Criteria of a Knowledge model for an Intelligent Problems Solver in Education

Nguyen, Hien D.; Nhon, V.; Tran, Nha; Pha, Xuan Hau

doi:10.1109/kse.2018.8573434

Cited by 9 publications

(14 citation statements)

References 4 publications

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“…In this section, the method for integrating this knowledge kernel and the knowledge of operators and functions is applied to construct the knowledge bases of linear algebra and graph theory. These knowledge bases are the foundations for designing the intelligent problem solver (IPS) for the corresponding courses, which satisfy the criteria of IPS in mathematics education [23].…”

Section: Application For Intelligent Systems In Educationmentioning

confidence: 99%

“…The integrating model between kernel ontology and the knowledge of functions was used to design the knowledge base of IPS in graph theory, as in Section 5.3. The knowledge base of this system meets requirements of an IPS in education [23]. The students used this system to support their learning of graph theory at university.…”

Section: Intelligent Problem Solver In Graph Theorymentioning

confidence: 99%

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A Method of Ontology Integration for Designing Intelligent Problem Solvers

2019

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Nowadays, designing knowledge-based systems which involve knowledge from different domains requires deep research of methods and techniques for knowledge integration, and ontology integration has become the foundation for many recent knowledge integration methods. To meet the requirements of real-world applications, methods of ontology integration need to be studied and developed. In this paper, an ontology model used as the knowledge kernel is presented, consisting of concepts, relationships between concepts, and inference rules. Additionally, this kernel is also added to other knowledge, such as knowledge of operators and functions, to form an integrated knowledge-based system. The mechanism of this integration method works upon the integration of the knowledge components in the ontology structure. Besides this, problems and the reasoning method to solve them on the integrated knowledge domain are also studied. Many related problems in the integrated knowledge domain and the reasoning method for solving them are also studied. Such an integrated model can represent the real-world knowledge domain about operators and functions with high accuracy and effectiveness. The ontology model can also be applied to build knowledge bases for intelligent problem solvers (IPS) in many mathematical courses in college, such as linear algebra and graph theory. These IPSs have great potential in helping students perform better in those college courses.

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Section: Application For Intelligent Systems In Educationmentioning

confidence: 99%

Section: Intelligent Problem Solver In Graph Theorymentioning

confidence: 99%

A Method of Ontology Integration for Designing Intelligent Problem Solvers

2019

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“…An IPS in education can solve many kinds of exercises from basic to advanced kinds in the course. It has to satisfy these requirements [4], [6], [36], [48]:…”

Section: Introductionmentioning

confidence: 99%

“…• The program is useful for studying. For meeting these requirements, according to [4], [6], [7], [48], a method for building the knowledge base of IPS has to satisfy the following criteria:…”

Section: Introductionmentioning

confidence: 99%

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A Method for Knowledge Representation to Design Intelligent Problems Solver in Mathematics Based on Rela-Ops Model

et al. 2020

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Knowledge-base is a fundamental platform in the architecture of an intelligent system. Relations and operators are popular knowledge in practice knowledge domains. In this paper, we propose a method to represent the model by combining these kinds of knowledge, called the Rela-Ops model. This model includes foundation components consisting of concepts, relations, operators, and inference rules. It is built based on ontology and object-oriented approaches. Besides the structure, each concept of the Rela-Ops model is a class of objects which also have behaviors to solve problems on their own. The processing of algorithms for solving problems on the Rela-Ops model combines the knowledge of relations and operators in the reasoning. Furthermore, we also propose a knowledge model for multiple knowledge domains, in which each sub-domain has the form as the Rela-Ops model. These representation methods have been applied to build knowledge bases of Intelligent Problems Solver (IPS) in mathematics. The knowledge base of 2D-Analytical Geometry in a high-school is built by using the Rela-Ops model, and the knowledge base of Linear Algebra in university is designed by using the model for multiple knowledge domains. The IPS system can automatically solve basic and advanced exercises in respective courses. The reasoning of their solutions is done in a step-by-step approach. It is similar to the solving method by humans. The solutions are also pedagogical and suitable for the learner's level and easy to be used by students studying 2D-Analytical Geometry in high-school and Linear Algebra in university. INDEX TERMS Knowledge representation, knowledge-based systems, intelligent problem-solver, knowledge engineering.

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