Universidad de Manila, also referred to by its acronym UdM, is a public coeducational city government funded higher education institution in Manila, Philippines. It was founded in April 26, 1995 with the approval by Mayor Alfredo Lim of Manila City Ordinance (MCO) No. 7885 “An Ordinance Authorizing the City Government of Manila to Establish and Operate the Dalubhasaan ng Maynila (City College of Manila). It offers both academic and technical-vocational courses and programs. Its Main Campus is located at the grounds of Mehan Gardens, Ermita in front of the Bonifacio Shrine (Kartilya ng Katipunan) and beside the Central Terminal station of LRT Line 1. It has a satellite Campus (UDM Annex) along Carlos Palanca Street in Santa Cruz..
This study presented the development of a Smart Collaborative Learning Platform that integrated Natural Language Processing (NLP), deep learning models, and recommendation algorithms to automate content generation and enhance learning experiences. The system was designed to process uploaded learning materials and transform them into structured outputs such as summaries, quizzes, and flashcards. It utilized NLP techniques to analyze and understand semantic content, enabling accurate interpretation of user inputs and educational materials. Deep learning models were employed to generate meaningful summaries and insights that supported efficient studying. Additionally, a recommendation engine personalized learning by suggesting relevant topics based on user behavior and performance. The platform also incorporated collaborative features that allowed users to interact, share knowledge, and engage in real-time learning activities. The system was evaluated using ISO 25010 software quality standards, focusing on functionality, usability, reliability, and performance. Results indicated that the platform achieved high user satisfaction and demonstrated strong system performance. Findings showed that the system improved learning efficiency, reduced study time, and enhanced knowledge retention. Furthermore, the integration of AI technologies enabled adaptive and personalized learning experiences. The study highlighted the effectiveness of combining automation and collaboration in modern education. Overall, the proposed platform provided an innovative and scalable solution for improving digital learning environments.
This chapter examines sport as a strategic instrument for human and social development, moving beyond its traditional focus on competition and athletic performance. While sport is often associated with physical excellence and entertainment, it also functions as a powerful platform for citizenship formation, social inclusion, life skills development, and community empowerment. Positioned within broader social policy and development frameworks, sport can contribute to nation-building by shaping responsible, engaged, and socially aware citizens. The chapter argues that sport serves as a developmental space where individuals acquire values such as discipline, teamwork, leadership, resilience, and civic responsibility. Through structured programs in schools, communities, and grassroots organizations, sport fosters not only physical competence but also social capital and participatory citizenship. It becomes a medium through which young people, particularly those from marginalized backgrounds, gain access to mentorship, social networks, and opportunities for upward mobility.
Postgraduate learning is critical for career development, research innovation, and national development. Access to these opportunities, though, continues to be uneven, particularly among underrepresented and marginalized groups. In spite of international attempts to enhance inclusion, equity gaps in postgraduate enrollment and graduation continue to persist. The current study investigates access determinants to postgraduate education and offers recommendations to improve equity in line with Sustainable Development Goal 4 (Quality Education). A mixed-methods design was used, coupling survey answers of 100 postgraduate students with qualitative interviews of 20 academic administrators from purposively chosen higher education institutions in the Philippines. Evidence indicated that financial requirements, geographical location, not knowing about opportunities, and institutional gatekeeping realistically limit access considerably. Although universities offer scholarships and flexible modes of learning, they are limited in scope and unevenly available. Administrators also mentioned difficulty in balancing institutional resources and diverse student needs, including working professionals and rural students. The research emphasizes inclusive policies, focused financial assistance, infrastructure for distance learning, and community organization partnerships to increase access. Such equity can only be achieved through concerted effort by government, academia, and industry to foster sustainable and inclusive lifelong learning. This study adds to the conversation of educational justice and presents actionable recommendations for expanding participation in higher studies.
This article examines the implications of DepEd Order No. 2, series of 2024, which directs the immediate removal of administrative tasks from public school teachers in the Philippines. Drawing on a convergent parallel mixed-methods study conducted in the Schools Division of Pasay City, the paper synthesizes evidence from 224 respondents, including 207 elementary teachers and 17 elementary school heads, and qualitative responses from 10 purposively selected participants. The study investigated whether relieving teachers of non-teaching administrative work enhances teacher empowerment, improves instructional quality and welfare, strengthens school readiness, and contributes to educational quality. Quantitative findings reveal consistently strong perceptions of positive effects. Teacher empowerment registered very high contribution across control (overall mean = 4.55), autonomy (4.54), and efficacy (4.60). Teachers also reported very high implication in terms of quality of classroom instruction (4.61), professional satisfaction (4.59), and workload reduction (4.65). In contrast, school heads rated school readiness dimensions only as moderately implemented: human resource needs (4.09), competency development (4.07), facilities/resources (4.08), and scheduling (4.06). Qualitative findings reinforce these results, highlighting themes of instructional focus, efficiency, uninterrupted teaching, preparation, responsiveness, support, transition management, and collaboration. The article argues that policy success depends not only on removing tasks from teachers but also on reallocating them through adequate staffing, training, communication systems, and phased implementation. A transition framework is proposed to guide schools and divisions in operationalizing the policy. The findings suggest that administrative task reduction has strong promise for improving teacher well-being and instructional effectiveness, but the reform requires sustained organizational support to produce durable gains in educational quality
Artificial Intelligence (AI) and Machine Learning (ML) have been increasingly affecting the fashion industry with real-time capabilities for personalized clothing. Despite fashion ultimately being just self-expression, identity & culture, many considerations, like differences in body shapes, tastes, requirements for the occasion, and continuously evolving trends, complicate the decision-making on what to wear. While personalization systems are more beneficial than one-size-fits-all, many systems still limit their capability for personalization through apps that do not focus on user preference and that are less accurate. This study shows the rapid evolution of a cross-platform mobile application for fashion recommendations, that fused content-based and Collaborative filtering with machine learning techniques to deliver personalized fashion recommendations. The app simplifies the choices about outfitting, reduces the time browsing for clothing, builds user confidence, and provides several options suitable to various user preferences. Firebase and Supabase offer database management and authentication security, while Machine Learning is leveraged to analyze the strong relationships between user and product data in order to provide a recommendation based on user preferences. The development utilized Agile methodologies, incorporating iterative tasks and adjustments guided by user feedback to improve functionality, usability, and precision. Result demonstrates that the application reduces time and browsing in finding outfits and increase user confidence through reliable, and timely suggestions suited to the situation. Moreover, the system showcased inclusivity by putting various styles and real-time trends, thus enabling merchants to connect with a wider audience. In summary, the findings shows that an AI-mobile based fashion recommendation system provides a more user-friendly, personalized, and various clothing selection method. The suggested solution promotes digital fashion technologies by focusing on individuality, diversity, and usability, thereby improving the role of AI in daily self-expression.
