| Issue |
BIO Web Conf.
Volume 190, 2025
The 3rd International Conference on Biology Education, Science, and Technology (INCOBEST 2025)
|
|
|---|---|---|
| Article Number | 01009 | |
| Number of page(s) | 18 | |
| DOI | https://doi.org/10.1051/bioconf/202519001009 | |
| Published online | 09 October 2025 | |
Using AI to Test Biological Systematic Thinking Based on Pisa and IB Standards
Biology department, Bukhara State University, 11, Muhammad Igbol st., Bukhara, 705018 Uzbekistan
This research examines a diagnostic model based on artificial intelligence (AI) along with PISA and IB international standards to assess the systemic thinking abilities of biology students (both bachelor’s and master’s) in Uzbekistan’s higher education system. The study investigated this model’s effectiveness in evaluating the professional preparation of future biology teachers. The research involved 1,340 students from pedagogical higher education institutions across the country. Their systemic thinking abilities were tested through complex situational tasks requiring interdisciplinary connections. PISA and IB criteria, along with AI algorithms, were used to analyze responses. Statistical analysis and correlation studies in SPSS software showed that the AI-based assessment system was 25% more effective at identifying students’ problem-solving and systemic thinking skills compared to traditional tests. The research also found that some students face difficulties adapting to global educational standards and lack sufficient skills in analyzing complex scientific data. The novelty of this research lies in creating a validated AI-based model that adapts PISA and IB assessment systems to measure students’ professional competencies in the Central Asian higher education context. These results provide a solid scientific and practical foundation for aligning biology education in Uzbekistan with international standards and improving the quality of professional training.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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