Exploring perspectives toward generative artificial intelligence integration in science education: A cross-generational study
In an era where artificial intelligence (AI) is revolutionizing various sectors, its integration into education presents both opportunities and challenges that warrant careful examination. This study explores the perspectives of science faculty members across different generational cohorts on the integration of generative AI (GenAI) in education in the Philippines, aiming to identify targeted areas for improvement. Utilizing a phenomenological approach with a cross-sectional design, the research involved semi-structured, in-depth interviews with 20 faculty members categorized into Generations X, Y (Millennials), and Z. The study sought to understand their knowledge, attitudes, perceived benefits, challenges, ethical concerns, and policy recommendations related to the integration of GenAI in science education. The results indicate varied familiarity with GenAI tools among the generations, with Gen X demonstrating moderate awareness but limited application and some resistance, Gen Y exhibiting diverse uses and concerns, especially in ethics, and Gen Z showing high awareness but perceived minimal practical engagement and confidence. Participants viewed GenAI as beneficial for enhancing efficiency and providing innovative learning tools, yet they also identified challenges such as over-dependence on technology, privacy-related ethical issues, and disparities in access. The study highlights the need for professional development, ethical guidelines, and infrastructure upgrades to ensure equitable GenAI integration. These findings offer valuable insights for developing effective strategies that harness the potential of GenAI while addressing generational differences, ultimately promoting a more seamless and inclusive educational environment.
Institutions
- Sorsogon State University (PH)
Publication Details
- Journal
- Social Sciences & Humanities Open
- Published
- 2025-12-19
- DOI
- https://doi.org/10.1016/j.ssaho.2025.102358
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00