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Arroyo, Ivon; Burleson, Winslow; Tai, Minghui; Muldner, Kasia; Woolf, Beverly Park – Journal of Educational Psychology, 2013
We provide evidence of persistent gender effects for students using advanced adaptive technology while learning mathematics. This technology improves each gender's learning and affective predispositions toward mathematics, but specific features in the software help either female or male students. Gender differences were seen in the students' style…
Descriptors: Gender Differences, Educational Technology, Technology Uses in Education, Mathematics Instruction
Chi, Min; VanLehn, Kurt – Educational Technology & Society, 2010
Certain learners are less sensitive to learning environments and can always learn, while others are more sensitive to variations in learning environments and may fail to learn (Cronbach & Snow, 1977). We refer to the former as high learners and the latter as low learners. One important goal of any learning environment is to bring students up…
Descriptors: Intelligent Tutoring Systems, Physics, Probability, Tutoring
Botvinick, Matthew M.; Niv, Yael; Barto, Andrew C. – Cognition, 2009
Research on human and animal behavior has long emphasized its hierarchical structure--the divisibility of ongoing behavior into discrete tasks, which are comprised of subtask sequences, which in turn are built of simple actions. The hierarchical structure of behavior has also been of enduring interest within neuroscience, where it has been widely…
Descriptors: Intelligent Tutoring Systems, Animal Behavior, Reinforcement, Models
Kuhn, Matt; Dempsey, Kathleen – Learning & Leading with Technology, 2011
In 1999, Richard Lee Colvin published an article in "The School Administrator" titled "Math Wars: Tradition vs. Real-World Applications" that described the pendulum swing of mathematics education reform. On one side are those who advocate for computational fluency, with a step-by-step emphasis on numbers and skills and the…
Descriptors: Feedback (Response), Problem Solving, Mathematics Education, Intelligent Tutoring Systems
Cifuentes, Laurent; Mercer, Rene; Alverez, Omar; Bettati, Riccardo – TechTrends: Linking Research and Practice to Improve Learning, 2010
We report on the design, development, implementation, and evaluation of a case-based instructional environment designed for learning network engineering skills for cybersecurity. We describe the societal problem addressed, the theory-based solution, and the preliminary testing and evaluation of that solution. We identify an architecture for…
Descriptors: Case Method (Teaching Technique), Problem Solving, Scaffolding (Teaching Technique), Instructional Design
Barnes, Tiffany; Stamper, John – Educational Technology & Society, 2010
In building intelligent tutoring systems, it is critical to be able to understand and diagnose student responses in interactive problem solving. However, building this understanding into a computer-based intelligent tutor is a time-intensive process usually conducted by subject experts. Much of this time is spent in building production rules that…
Descriptors: Intelligent Tutoring Systems, Logical Thinking, Tutors, Probability
Stamper, John Carroll – ProQuest LLC, 2010
Intelligent Tutoring Systems (ITSs) that adapt to an individual student's needs have shown significant improvement in achievement over non-adaptive instruction (Murray 1999). This improvement occurs due to the individualized instruction and feedback that an ITS provides. In order to achieve the benefits that ITSs provide, we must find a way to…
Descriptors: Intelligent Tutoring Systems, Individualized Instruction, Adjustment (to Environment), Feedback (Response)
Muldner, Kasia; Conati, Cristina – International Journal of Artificial Intelligence in Education, 2010
Although worked-out examples play a key role in cognitive skill acquisition, research demonstrates that students have various levels of meta-cognitive abilities for using examples effectively. The Example Analogy (EA)-Coach is an Intelligent Tutoring System that provides adaptive support to foster meta-cognitive behaviors relevant to a specific…
Descriptors: Intelligent Tutoring Systems, Problem Solving, Cognitive Psychology, Thinking Skills
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
Sampson, Demetrios G., Ed.; Ifenthaler, Dirk, Ed.; Isaías, Pedro, Ed. – International Association for Development of the Information Society, 2021
These proceedings contain the papers of the 18th International Conference on Cognition and Exploratory Learning in the Digital Age (CELDA 2021), held virtually, due to an exceptional situation caused by the COVID-19 pandemic, from October 13-15, 2021, and organized by the International Association for Development of the Information Society…
Descriptors: Computer Simulation, Open Educational Resources, Telecommunications, Handheld Devices
Pinkwart, Niels; Ashley, Kevin; Lynch, Collin; Aleven, Vincent – International Journal of Artificial Intelligence in Education, 2009
Argumentation is a process that occurs often in ill-defined domains and that helps deal with the ill-definedness. Typically a notion of "correctness" for an argument in an ill-defined domain is impossible to define or verify formally because the underlying concepts are open-textured and the quality of the argument may be subject to discussion or…
Descriptors: Persuasive Discourse, Law Students, Intelligent Tutoring Systems, Problem Solving
Durlach, Paula J., Ed; Lesgold, Alan M., Ed. – Cambridge University Press, 2012
This edited volume provides an overview of the latest advancements in adaptive training technology. Intelligent tutoring has been deployed for well-defined and relatively static educational domains such as algebra and geometry. However, this adaptive approach to computer-based training has yet to come into wider usage for domains that are less…
Descriptors: Expertise, Educational Strategies, Semantics, Intelligent Tutoring Systems
Rafferty, Anna N., Ed.; Whitehill, Jacob, Ed.; Romero, Cristobal, Ed.; Cavalli-Sforza, Violetta, Ed. – International Educational Data Mining Society, 2020
The 13th iteration of the International Conference on Educational Data Mining (EDM 2020) was originally arranged to take place in Ifrane, Morocco. Due to the SARS-CoV-2 (coronavirus) epidemic, EDM 2020, as well as most other academic conferences in 2020, had to be changed to a purely online format. To facilitate efficient transmission of…
Descriptors: Educational Improvement, Teaching Methods, Information Retrieval, Data Processing
Kiesmuller, Ulrich – ACM Transactions on Computing Education, 2009
At schools special learning and programming environments are often used in the field of algorithms. Particularly with regard to computer science lessons in secondary education, they are supposed to help novices to learn the basics of programming. In several parts of Germany (e.g., Bavaria) these fundamentals are taught as early as in the seventh…
Descriptors: Foreign Countries, Feedback (Response), Secondary School Students, Research Methodology
D'Mello, Sidney K.; Lehman, Blair; Person, Natalie – International Journal of Artificial Intelligence in Education, 2010
We explored the affective states that students experienced during effortful problem solving activities. We conducted a study where 41 students solved difficult analytical reasoning problems from the Law School Admission Test. Students viewed videos of their faces and screen captures and judged their emotions from a set of 14 states (basic…
Descriptors: Video Technology, Electronic Learning, Handheld Devices, Student Attitudes

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