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Nižnan, Juraj; Pelánek, Radek; Rihák, Jirí – International Educational Data Mining Society, 2015
Intelligent behavior of adaptive educational systems is based on student models. Most research in student modeling focuses on student learning (acquisition of skills). We focus on prior knowledge, which gets much less attention in modeling and yet can be highly varied and have important consequences for the use of educational systems. We describe…
Descriptors: Prior Learning, Models, Intelligent Tutoring Systems, Bayesian Statistics
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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
Rus, Vasile; Lintean, Mihai; Azevedo, Roger – International Working Group on Educational Data Mining, 2009
This paper presents several methods to automatically detecting students' mental models in MetaTutor, an intelligent tutoring system that teaches students self-regulatory processes during learning of complex science topics. In particular, we focus on detecting students' mental models based on student-generated paragraphs during prior knowledge…
Descriptors: Data Analysis, Prior Learning, Cognitive Structures, College Students
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Kabassi, K.; Virvou, M. – Instructional Science: An International Journal of Learning and Cognition, 2006
This paper describes how the Multi-Attribute Utility Theory can be combined with adaptive techniques to improve individualised teaching in an Intelligent Learning Environment (ILE). The ILE is called Web F-SMILE, it operates over the Web and is meant to help novice users learn basic skills of computer use. Tutoring is dynamically adapted to the…
Descriptors: Intelligent Tutoring Systems, Educational Environment, Computer Software, Web Based Instruction
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Gregg, Dawn G. – Learning Organization, 2007
Purpose: The purpose of this paper is to illustrate the advantages of using intelligent agents to facilitate the location and customization of appropriate e-learning resources and to foster collaboration in e-learning environments. Design/methodology/approach: This paper proposes an e-learning environment that can be used to provide customized…
Descriptors: Electronic Learning, Cognitive Style, Student Characteristics, Prior Learning
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Wood, H.; Wood, D. – Computers & Education, 1999
Discusses the application of the theory of contingent tutoring to the design of a computer-based system for algebra. Considers help seeking and analyzes interactions between secondary school students and the computer-based tutoring system to explore the relations between individual differences in learner-tutor interaction, learner's prior…
Descriptors: Algebra, Computer Software Development, Courseware, Help Seeking