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Grubišic, Ani; Žitko, Branko; Stankov, Slavomir – Journal of Technology and Science Education, 2020
In intelligent e-learning systems that adapt a learning and teaching process to student knowledge, it is important to adapt the system as quickly as possible. However, adaptation is not possible until the student model is initialized. In this paper, a new approach to student model initialization using domain knowledge representative subset is…
Descriptors: Electronic Learning, Educational Technology, Models, Intelligent Tutoring Systems
Suraweera, Pramuditha; Mitrovic, Antonija; Martin, Brent – International Journal of Artificial Intelligence in Education, 2010
Intelligent Tutoring Systems (ITS) are effective tools for education. However, developing them is a labour-intensive and time-consuming process. A major share of the effort is devoted to acquiring the domain knowledge that underlies the system's intelligence. The goal of this research is to reduce this knowledge acquisition bottleneck and better…
Descriptors: Intelligent Tutoring Systems, Programming, Engineering, Tutoring
Colace, Francesco; De Santo, Massimo; Gaeta, Matteo – Interactive Technology and Smart Education, 2009
Purpose: The development of adaptable and intelligent educational systems is widely considered one of the great challenges in scientific research. Among key elements for building advanced training systems, an important role is played by methodologies chosen for knowledge representation. In this scenario, the introduction of ontology formalism can…
Descriptors: Electronic Learning, Knowledge Representation, Bayesian Statistics, Mathematics
Baschera, Gian-Marco; Gross, Markus – International Journal of Artificial Intelligence in Education, 2010
We present an inference algorithm for perturbation models based on Poisson regression. The algorithm is designed to handle unclassified input with multiple errors described by independent mal-rules. This knowledge representation provides an intelligent tutoring system with local and global information about a student, such as error classification…
Descriptors: Foreign Countries, Spelling, Intelligent Tutoring Systems, Prediction
Zhou, Gang – 1994
Research in the area of knowledge-based tutoring systems (KBTS) and intelligent tutoring systems (ITS) has great implications for computer applications in education and training. In a KBTS, course material is represented independently of teacher procedures, so that problems and remedial comments can be generated differently for each student. Such…
Descriptors: Cognitive Style, Computer System Design, Curriculum Development, Instructional Development
Aroyo, Lora; Mizoguchi, Riichiro – Journal of Interactive Learning Research, 2004
The ultimate aim of this research is to specify and implement a general authoring framework for content and knowledge engineering for Intelligent Educational Systems (IES). In this context we attempt to develop an authoring tool supporting this framework that is powerful in its functionality, generic in its support of instructional strategies and…
Descriptors: Educational Strategies, Engineering, Programming, Intelligent Tutoring Systems
Van Rosmalen, Peter; Vogten, Hubert; Van Es, Rene; Passier, Harrie; Poelmans, Patricia; Koper, Rob – Educational Technology & Society, 2006
The objective of this paper is to introduce a standards-based model for adaptive e-learning and to investigate the conditions and tools required by authors to implement this model. Adaptation in the context of e-learning is about creating a learner experience that purposely adjusts to various conditions over a period of time with the intention of…
Descriptors: Educational Technology, Instructional Design, Web Based Instruction, Electronic Learning

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