Artificial Intelligence (AI) has increasingly become a transformative force in the education sector, offering unprecedented opportunities to enhance learning experiences and outcomes. This study examines the potential adverse effects of AI-assisted learning on critical cognitive skills, particularly critical thinking and problem-solving, within the context of Albania's educational landscape. Employing a quantitative methodology, a survey of 53 students was conducted across various educational institutions in Albania to gather data on their experiences and perceptions regarding AI-assisted learning. The findings indicate no significant difference in critical thinking skills between students with prior exposure to AI tools and those without. However, there is a statistically significant negative correlation between reliance on AI tools for assignments and students' problem-solving skills, suggesting that excessive dependence on AI can hinder the development of independent problem-solving abilities. Conversely, a strong positive correlation was found between the frequency of AI tool usage and students' perceptions of academic performance and assignment efficiency, highlighting the potential benefits of AI in enhancing these aspects of the educational experience. These results emphasize the need for a balanced integration of AI tools in education to ensure they complement rather than replace traditional learning methods. The study's findings have significant implications for educators and policymakers, suggesting that while AI can enhance certain educational outcomes, it is essential to address its potential risks to promote the development of essential cognitive skills. Future research should focus on larger, more diverse samples, incorporate objective measures of cognitive skills, and explore the long-term impacts of AI-assisted learning.

This chapter explores the evolving landscape of smart classrooms, focusing on the integration of sustainable internet of things (IoT) technologies. This chapter systematically reviews current trends, highlighting how IoT innovations are reshaping educational environments to enhance learning experiences and improve resource efficiency. The chapter examines the impact of smart technologies on classroom design, teaching methodologies, and sustainability practices, offering insights into the benefits and challenges of adopting IoT in education. This chapter underscores the potential of sustainable IoT solutions to create more adaptive, efficient, and environmentally conscious educational spaces, setting the stage for the future of education.

Electricity or power has become an essential service which is instrumental to many social, economic and technological developments worldwide. However, power utilities competing in emerging markets are confronted with challenges of shortfall in revenue due to collection losses known as Non-Technical losses (NTLs). Assessing and plummeting NTL to increase revenue, and reliability of the distribution of power remains a top priority for the utilities and regulators. The amount of data generated by power utilities offers exceptional opportunities owing to Machine Learning (ML) techniques to better understand the payment and consumption patterns of consumers. Consumers on the same profile can be segmented into clusters of similar behaviour through Customer segmentation. This paper applies k-means and DBSCAN clustering algorithms to segment customers by a measure of their bill payments, consumption and tariff plans then grouped into clusters. The clusters encountered, shows different categories of consumers in relation to their obligation profiles and tariff plans. K-means gives a better visualization in terms of cluster assignment. Dense clusters and outliers were viewed in DBSCAN.

This chapter explores the transformative role of artificial intelligence (AI) in education, focusing on secondary and higher education contexts. This chapter provides a comprehensive overview of how AI technologies are reshaping educational practices through personalized learning, adaptive curriculum design, and enhanced student engagement. By examining current trends, such as AI-driven assessment tools, learning analytics, and adaptive learning systems, the chapter highlights both the opportunities and challenges AI presents for educators and institutions. Key ethical considerations, including algorithmic bias, data privacy, and equitable access, are addressed, emphasizing the need for responsible AI deployment in educational settings. The chapter also examines the evolving role of educators in AI-enhanced classrooms, where traditional teaching roles are augmented by AI's ability to support personalized learning experiences.

This chapter lays the foundation for exploring the transformative potential of adaptive technologies in inclusive education. This chapter examines the principles of adaptive education, emphasizing its role in addressing the diverse needs of learners, particularly students with disabilities. The discussion highlights the integration of assistive technologies and artificial intelligence as critical tools for fostering equity, accessibility, and engagement in educational environments. By addressing key barriers such as cost, accessibility, and teacher preparedness, the chapter advocates for the adoption of innovative and inclusive practices to empower all learners. Grounded in interdisciplinary research and ethical considerations, this chapter sets the stage for understanding how adaptive technologies can reshape education systems to create a more inclusive and equitable future for students worldwide.