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Showing 1 to 15 of 26 results Save | Export
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Kole Norberg; Husni Almoubayyed; Stephen E. Fancsali; Logan De Ley; Kyle Weldon; April Murphy; Steve Ritter – Grantee Submission, 2023
Large Language Models have recently achieved high performance on many writing tasks. In a recent study, math word problems in Carnegie Learning's MATHia adaptive learning software were rewritten by human authors to improve their clarity and specificity. The randomized experiment found that emerging readers who received the rewritten word problems…
Descriptors: Word Problems (Mathematics), Mathematics Instruction, Artificial Intelligence, Intelligent Tutoring Systems
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Lechuga, Christopher G.; Doroudi, Shayan – International Journal of Artificial Intelligence in Education, 2023
Computer-assisted instructional programs such as intelligent tutoring systems are often used to support blended learning practices in K-12 education, as they aim to meet individual student needs with personalized instruction. While these systems have been shown to be effective under certain conditions, they can be difficult to integrate into…
Descriptors: Algorithms, Intelligent Tutoring Systems, Grouping (Instructional Purposes), Ability Grouping
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Huaiya Liu; Yuyue Zhang; Jiyou Jia – IEEE Transactions on Learning Technologies, 2024
Intelligent tutoring systems (ITSs) aim to deliver personalized learning support to each learner, aligning with the educational aspiration of many countries, including China. ITSs' personalized support is mainly achieved by providing individual prompts to learners when they encounter difficulties in problem-solving. The guiding principles and…
Descriptors: Intelligent Tutoring Systems, Mathematics Achievement, Individualized Instruction, Foreign Countries
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Cindy Peng; Conrad Borchers; Vincent Aleven – Grantee Submission, 2024
Prior studies identified effective, but mainly non-digital, homework aids. This research involved 18 middle school students in a lo-fi prototyping study to integrate traditional homework support tools with intelligent tutoring systems (ITS), leveraging rich log data for personalized learning. Feature investigations in standardized diaries, goal…
Descriptors: Middle School Students, Intelligent Tutoring Systems, Homework, Design
Yasemin Copur-Gencturk; Jingxian Li; Sebnem Atabas – American Educational Research Journal, 2024
Scalable and accessible professional development programs have the potential to address the opportunity gap many teachers experience. Yet many asynchronous online programs lack interaction with and timely feedback to teachers. We addressed this problem by developing a virtual, interactive program that uses intelligent tutoring systems to provide…
Descriptors: Artificial Intelligence, Faculty Development, Individualized Instruction, Interaction
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de Chiusole, Debora; Stefanutti, Luca; Anselmi, Pasquale; Robusto, Egidio – International Journal of Artificial Intelligence in Education, 2020
An intelligent tutoring system for learning basic statistics, called Stat-Knowlab, is presented and analyzed. The algorithms implemented in the system are based on the competence-based knowledge space theory, a mathematical theory developed for the formative assessment of knowledge and learning. The system's architecture consists of the two…
Descriptors: Statistics, Intelligent Tutoring Systems, Mathematics Instruction, Formative Evaluation
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Wang, Shuai; Christensen, Claire; Cui, Wei; Tong, Richard; Yarnall, Louise; Shear, Linda; Feng, Mingyu – Interactive Learning Environments, 2023
Adaptive learning systems personalize instruction to students' individual learning needs and abilities. Such systems have shown positive impacts on learning. Many schools in the United States have adopted adaptive learning systems, and the rate of adoption in China is accelerating, reaching almost 2 million unique users for one product alone in…
Descriptors: Comparative Analysis, Teaching Methods, Intelligent Tutoring Systems, Foreign Countries
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Glaze, Andrew; Moyer-Packenham, Patricia; Longhurst, Max – Journal of Computers in Mathematics and Science Teaching, 2021
The purpose of this mixed-methods study was to investigate the relationship between teachers' conceptions of mathematics and their use of intelligent tutoring systems for mathematics instruction. Intelligent tutoring systems are adaptive computer programs which administer mathematics instruction to students based on their cognitive state. A…
Descriptors: Junior High School Teachers, Mathematics Teachers, Teacher Attitudes, Technology Uses in Education
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Mao, Ye; Marwan, Samiha; Price, Thomas W.; Barnes, Tiffany; Chi, Min – International Educational Data Mining Society, 2020
Modeling student learning processes is highly complex since it is influenced by many factors such as motivation and learning habits. The high volume of features and tools provided by computer-based learning environments confounds the task of tracking student knowledge even further. Deep Learning models such as Long-Short Term Memory (LSTMs) and…
Descriptors: Time, Models, Artificial Intelligence, Bayesian Statistics
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Meng, Qingquan; Jia, Jiyou; Zhang, Zhiyong – Interactive Technology and Smart Education, 2020
Purpose: The purpose of this study is to verify the effect of smart pedagogy to facilitate the high order thinking skills of students and to provide the design suggestion of curriculum and intelligent tutoring systems in smart education. Design/methodology/approach: A smart pedagogy framework was designed. The quasi-experiment was conducted in a…
Descriptors: Thinking Skills, Instructional Effectiveness, Technology Integration, Intelligent Tutoring Systems
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Serhan, Derar; Almeqdadi, Farouq – International Journal of Technology in Education and Science, 2020
Enhancing students' conceptual understanding and increasing student motivation to effectively participate in classroom discussions are important for instructors of mathematics. Web-based homework management systems provide alternatives to the traditional pen-and-paper based approaches. In addition, these tools facilitate the creation of a…
Descriptors: Student Attitudes, Mathematics Instruction, Homework, Assignments
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Huang, Tao; Liang, Mengyi; Yang, Huali; Li, Zhi; Yu, Tao; Hu, Shengze – International Educational Data Mining Society, 2021
Influenced by COVID-19, online learning has become one of the most important forms of education in the world. In the era of intelligent education, knowledge tracing (KT) can provide excellent technical support for individualized teaching. For online learning, we come up with a new knowledge tracing method that integrates mathematical exercise…
Descriptors: Mathematics Instruction, Teaching Methods, Online Courses, Distance Education
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Wu, Huey-Min – Educational Psychology, 2019
Based on a cognitive diagnostic model, an online individualised tutor program was developed in this study. An experiment was conducted in practical educational settings exploring the effectiveness of the online individualised tutor remedial program based on the diagnostic reports of the cognitive diagnostic model. The methodology of this study was…
Descriptors: Mathematics Instruction, Intelligent Tutoring Systems, Instructional Effectiveness, Teaching Methods
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Walkington, Candace; Bernacki, Matthew L. – Journal of Experimental Education, 2018
Instruction can be made relevant to students when it draws upon and utilizes their interests, experiences, and "funds of knowledge" in productive ways to support classroom learning. This approach has been referred to as "context personalization." In this paper, we discuss the cognitive basis of personalization interventions,…
Descriptors: Individualized Instruction, Instructional Design, Relevance (Education), Cognitive Processes
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Bernacki, Matthew L.; Walkington, Candace – Journal of Educational Psychology, 2018
Context personalization--the incorporation of students' out-of-school interests into learning tasks--has recently been shown to positively affect students' situational interest and their performance and learning in mathematics. However, few studies have shown effects on both interest and achievement, drawing into question whether context…
Descriptors: High School Students, Student Interests, Individualized Instruction, Mathematics Instruction
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