| Authors |
Zavala, Genaro ; Melendez Anzures, Frank Eduardo ; Dominguez, Angeles ; Gudonienė, Daina ; Ballatore, Maria Giulia ; Orehovački, Tihomir ; Pereira Pessoa, Marcus V ; Rojas López, Juan Carlos ; Grijalva Quiñonez, Christian Samhir |
| Abstract [eng] |
Introduction Artificial intelligence (AI) is transforming all sectors of society, and higher education is no exception. In STEM (Science, Technology, Engineering, and Mathematics) education, AI has the potential to revolutionize teaching methodologies by enhancing personalized learning, automating assessment processes, and facilitating access to advanced knowledge (Berge & Haugsevje, 2024; Uzumcu & Acilmis, 2024). However, integrating AI into STEM education presents multiple challenges that have hindered its widespread adoption, exacerbating existing gaps in access to technology, digital literacy, and collaboration opportunities (Adeshola & Adepoju, 2024). One of the most pressing issues is the gap in AI literacy (Chandel & Lim, 2024). Many educators lack fundamental knowledge about AI, its applications, and its impact on education, limiting their ability to leverage its pedagogical benefits. Unlike other educational innovations, AI requires technical skills and a deep understanding of its ethical implications and applicability across different educational contexts. The lack of AI literacy restricts its adoption in the classroom and leaves students unprepared for a future where AI usage will be an essential competency in their professional careers (Sperling et al., 2024). Another significant challenge is the disparity in access to AI resources and tools. While well-funded universities and institutions have begun integrating AI tools into their curricula, others lack the necessary technological infrastructure (Michel-Villarreal et al., 2023). Limited access to advanced software, appropriate hardware, and AI-driven educational platforms creates disparities between those institutions able to innovate and those that remain behind. This inequality is particularly pronounced in emerging countries or regions with lower investment in STEM education, where both educators and students struggle to have access to cutting-edge technology (Bulathwela et al., 2024). In this context, the principles of open science offer a valuable framework for addressing many of these challenges. Open and reproducible practices in education, such as the co-creation of resources, shared pedagogical strategies, and equitable access to tools, can democratize AI integration and foster a more inclusive STEM ecosystem (Azevedo et al., 2021). [...]. |
