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Hagge, Mathew; Amin-Naseri, Mostafa; Jackman, John; Guo, Enruo; Gilbert, Stephen B.; Starns, Gloria; Faidley, Leann – Advances in Engineering Education, 2017
Students learn when they connect new information to existing understanding or when they modify existing understanding to accept new information. Most current teaching methods focus on trying to get students to solve problems in a manner identical to that of an expert. This study investigates the effectiveness of assessing student understanding…
Descriptors: Intelligent Tutoring Systems, Thermodynamics, Problem Solving, Decision Making
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Hooshyar, Danial; Binti Ahmad, Rodina; Wang, Minhong; Yousefi, Moslem; Fathi, Moein; Lim, Heuiseok – Journal of Educational Computing Research, 2018
Games with educational purposes usually follow a computer-assisted instruction concept that is predefined and rigid, offering no adaptability to each student. To overcome such problem, some ideas from Intelligent Tutoring Systems have been used in educational games such as teaching introductory programming. The objective of this study was to…
Descriptors: Intelligent Tutoring Systems, Teaching Methods, Introductory Courses, Programming
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de Oliveira Costa Machado, Marcelo; Barrére, Eduardo; Souza, Jairo – International Journal of Distance Education Technologies, 2019
Adaptive curriculum sequencing (ACS) is still a challenge in the adaptive learning field. ACS is a NP-hard problem especially considering the several constraints of the student and the learning material when selecting a sequence from repositories where several sequences could be chosen. Therefore, this has stimulated several researchers to use…
Descriptors: Sequential Approach, Intelligent Tutoring Systems, Mathematics, Problem Solving
Ford, Christopher Jay – ProQuest LLC, 2018
Personalized learning for students has been an emerging trend which seeks to support teaching and learning in the 21st century (Netoch, 2017). This study identified beliefs of secondary educators on the different aspects of personalized learning for students. Areas covered in this study included teacher professional development on the personalized…
Descriptors: Secondary School Teachers, Teacher Attitudes, Beliefs, Individualized Instruction
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Aravind, Vasudeva Rao; McConnell, Marcella Kay – World Journal on Educational Technology: Current Issues, 2018
Educating our future citizens in science and engineering is vitally important to ensure future advancement. Presently, in the light of environmental sustainability, it is critical that students learn concepts relating to energy, its consumption and future demands. In this article, we harness the state of the educational technology, namely…
Descriptors: Intelligent Tutoring Systems, Science Instruction, Energy, Instructional Design
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Mostafavi, Behrooz; Barnes, Tiffany – International Journal of Artificial Intelligence in Education, 2017
Deductive logic is essential to a complete understanding of computer science concepts, and is thus fundamental to computer science education. Intelligent tutoring systems with individualized instruction have been shown to increase learning gains. We seek to improve the way deductive logic is taught in computer science by developing an intelligent,…
Descriptors: Artificial Intelligence, Problem Solving, Educational Technology, Technology Uses in Education
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Shen, Shitian; Chi, Min – International Educational Data Mining Society, 2017
One of the most challenging tasks in the field of Educational Data Mining (EDM) is to cluster students directly based on system-student sequential moment-to-moment interactive trajectories. The objective of this study is to build a general temporal clustering framework that captures the distinct characteristics of students' sequential behaviors…
Descriptors: Sequential Approach, Cluster Grouping, Interaction, Student Behavior
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Aguerrebere, Cecilia; Cobo, Cristóbal; Whitehill, Jacob – International Educational Data Mining Society, 2018
When implementing large-scale educational computing initiatives (e.g., One Laptop Per Child) it is vital to allocate resources for training, support, and device deployment judiciously. One question that arises is how learners' engagement with online educational resources is affected by receiving a new computer; do the benefits justify the costs?…
Descriptors: Management Systems, Foreign Countries, Resource Allocation, Learner Engagement
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McGuire, Patrick; Tu, Shihfen; Logue, Mary Ellin; Mason, Craig A.; Ostrow, Korinn – Educational Media International, 2017
This study compared the effects of three different feedback formats provided to sixth grade mathematics students within a web-based online learning platform, ASSISTments. A sample of 196 students were randomly assigned to one of three conditions: (1) text-based feedback; (2) image-based feedback; and (3) correctness only feedback. Regardless of…
Descriptors: Feedback (Response), Middle Schools, Randomized Controlled Trials, Mathematics Instruction
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Aleven, Vincent; McLaren, Bruce M.; Sewall, Jonathan; van Velsen, Martin; Popescu, Octav; Demi, Sandra; Ringenberg, Michael; Koedinger, Kenneth R. – International Journal of Artificial Intelligence in Education, 2016
In 2009, we reported on a new Intelligent Tutoring Systems (ITS) technology, example-tracing tutors, that can be built without programming using the Cognitive Tutor Authoring Tools (CTAT). Creating example-tracing tutors was shown to be 4-8 times as cost-effective as estimates for ITS development from the literature. Since 2009, CTAT and its…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Programming, Educational Technology
Aleven, Vincent; McLaren, Bruce M.; Sewall, Jonathan; van Velsen, Martin; Popescu, Octav; Demi, Sandra; Ringenberg, Michael; Koedinger, Kenneth R. – Grantee Submission, 2016
In 2009, we reported on a new Intelligent Tutoring Systems (ITS) technology, example-tracing tutors, that can be built without programming using the Cognitive Tutor Authoring Tools (CTAT). Creating example-tracing tutors was shown to be 4-8 times as cost-effective as estimates for ITS development from the literature. Since 2009, CTAT and its…
Descriptors: Intelligent Tutoring Systems, Programming, Artificial Intelligence, Visual Aids
Christopher Thomas Alvin – ProQuest LLC, 2015
Many problems related to synthesis with intelligent tutoring may be phrased as program synthesis problems using AI-style search and formal reasoning techniques. The _x000C_first two results in this dissertation focus on problem synthesis as an aspect of intelligent tutoring systems applied to STEM-based education frameworks, specifically high…
Descriptors: Synthesis, Intelligent Tutoring Systems, Artificial Intelligence, Problem Solving
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Easterday, Matthew W.; Rees Lewis, Daniel; Gerber, Elizabeth M. – International Journal of Artificial Intelligence in Education, 2017
Intelligent tutors based on expert systems often struggle to provide formative feedback on complex, ill-defined problems where answers are unknown. Hybrid crowdsourcing systems that combine the intelligence of multiple novices in face-to-face settings might provide an alternate approach for providing intelligent formative feedback. The purpose of…
Descriptors: Intelligent Tutoring Systems, Formative Evaluation, Feedback (Response), Novices
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Paneque, Juan J.; Cobo, Pedro; Fortuny, Josep M. – Technology, Knowledge and Learning, 2017
This ethnographical study aims to interpret how an intelligent tutorial system, geogebraTUTOR, mediates to the student's argumentative processes. Data consisted of four geometrical problems proposed to a group of four students aged 16-17. Qualitative analysis of two selected cases led to the identification of the development of argumentative…
Descriptors: Ethnography, Intelligent Tutoring Systems, Geometry, Mathematics Instruction
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Poitras, Eric G.; Lajoie, Susanne P.; Doleck, Tenzin; Jarrell, Amanda – Educational Technology & Society, 2016
Learner modeling, a challenging and complex endeavor, is an important and oft-studied research theme in computer-supported education. From this perspective, Educational Data Mining (EDM) research has focused on modeling and comprehending various dimensions of learning in computer-based learning environments (CBLE). Researchers and designers are…
Descriptors: Intelligent Tutoring Systems, Data, Data Analysis, Medical Evaluation
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