Bridging the Digital Divide: Small Language Models as a Pathway for Physics and Photonics Education in Underdeveloped Regions
2025/06/14 by Asghar Ghorbani, Hanieh Fattahi, Ghorbani, Asghar +1
Arts and Humanities · Computer Science · #Artificial Intelligence (cs.AI) #Computers and Society (cs.CY) #Digital literacy in education #FOS: Computer and information sciences #FOS: Physical sciences #Physics Education (physics.ed-ph) #Second Language Learning and Teaching
paper · pdf · doi:10.48550/arxiv.2506.12403
openalex publication_date 2025/06/14 · openalex created_date 2025/10/13 · openalex updated_date 2026/07/28
Abstract
Limited infrastructure, scarce educational resources, and unreliable internet access often hinder physics and photonics education in underdeveloped regions. These barriers create deep inequities in Science, Technology, Engineering, and Mathematics (STEM) education. This article explores how Small Language Models (SLMs)-compact, AI-powered tools that can run offline on low-power devices, offering a scalable solution. By acting as virtual tutors, enabling native-language instruction, and supporting interactive learning, SLMs can help address the shortage of trained educators and laboratory access. By narrowing the digital divide through targeted investment in AI technologies, SLMs present a scalable and inclusive solution to advance STEM education and foster scientific empowerment in marginalized communities.
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