ORGANIZING INQUIRY-BASED LEARNING THROUGH ARTIFICIAL INTELLIGENCE: EFFECTIVE METHODS FOR DEVELOPING SCIENTIFIC RESEARCH PROJECTS

Authors

  • Nygymetzhanova Gulzhan Kymbatkyzy Biology and Chemistry Teacher, Teacher-Researcher, Municipal Public Institution "S. Bekbosynov Secondary School", Arkhat Village, Abai District, Abai Region, Republic of Kazakhstan https://orcid.org/0009-0008-8998-7644

DOI:

https://doi.org/10.63034/esr-793

Keywords:

artificial intelligence, inquiry-based learning, scientific research project, mitotic index, EcoShield, microalgae biosystem, prompt engineering, academic integrity

Abstract

This article examines the author's methodology and practical results of organizing students' research activities using artificial intelligence (AI) technologies in the modern educational environment. The author proposes a six-stage algorithm for developing scientific research projects with AI support. The practical section analyzes six real scientific research projects prepared by school students from different regions of Kazakhstan (Almaty City, Abai, Aktobe, and Kyzylorda Regions) as case studies, demonstrating the empirical, mathematical, and analytical effectiveness of AI. A comparative analysis of the time required before and after the implementation of AI tools is presented, and the mentoring role of the teacher and the principles of academic integrity are clearly defined.

References

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Ministry of Education of the Republic of Kazakhstan. (2024). Methodological Guidelines for the Use of Digital Technologies and Artificial Intelligence Tools in Educational Organizations. Astana.

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Luckin, R. (2018). Machine Learning and Human Intelligence: The Future of Education for the 21st Century. London: UCL IOE Press. 230 p.

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Published

2026-07-23

How to Cite

Nygymetzhanova, G. (2026). ORGANIZING INQUIRY-BASED LEARNING THROUGH ARTIFICIAL INTELLIGENCE: EFFECTIVE METHODS FOR DEVELOPING SCIENTIFIC RESEARCH PROJECTS. Eurasian Science Review An International Peer-Reviewed Multidisciplinary Journal, 3(8), 234–245. https://doi.org/10.63034/esr-793