METHODOLOGICAL APPROACHES TO TEACHING DEFINITE AND INDEFINITE INTEGRALS BASED ON ARTIFICIAL INTELLIGENCE IN HIGHER EDUCATION

Authors

  • Qo'janboyev Ruslanbek Zamirbek ugli, Botirova Mavluda To’xtasin kizi Andijan State Pedagogical Institute Student of Chemistry, Andijan State Pedagogical Institute Teacher of the Department of Mathematics and Informatics

DOI:

https://doi.org/10.5281/zenodo.20139736

Keywords:

artificial intelligence, definite integral, indefinite integral, mathematical analysis, methodological approach, digital pedagogy, interactive learning, mathematical competence, GeoGebra, ChatGPT.

Abstract

This article analyzes methodological approaches to teaching definite and indefinite integrals in higher education based on artificial intelligence technologies. The study highlights the didactic possibilities of artificial intelligence tools in teaching mathematical analysis, their role in developing students’ mathematical thinking, and their effectiveness in visualization and interactive teaching of integral topics. In addition, the pedagogical mechanisms for improving the teaching of integral concepts through digital platforms such as GeoGebra, Wolfram Mathematica, ChatGPT and other educational technologies are substantiated. During the research, methods such as analysis, comparative analysis, pedagogical observation, and methodological modeling were used. The results showed that the use of artificial intelligence technologies contributes to the development of students’ independent thinking, mathematical competence, and problem-solving skills.

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References

[1] Thomas G.B. Calculus and Analytic Geometry. — Pearson Education, 2018.

[2] Selwyn N. Education and Technology: Key Issues and Debates. — Bloomsbury Publishing, 2017.

[3] Luckin R. Machine Learning and Human Intelligence. — UCL Institute of Education Press, 2018.

[4] Tall D. Advanced Mathematical Thinking. — Springer, 2002.

[5] Muslimov N.A. Fundamentals of Pedagogical Competence and Innovative Activity. — Tashkent, 2015.

[6] Tall D. Advanced Mathematical Thinking. — Springer, 2002.

[7] Selwyn N. Education and Technology: Key Issues and Debates. — Bloomsbury Publishing, 2017.

[8] Luckin R. Machine Learning and Human Intelligence. — UCL Institute of Education Press, 2018.

[9] Thomas G.B. Calculus and Analytic Geometry. — Pearson Education, 2018.

[10] Hiebert J. Conceptual and Procedural Knowledge in Mathematics. — Routledge, 2013.

[11] Muslimov N.A. Fundamentals of Pedagogical Competence and Innovative Activity. — Tashkent, 2015.

[12] Tall D. Advanced Mathematical Thinking. — Springer, 2002.

[13] Thomas G.B. Calculus and Analytic Geometry. — Pearson Education, 2018.

[14] Luckin R. Machine Learning and Human Intelligence. — UCL Institute of Education Press, 2018.

[15] Hiebert J. Conceptual and Procedural Knowledge in Mathematics. — Routledge, 2013.

[16] Selwyn N. Education and Technology: Key Issues and Debates. — Bloomsbury Publishing, 2017.

[17] Jonassen D. Learning to Solve Problems with Technology. — Routledge, 2004.

[18] Muslimov N.A. Fundamentals of Pedagogical Competence and Innovative Activity. — Tashkent, 2015.

[19] Tall D. Advanced Mathematical Thinking. — Springer, 2002.

[20] Thomas G.B. Calculus and Analytic Geometry. — Pearson Education, 2018.

[21] Selwyn N. Education and Technology: Key Issues and Debates. — Bloomsbury Publishing, 2017.

[22] Jonassen D. Learning to Solve Problems with Technology. — Routledge, 2004.

[23] Luckin R. Machine Learning and Human Intelligence. — UCL Institute of Education Press, 2018.

[24] Muslimov N.A. Fundamentals of Pedagogical Competence and Innovative Activity. — Tashkent, 2015.

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Published

2026-05-12

Issue

Vol. 5 No. 5 (2026): Journal of Multidisciplinary Sciences and Innovations

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Authors retain the copyright of their manuscripts, and all Open Access articles are disseminated under the terms of the Creative Commons Attribution License 4.0 (CC-BY), which licenses unrestricted use, distribution, and reproduction in any medium, provided that the original work is appropriately cited. The use of general descriptive names, trade names, trademarks, and so forth in this publication, even if not specifically identified, does not imply that these names are not protected by the relevant laws and regulations.

How to Cite

METHODOLOGICAL APPROACHES TO TEACHING DEFINITE AND INDEFINITE INTEGRALS BASED ON ARTIFICIAL INTELLIGENCE IN HIGHER EDUCATION. (2026). Journal of Multidisciplinary Sciences and Innovations, 5(5), 756-763. https://doi.org/10.5281/zenodo.20139736

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