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Education

Empowering diversity in science, technology, engineering, and mathematics through university-led engineering outreach programs for K–12 students

November 17, 2025 by Qusay H. Mahmoud, Hossam Kishawy, Laura Thursby, Kimberly Davis, Ellen James

Despite the recognized value of science, technology, engineering, and mathematics (STEM) education, significant barriers prevent equitable access to STEM learning opportunities, particularly for young individuals. These barriers range from limited access to quality STEM resources and insufficient support for educators to financial constraints associated with pursuing higher … [Read more...] about Empowering diversity in science, technology, engineering, and mathematics through university-led engineering outreach programs for K–12 students

From artificial intelligence to artificial mind: A paradigm shift

December 27, 2024 by Mohammad Ghiasi

Considering the development of artificial intelligence (AI) in various fields, especially the closeness of its function to the human brain in terms of perception and the understanding of sensory and emotional concepts, it can be concluded that this concept is cognitively evolving toward an artificial mind (AM). This article introduces the concept of AM as a more accurate … [Read more...] about From artificial intelligence to artificial mind: A paradigm shift

Unleashing the potential of ChatGPT in education

December 27, 2024 by Balaji Chandrasekaran, Smrithy Girijakumari Sreekantan Nair,

ChatGPT, an advanced language model powered by artificial intelligence, has emerged as a transformative tool in the field of education. This article explores the potential of ChatGPT in revolutionizing learning and collaboration within educational settings. By leveraging natural language processing and machine learning, ChatGPT offers an interactive and personalized learning … [Read more...] about Unleashing the potential of ChatGPT in education

Learning 101 reloaded: Revisiting the basics for the GenAI era

December 27, 2024 by Junaid Qadir

In this paper, we delve into the transformative landscape of education amidst the disruptive advances of generative AI (GenAI), characterized by an unprecedented capacity to generate new information with tools such as ChatGPT. Building upon my previous publication, “Learning 101: the Untaught Basics,” in this magazine, I interrogate what has changed since then and how learners … [Read more...] about Learning 101 reloaded: Revisiting the basics for the GenAI era

The potential of augmented reality in Indian rural primary education [STEM Education]

July 10, 2024 by Dipali Basumatary, Ranjan Maity

Technology-enhanced learning has the potential to increase educational quality. In this study, we examine the integration of augmented reality (AR) technology in rural primary schools in India. We listed articles associated with AR-based applications for Indian preschool and primary education from 2018 to 2023, and we observed that they are only 10% of contemporary AR-based … [Read more...] about The potential of augmented reality in Indian rural primary education [STEM Education]

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About the Magazine

IEEE Potentials Magazine is the publication dedicated to undergraduate and graduate students and young professionals. IEEE Potentials explores career strategies, the latest in research, and important technical developments. Through its articles, it also relates theories to practical applications, highlights technology’s global impact, and generates international forums that foster the sharing of diverse ideas about the profession.

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Privacy-preserving distributed learning: Techniques, applications, and future challenges

The rapid increase in data generated by connected devices has created a pressing need for privacy-preserving techniques in distributed learning. This article examines methods that enable collaborative machine learning (ML) while maintaining data security and user privacy. Key approaches such as federated learning (FL), differential privacy (DP), secure multiparty computation (SMPC), and homomorphic encryption (HE) are analyzed for their unique capabilities and various applications. FL facilitates model training across decentralized data sources, ensuring data remain local, while DP mitigates privacy risks by adding controlled noise. SMPC and HE support secure computations on encrypted data, maintaining confidentiality during processing. Despite their effectiveness, these techniques face challenges related to computational complexity, scalability, and regulatory compliance. The article reviews current advancements, practical implementations, and future directions, emphasizing the need for optimized, accessible solutions to enhance data security in distributed systems.

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