University of South Florida (USF) M3 Publishing
Abstract
The paper explores the ethical integration of AI in Challenge-Based Learning (CBL) within higher education. CBL fosters critical thinking, interdisciplinary collaboration, and real-world problem-solving. AI enhances CBL by providing personalized learning, adaptive problem-solving, and real-time feedback. However, ethical concerns—such as algorithmic bias, data privacy, faculty roles, and governance—must be addressed. The paper proposes a framework for responsible AI integration, emphasizing inclusive access, data ethics, human-AI collaboration, governance, interdisciplinary co-design, iterative ethics, and digital literacy. AI can augment learning, improve scalability, and enhance faculty roles, but risks like inequity, over-reliance, and weak accountability must be mitigated. The framework ensures AI aligns with academic integrity, institutional values, and the evolving needs of higher education.
DOI
https://www.doi.org/10.5038/9781955833127
Recommended Citation
Dogan, S. (2024). Ethical intelligence: Responsible AI integration in challenge-based learning. In W. B. James, C. Cobanoglu, & M. Cavusoglu (Eds.), Advances in global education and research (Vol. 5, pp. 1–11). USF M3 Publishing. https://www.doi.org/10.5038/9781955833127
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License
