This study introduces a web-based application for savings and loan cooperatives, integrating a payment gateway to streamline financial transactions and improve operational efficiency. Developed using the waterfall methodology, the application enables members to deposit savings, apply for loans, and make installment payments online. Key features include automated financial reporting, secure transaction processing, and accessibility for cooperative managers and members. Black-box testing validated that the system met all functional requirements, ensuring reliable and secure operations. The application reduces operational workload, improves service quality, and supports real-time financial transparency by automating administrative tasks and offering multiple payment options—such as bank transfers and e-wallets. This solution demonstrates significant potential for transforming cooperative financial management by providing a scalable, user-friendly, and secure platform that enhances member services and promotes operational sustainability.

Artificial intelligence (AI) technology is already challenging a variety of societal areas, including education. It istransforming education to data driven. AI-enhanced technologies in education (abbreviated AIinED) will have asignificant role in

The integration of generative artificial intelligence (AI) tools, particularly large language models (LLMs), into higher education presents both opportunities for pedagogical innovation and challenges to academic integrity. While recent initiatives, such as the European Union's AI Act and UNESCO's Recommendation on the Ethics of Artificial Intelligence, have provided frameworks for ethical AI adoption, their practical implementation at the institutional level remains uneven. This study investigates how university faculty perceive the ethical implications of AI use in academic environments. Conducted as part of the EmpowerAI Erasmus+ project, a structured focus group involving 21 lecturers from the Technical University of Sofia in Bulgaria explored faculty staff attitudes toward AI's role in areas such as critical thinking, authorship, fairness, access, and privacy. Through thematic analysis, the study identifies emerging tensions between innovation and responsibility, and between equitable access and academic rigor. The findings underscore the need for context-sensitive institutional policies and educator training on AI ethics. The paper aims to contribute empirical evidence to the growing body of literature on responsible AI integration in higher education and informs the co-creation of actionable ethical guidelines that reflect both regulatory expectations and academic values.