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Shakya, Anup; Rus, Vasile; Venugopal, Deepak – International Educational Data Mining Society, 2021
Predicting student problem-solving strategies is a complex problem but one that can significantly impact automated instruction systems since they can adapt or personalize the system to suit the learner. While for small datasets, learning experts may be able to manually analyze data to infer student strategies, for large datasets, this approach is…
Descriptors: Prediction, Problem Solving, Intelligent Tutoring Systems, Learning Strategies
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Xiang Wu; Huanhuan Wang; Yongting Zhang; Baowen Zou; Huaqing Hong – IEEE Transactions on Learning Technologies, 2024
Generative artificial intelligence has become the focus of the intelligent education field, especially in the generation of personalized learning resources. Current learning resource generation methods recommend customized courses based on learning styles and interests, improving learning efficiency. However, these methods cannot generate…
Descriptors: Artificial Intelligence, Individualized Instruction, Intelligent Tutoring Systems, Cognitive Style
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Thapliyal, Monika; Ahuja, Neelu Jyothi; Shankar, Achyut; Cheng, Xiaochun; Kumar, Manoj – Journal of Computing in Higher Education, 2022
This paper presents the ontological design and implementation of the differentiated learning environment in the domain model of an intelligent tutoring system for children with specific learning disabilities. It addresses the learners need for differentiated instruction in a preferential learning environment. The proposed model helps to identify…
Descriptors: Individualized Instruction, Intelligent Tutoring Systems, Students with Disabilities, Learning Disabilities
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Dos Santos, Luis Miguel – International Journal of Education and Practice, 2019
Effective teaching and learning strategy is one of the most important topics in the field of teachers' professional development. Teachers' education and pre-service teachers' training programmes provide necessary coursework, field experience, and student teaching internship experience to pre-service, potential, and second career teachers who are…
Descriptors: Preservice Teachers, Teacher Education Programs, Problem Solving, Models
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VanLehn, Kurt; Zhang, Lishan; Burleson, Winslow; Girard, Sylvie; Hidago-Pontet, Yoalli – IEEE Transactions on Learning Technologies, 2017
This project aimed to improve students' learning and task performance using a non-cognitive learning companion in the context of both a tutor and a meta-tutor. The tutor taught students how to construct models of dynamic systems and the meta-tutor taught students a learning strategy. The non-cognitive learning companion was designed to increase…
Descriptors: Metacognition, Learning Strategies, Nonverbal Communication, High School Students
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Arendale, David R. – International Journal of Higher Education, 2014
The Peer Assisted Learning (PAL) program at the University of Minnesota is a primary academic support program for historically difficult, introductory college courses that serve as gatekeepers to academic degree programs. Based upon operating principles of other academic support programs and educational theories, PAL is integrated into the courses…
Descriptors: Cooperative Learning, Communities of Practice, Self Directed Groups, Study
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Aleven, Vincent; Roll, Ido; McLaren, Bruce M.; Koedinger, Kenneth R. – Educational Psychologist, 2010
Assessment of students' self-regulated learning (SRL) requires a method for evaluating whether observed actions are appropriate acts of self-regulation in theEv specific learning context in which they occur. We review research that has resulted in an automated method for context-sensitive assessment of a specific SRL strategy, help seeking while…
Descriptors: Feedback (Response), Help Seeking, Intelligent Tutoring Systems, Tutoring
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Feng, Mingyu, Ed.; Käser, Tanja, Ed.; Talukdar, Partha, Ed. – International Educational Data Mining Society, 2023
The Indian Institute of Science is proud to host the fully in-person sixteenth iteration of the International Conference on Educational Data Mining (EDM) during July 11-14, 2023. EDM is the annual flagship conference of the International Educational Data Mining Society. The theme of this year's conference is "Educational data mining for…
Descriptors: Information Retrieval, Data Analysis, Computer Assisted Testing, Cheating
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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
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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
Barrus, Angela – ProQuest LLC, 2013
This study empirically evaluated the effectiveness of the instructional design, learning tools, and role of the teacher in three versions of a semester-long, high-school remedial Algebra I course to determine what impact self-regulated learning skills and learning pattern training have on students' self-regulation, math achievement, and…
Descriptors: Learning Strategies, Independent Study, High School Students, Instructional Design
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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
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Gynnild, Vidar; Holstad, Anders; Myrhaug, Dag – International Journal of Science Education, 2007
This paper presents a number of case studies in Oceanography, an optional module in the third/fourth year of a Master of Science programme at Norwegian University of Science and Technology. The main objective was to gain more thorough insights into student learning by examining two sets of individual oral examinations. In addition, all students…
Descriptors: Psychotherapy, Oceanography, Case Studies, Engineering Education
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Vos, H. J. – Computers in Human Behavior, 1999
Formulates decision rules for adapting the appropriate amount of instruction to learning needs in intelligent-tutoring systems. Highlights include minimax decision theory (a minimum information approach), a binomial model, and a comparison of the Bayesian decision component in the Minnesota Adaptive Instructional System and the minimax strategy.…
Descriptors: Comparative Analysis, Decision Making, Instructional Design, Intelligent Tutoring Systems
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Hu, Xiangen, Ed.; Barnes, Tiffany, Ed.; Hershkovitz, Arnon, Ed.; Paquette, Luc, Ed. – International Educational Data Mining Society, 2017
The 10th International Conference on Educational Data Mining (EDM 2017) is held under the auspices of the International Educational Data Mining Society at the Optics Velley Kingdom Plaza Hotel, Wuhan, Hubei Province, in China. This years conference features two invited talks by: Dr. Jie Tang, Associate Professor with the Department of Computer…
Descriptors: Data Analysis, Data Collection, Graphs, Data Use
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