker, Ryan S. J. D.; Goldstein, Adam B.; Heffernan, Neil T. – International Journal of Artificial Intelligence in Education, 2011
Intelligent tutors have become increasingly accurate at detecting whether a student knows a skill, or knowledge component (KC), at a given time. However, current student models do not tell us exactly at which point a KC is learned. In this paper, we present a machine-learned model that assesses the probability that a student learned a KC at a…
Descriptors: Intelligent Tutoring Systems, Mastery Learning, Probability, Knowledge Level
Rowe, Jonathan P.; Shores, Lucy R.; Mott, Bradford W.; Lester, James C. – International Journal of Artificial Intelligence in Education, 2011
A key promise of narrative-centered learning environments is the ability to make learning engaging. However, there is concern that learning and engagement may be at odds in these game-based learning environments. This view suggests that, on the one hand, students interacting with a game-based learning environment may be engaged but unlikely to…
Descriptors: Problem Solving, Educational Technology, Virtual Classrooms, Educational Environment

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