Learning Styles and Adaptive ICT-Based Learning Environment

2008 ◽  
pp. 413-429 ◽  
Author(s):  
Zlatko J. Kovacic
Keyword(s):  
Learning Environment ◽  
Learning Styles ◽  
Intelligent Agents ◽  
Intelligent Systems ◽  
Economies Of Scale ◽  
Adaptive Hypermedia ◽  
Technological Infrastructure ◽  
Hypermedia Learning ◽  
Learning Path ◽  
Determining Factor

This chapter has two aims. First, to provide an overview of learning styles research and secondly, to provide an overview of research in adaptive hypermedia learning environment systems, those where different learning styles are considered and used to create a personalized learning environment. For most distance education institutions individualization of the learning environment for each student is not an option because economies of scale are the determining factor of cost reduction. However, the latest advances in database management, artificial intelligent systems and intelligent agents provide a technological infrastructure for individualizing the learning path for every learner at a lower cost. This chapter focuses on learning styles and how we can integrate and use them as a source of adaptation in an adaptive hypermedia learning environment systems.

Learning Styles and Adaptive ICT-Based Learning Environment

2011 ◽  
pp. 136-152
Author(s):  
Zlatko J. Kovacic
Keyword(s):  
Learning Environment ◽  
Learning Styles ◽  
Intelligent Agents ◽  
Intelligent Systems ◽  
Economies Of Scale ◽  
Adaptive Hypermedia ◽  
Technological Infrastructure ◽  
Hypermedia Learning ◽  
Learning Path ◽  
Determining Factor

This chapter has two aims. First, to provide an overview of learning styles research and secondly, to provide an overview of research in adaptive hypermedia learning environment systems, those where different learning styles are considered and used to create a personalized learning environment. For most distance education institutions individualization of the learning environment for each student is not an option because economies of scale are the determining factor of cost reduction. However, the latest advances in database management, artificial intelligent systems and intelligent agents provide a technological infrastructure for individualizing the learning path for every learner at a lower cost. This chapter focuses on learning styles and how we can integrate and use them as a source of adaptation in an adaptive hypermedia learning environment systems.

Learning Styles and Adaptive ICT-Based Learning Environment

2011 ◽  
pp. 131-152
Author(s):  
Zlatko J. Kovacic
Keyword(s):  
Learning Environment ◽  
Learning Styles ◽  
Intelligent Agents ◽  
Intelligent Systems ◽  
Economies Of Scale ◽  
Adaptive Hypermedia ◽  
Technological Infrastructure ◽  
Hypermedia Learning ◽  
Learning Path ◽  
Determining Factor

This chapter has two aims. First, to provide an overview of learning styles research and secondly, to provide an overview of research in adaptive hypermedia learning environment systems, those where different learning styles are considered and used to create a personalized learning environment. For most distance education institutions individualization of the learning environment for each student is not an option because economies of scale are the determining factor of cost reduction. However, the latest advances in database management, artificial intelligent systems and intelligent agents provide a technological infrastructure for individualizing the learning path for every learner at a lower cost. This chapter focuses on learning styles and how we can integrate and use them as a source of adaptation in an adaptive hypermedia learning environment systems.

A Model for an Adaptive Hypermedia Learning System Based on Data Mining Technique

2017 ◽  
pp. 65-85
Author(s):  
Mahnane Lamia ◽  
Mohamed Hafidi
Keyword(s):  
Learning Styles ◽  
Learning Style ◽  
Personal Characteristics ◽  
Learning Objects ◽  
Learning System ◽  
Learning Performance ◽  
Adaptive Hypermedia ◽  
Data Mining Technique ◽  
Pedagogical Strategies ◽  
Hypermedia Learning

Since the learning style of each learner is different. Adaptive hypermedia learning system (AHLS) must fit different learner's needs. A number of AHLS have been developed to support learning styles as a source for adaptation. However, these systems suffer from several problems, namely: less attention was paid to the relationship between learning styles and learning performance. This paper proposes an AHLS model based on learning styles and learning performance. On one hand, the developed prototype will assist a learner in accessing and using learning resources which are adapted according to his/her personal characteristics (in this case his/her learning style and level of knowledge). On the other hand, it will facilitate the learning content teacher in the creation of appropriate learning objects and their application to suitable pedagogical strategies.

scholarly journals Diagnostics of psychological readiness of high school students for research activities in mathematics in the design context of a hybrid intellectual learning environment

2021 ◽  
Vol 54 (6) ◽  
pp. 192-210
Author(s):  
Svetlana N. Dvoryatkina ◽  
◽  
Vera S. Merenkova ◽  
Eugeny I. Smirnov ◽  
◽  
...  
Keyword(s):  
High School Students ◽  
Learning Environment ◽  
Boundary Conditions ◽  
Intelligent Systems ◽  
Intelligent System ◽  
Educational Institution ◽  
Value Orientations ◽  
School Students ◽  
Research Activities ◽  
Scientific Potential

Introduction. The problem of improving the process of organizing and supporting the project and research activities of schoolchildren through intelligent management for the purpose of self-organization of the individual, understanding and comprehending complex mathematical knowledge as a principle of personal development is relevant and far from solved. Intelligent systems provide the process of individualization of learning, the establishment of personalized and computerized feedback of cognitive and creative processes. The purpose of the article is to assess the student's readiness for research activities in the context of designing a hybrid intelligent learning environment. Materials and methods. The assessment of the student's psychological readiness for research activities in the conditions of using a hybrid intellectual environment was carried out on an experimental representative sample of students of 1-2 courses of secondary vocational education (n1=42) and students of the senior classes of secondary schools (n2=30). The diagnosis was carried out using the intelligence structure test of R. Amthauer, the creativity questionnaire of D. Johnson, the test "Individual styles of thinking" by A. Alekseev, L. Gromova, the methods of value orientations by M. Rokich, etc. The significance of the differences was established by means of Student's t-test, Fisher's angular transformation, χ2-test. The results of the study. The assessment of psychological readiness for research activities in mathematics was carried out on the basis of the developed nine parameters of scientific potential. The presented results allow us to pre-set the framework of boundary conditions in order to minimize the imprinting time of a hybrid intelligent system (including the selection of the neural network topology). For all three groups of criteria, differences by gender were established, for example, by the parameter "value orientations" (temp  = 2.26 > tcr = 2.02); by the parameter "creativity" (χemp2 = 6,02 ≥ χcr2 (0,05;2) = 5,99). And also by the type of educational institution, for example, by the parameter “motivation to achieve the result” (φemp = 0,186 > φcr = 1,64). Conclusion. The results of the research are of practical value, as they serve as a technological basis for establishing the boundaries and boundary conditions of the most significant parameters for the effective realization of scientific potential, expressed in the work of a specialized web interface created with the student's personal account.

scholarly journals Agents’ ontologies negotiation in cohesive hybrid intelligent multi-agent systems

2021 ◽  
Vol 2094 (3) ◽  
pp. 032033
Author(s):  
I A Kirikov ◽  
S V Listopad ◽  
A S Luchko
Keyword(s):  
Intelligent Agents ◽  
Intelligent Systems ◽  
Multi Agent Systems ◽  
Labor Costs ◽  
Joint Work ◽  
Working Process ◽  
Agent Systems ◽  
Development Teams ◽  
Multi Agent ◽  
Domain Models

Abstract The paper proposes the model for negotiating intelligent agents’ ontologies in cohesive hybrid intelligent multi-agent systems. Intelligent agent in this study will be called relatively autonomous software entity with developed domain models and goal-setting mechanisms. When such agents have to work together within single hybrid intelligent multi-agent systems to solve some problem, the working process “go wild”, if there are significant differences between the agents’ “points of view” on the domain, goals and rules of joint work. In this regard, in order to reduce labor costs for integrating intelligent agents into a single system, the concept of cohesive hybrid intelligent multi-agent systems was proposed that implement mechanisms for negotiating goals, domain models and building a protocol for solving the problems posed. The presence of these mechanisms is especially important when building intelligent systems from intelligent agents created by various independent development teams.

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