In recent years,the rapid development of artificial intelligence(AI)technology has been driving profound transformations in higher education.As a fundamental course in science and engineering disciplines,Advanced Math...In recent years,the rapid development of artificial intelligence(AI)technology has been driving profound transformations in higher education.As a fundamental course in science and engineering disciplines,Advanced Mathematics plays a crucial role in cultivating students’logical thinking and innovative capabilities.However,the current teaching models exhibit significant shortcomings in fostering students’ability to identify and solve problems,primarily reflected in the monotony of teaching content,the limitations of students’thinking,and the constraints of instructional methods.In response to these issues,this paper proposes an AI-based teaching approach for Advanced Mathematics.By utilizing scenario simulations to guide students in discovering problems and employing modeling tools to assist them in solving problems in real time,the study constructs a comprehensive teaching model that spans the entire process from problem identification to problem resolution.Research findings indicate that the application of AI technology can effectively enhance students’abilities in problem awareness,logical reasoning,and creative thinking.This study provides both theoretical support and practical reference for the reform of Advanced Mathematics education and the innovation of higher-level talent cultivation models.展开更多
Solving Algebraic Problems with Geometry Diagrams(APGDs)poses a significant challenge in artificial intelligence due to the complex and diverse geometric relations among geometric objects.Problems typically involve bo...Solving Algebraic Problems with Geometry Diagrams(APGDs)poses a significant challenge in artificial intelligence due to the complex and diverse geometric relations among geometric objects.Problems typically involve both textual descriptions and geometry diagrams,requiring a joint understanding of these modalities.Although considerable progress has been made in solving math word problems,research on solving APGDs still cannot discover implicit geometry knowledge for solving APGDs,which limits their ability to effectively solve problems.In this study,a systematic and modular three-phase scheme is proposed to design an algorithm for solving APGDs that involve textual and diagrammatic information.The three-phase scheme begins with the application of the statetransformer paradigm,modeling the problem-solving process and effectively representing the intermediate states and transformations during the process.Next,a generalized APGD-solving approach is introduced to effectively extract geometric knowledge from the problem’s textual descriptions and diagrams.Finally,a specific algorithm is designed focusing on diagram understanding,which utilizes the vectorized syntax-semantics model to extract basic geometric relations from the diagram.A method for generating derived relations,which are essential for solving APGDs,is also introduced.Experiments on real-world datasets,including geometry calculation problems and shaded area problems,demonstrate that the proposed diagram understanding method significantly improves problem-solving accuracy compared to methods relying solely on simple diagram parsing.展开更多
基金supported by the 2023 Teaching Reform and Research Project of China University of Petroleum(Beijing),Karamay Campus(Grant No.JG2023048)the 2024 National Undergraduate Innovation and Entrepreneurship Training Program of China(Project No.202419414009)the 2024 General Program of the Natural Science Foundation of Xinjiang Uygur Autonomous Region(Grant No.2024D01A160).
文摘In recent years,the rapid development of artificial intelligence(AI)technology has been driving profound transformations in higher education.As a fundamental course in science and engineering disciplines,Advanced Mathematics plays a crucial role in cultivating students’logical thinking and innovative capabilities.However,the current teaching models exhibit significant shortcomings in fostering students’ability to identify and solve problems,primarily reflected in the monotony of teaching content,the limitations of students’thinking,and the constraints of instructional methods.In response to these issues,this paper proposes an AI-based teaching approach for Advanced Mathematics.By utilizing scenario simulations to guide students in discovering problems and employing modeling tools to assist them in solving problems in real time,the study constructs a comprehensive teaching model that spans the entire process from problem identification to problem resolution.Research findings indicate that the application of AI technology can effectively enhance students’abilities in problem awareness,logical reasoning,and creative thinking.This study provides both theoretical support and practical reference for the reform of Advanced Mathematics education and the innovation of higher-level talent cultivation models.
基金supported by the National Natural Science Foundation of China(No.61977029)the Fundamental Research Funds for the Central Universities,CCNU(No.3110120001).
文摘Solving Algebraic Problems with Geometry Diagrams(APGDs)poses a significant challenge in artificial intelligence due to the complex and diverse geometric relations among geometric objects.Problems typically involve both textual descriptions and geometry diagrams,requiring a joint understanding of these modalities.Although considerable progress has been made in solving math word problems,research on solving APGDs still cannot discover implicit geometry knowledge for solving APGDs,which limits their ability to effectively solve problems.In this study,a systematic and modular three-phase scheme is proposed to design an algorithm for solving APGDs that involve textual and diagrammatic information.The three-phase scheme begins with the application of the statetransformer paradigm,modeling the problem-solving process and effectively representing the intermediate states and transformations during the process.Next,a generalized APGD-solving approach is introduced to effectively extract geometric knowledge from the problem’s textual descriptions and diagrams.Finally,a specific algorithm is designed focusing on diagram understanding,which utilizes the vectorized syntax-semantics model to extract basic geometric relations from the diagram.A method for generating derived relations,which are essential for solving APGDs,is also introduced.Experiments on real-world datasets,including geometry calculation problems and shaded area problems,demonstrate that the proposed diagram understanding method significantly improves problem-solving accuracy compared to methods relying solely on simple diagram parsing.
