This conceptual review explores the integration of AI tools in science curricula, highlighting challenges and potential benefits for higher education institutions.
Key Points
The integration of AI into science curricula shows promise, especially when aligned with the constructivist pedagogical framework.
AI applications are most effective when tailored to meet learner requirements and disciplinary structures, as shown in notable case studies.
Several challenges arise during implementation, including faculty readiness and algorithmic bias, which must be addressed for success.
Five key recommendations are provided to improve AI integration in higher education, emphasizing interdisciplinary collaboration and equitable infrastructure.
Cite This Study
Konstantinos Τ. Kotsis (2025) studied this question.