Evaluation of an interdisciplinary Project-based STEM model in biotechnology education

Abstract

The integration of STEM education into biotechnology is essential for developing research competence, interdisciplinary thinking, and practical problem-solving skills in future biology teachers. However, the implementation of interdisciplinary STEM models supported by experimental research and artificial intelligence remains limited in biotechnology education. This study aimed to develop and evaluate an interdisciplinary STEM project integrating biotechnology, ecology, chemistry, engineering, mathematics, and artificial intelligence within biology teacher education. A mixed-methods approach combining laboratory experimentation, project-based learning, questionnaires, interviews, and statistical analysis was employed. The STEM project was based on investigating the effects of copper, zinc, and cadmium on the growth of Phaseolus vulgaris, while students applied artificial intelligence tools, including ChatGPT, Claude AI, Python, and OneCompiler, for data processing, visualization, and scientific interpretation. Educational outcomes showed that 83.3% of participants reported mastering the stages of experimental planning, data collection, and data analysis, while 91.7% reported increased interest in biotechnology after completing the project. Participants also reported improved research competence, interdisciplinary understanding, and confidence in applying scientific methods to environmental problems.The scientific novelty of this study lies in the development of an interdisciplinary STEM model that integrates experimental biotechnology, project-based learning, and artificial intelligence into a unified educational framework. The proposed model contributes to strengthening research-oriented biotechnology education and provides a practical approach for preparing future biology teachers capable of addressing interdisciplinary scientific challenges.