An ethical AI framework for STEM education

A mixed-methods evaluation

Authors

DOI:

https://doi.org/10.32674/04054e51

Keywords:

artificial intelligence in education, federated learning, blockchain technology, educational ethics, STEM pedagogy, data privacy

Abstract

This study introduces a novel ethical AI framework for undergraduate STEM education that prioritizes privacy, transparency, and accountability. Employing a convergent parallel mixed-methods design, this study engaged 412 undergraduate STEM students, 15 faculty members, and 10 administrators across three universities over two semesters. Data collection integrated quantitative learning analytics with qualitative stakeholder interviews and focus groups to capture both measurable outcomes and lived experiences. The results demonstrate that responsible AI design significantly improves student engagement (35%), instructor acceptance (78%), and reduces performance gaps between student groups by 40%, all while maintaining the model's predictive accuracy at 89%. This research demonstrates that AI can be designed to be both technically robust and ethically committed.

Author Biographies

  • Meysam Abedi, University of Eastern Finland

    MEYSAM ABEDI, PhD Candidate, is a doctoral researcher in the School of Computing at the University of Eastern Finland. His research focuses on ethical AI frameworks, federated learning, and privacy-preserving technologies in educational contexts. With over 20 years of professional experience in machine learning and artificial intelligence, his work bridges theoretical research and practical applications in STEM education. Email: meyabedi@uef.fi

  • Ismaila Temitayo Sanusi, University of Eastern Finland

    ISMAILA TEMITAYO SANUSI, PhD, is a Postdoctoral Researcher in the School of Computing at the University of Eastern Finland. His research interests include democratizing machine learning and artificial intelligence through K-12 education, computational thinking, and educational technology. He focuses on making AI and ML accessible to diverse learners and understanding how to effectively teach these concepts in educational settings. Email: ismaila.sanusi@uef.fi

  • Markku Tukiainen, University of Eastern Finland

    MARKKU TUKIAINEN, PhD, is a Professor and Head of the School of Computing at the University of Eastern Finland. His research areas encompass educational technology, software engineering, human-computer interaction (HCI), ICT4D, computer science education, and extended realities (XR, VR, AR, MR). He leads research initiatives that bridge technology and pedagogy to enhance learning experiences. Email: markku.tukiainen@uef.fi

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Additional Files

Published

2026-07-05

Issue

Vol. 25 (2026): American Journal of STEM Education

Section

STEM Education (regular)

License

Copyright (c) 2026 Meysam Abedi, Ismaila Temitayo Sanusi, Markku Tukiainen

Creative Commons License

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

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

Abedi, M., Sanusi, I. T., & Tukiainen, M. (2026). An ethical AI framework for STEM education: A mixed-methods evaluation. American Journal of STEM Education, 25, 121-146. https://doi.org/10.32674/04054e51