A pedagogical approach: toward leveraging mathematical modeling and AI to support integrating humanities into STEM education
Quintana M. Clark
Source record
Source: Crossref
Published: Jan 28, 2025
DOI: 10.3389/feduc.2024.1396104
Open original source ↗Source abstract
This paper examines the transformative potential of integrating humanities into STEM education using interdisciplinary approaches, AI, and Model Eliciting Activities (MEAs). The integration is motivated by the increasing complexity of global challenges, such as climate change, which demand solutions that extend beyond traditional STEM boundaries and incorporate ethical, cultural, and societal considerations. This study profiles a multi-year, NSF-funded project focused on enhancing STEM literacy among underrepresented minority students through agricultural sciences-based MEAs that address key societal challenges in health, energy, urban green spaces, and food security. The paper details the curriculum’s design principles, emphasizing real-world, culturally relevant contexts. Results indicate that while quantitative measures show limited significant changes in interest and motivation, qualitative findings highlight increased student engagement, especially regarding real-world issues. The study underscores the importance of structural and interactional components, such as culturally relevant pedagogy, for successful curriculum implementation. Future research is recommended to explore broader applications of this model across diverse educational settings, aiming to refine interdisciplinary educational frameworks that equip students with technical skills and ethical awareness to navigate societal challenges responsibly. This case study provides a framework for educators seeking to implement interdisciplinary approaches that prepare students to address complex global challenges by integrating technical skills with ethical and cultural understanding.
Evidence graph
No public relationships recorded yet.
Integrity note: This page is a factual metadata record created by deterministic ingestion. It is not a claim that the work moves a mathematical frontier or has been independently verified.