AI- and IoT-Driven Mobile Learning Environments: A Framework for Educational Transformation, Workforce Development, and Digital Inclusion - Hijazi, Shadi; Mokal, Mahvish Nawaz; Halder, Andrina; Victor, Velantina; John, Garrick (International Journal of Interactive Mobile Technologies (iJIM), 2025)
The integration of artificial intelligence (AI) and the Internet of Things (IoT) into mobile learning has gained significant scholarly and industry attention for their potential to deliver adaptive, context-aware, and inclusive educational experiences. AI–IoT-enhanced mobile platforms combine intelligent data analytics, real-time feedback systems, and connected devices to create immersive, location-based, and personalized learning environments. This study examines the design, implementation, and impact of AI–IoT-driven mobile learning ecosystems in advancing educational transformation, workforce development, and digital inclusion. Drawing on socio-technical systems (STS) theory, the study employs a mixed-methods approach, integrating a systematic review of peer-reviewed literature (2018–2025) with multi-sector case studies across K–12, higher education, and industry-based training. The analysis investigates technological features, pedagogical strategies, and deployment frameworks, identifying key benefits such as enhanced learner engagement, improved skill acquisition, greater accessibility for underserved communities, and increased learning autonomy. It also addresses critical challenges, including algorithmic bias, data privacy concerns, unequal device access, and cultural or linguistic adaptability. Findings indicate that AI–IoT integration can optimize adaptive content delivery, support context-aware experiential learning, and enable evidence-based instructional design when guided by ethical and equity-focused principles.