Abstract
Nowadays, building intelligent systems for science, technology, engineering, and math (STEM) education is necessary to support the studying of learners. Intelligent problem solver (IPS) is a system that can be able to solve or tutor how to solve the problems automatically. Learners only declare hypothesis and goal of problems based on a sufficient specification language. They can request the program to solve it automatically or to give instructions that help them to solve it themselves. Knowledge representation plays a vital role in these kinds of intelligent systems. There are various methods for knowledge representation; however, they do not meet the requirements of an IPS in STEM education. In this paper, we propose the criteria of a knowledge model for an IPS in education. These criteria orient to develop a method for knowledge representation to meet actual requirements in practice, especially pedagogical requirements. For proving the effectiveness of these criteria, a knowledge model is also constructed. This model can satisfy these criteria and be applied to build IPS for courses, such as mathematics and physics.
Highlights
Knowledge representation plays a vital role in designing intelligent systems
We propose the criteria of a method to represent the knowledge of an Intelligent problem solver (IPS) in STEM education. e method for knowledge representation includes a knowledge model, model of problems, and reasoning method to solve problems
(i) is method is built based on (i) is method has not yet (i) is method is built based (i) is method is built based on the the solid mathematical structure built based on a solid on a particular mathematical solid mathematical structure (ii) Problems can be modeled mathematical foundation structure (ii) Problems can be modeled, and based on the knowledge model (ii) It has not yet had a model (ii) is method has a model of algorithms for solving them are (iii) e finiteness and of general problems in the general problems based on its designed based on the knowledge effectiveness of the algorithms for knowledge domain knowledge model model solving those problems are proved
Summary
Knowledge representation plays a vital role in designing intelligent systems. Science, technology, engineering, and math (STEM) education emphasizes connections about concepts across different STEM fields to treat STEM education as a whole [1]. E structure of those components can be used to design algorithms for reasoning (ii) Criteria can be used to build practical, intelligent systems, especially for IPS in courses problem-solving process ose criteria are used to evaluate standards according to the unique characteristics of specific combinations of software development projects [21]. Those criteria are not suitable for the characteristics of intelligent educational software: Build the criteria for software development to adapt to the pedagogical criteria of the intelligent learning system. (i) is method is built based on (i) is method has not yet (i) is method is built based (i) is method is built based on the the solid mathematical structure built based on a solid on a particular mathematical solid mathematical structure (ii) Problems can be modeled mathematical foundation structure (ii) Problems can be modeled, and based on the knowledge model (ii) It has not yet had a model (ii) is method has a model of algorithms for solving them are (iii) e finiteness and of general problems in the general problems based on its designed based on the knowledge effectiveness of the algorithms for knowledge domain knowledge model model solving those problems are proved
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Applied Computational Intelligence and Soft Computing
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
