Mental health concerns are on the rise among college students in the Philippines, where academic stress and limited access to counseling services continue to pose serious challenges. With mobile technology becoming more integrated into daily life, it offers a practical opportunity to support student well-being through accessible, self-help tools. This study presents the design and evaluation of a mobile application that combines art therapy and sound therapy to help reduce stress and promote relaxation among students in higher education. Guided by the Technology Acceptance Model (TAM), the research explored how users perceived the app's usefulness, ease of use, and overall experience. The app was developed using a blended Agile approach and tested by 50 purposively selected college students experiencing academic stress. Results showed strong user acceptance, with high ratings in ease of use (x=4.56), satisfaction (x=4.36), and intention to use (x=3.96). Perceived usefulness was strongly correlated with both satisfaction (r=0.73) and continued use (r=0.78), indicating that the app effectively supported stress relief and user engagement. This study contributes practical insights for integrating mobile wellness solutions in Philippine education, particularly in settings where traditional mental health support remains limited. It encourages the adoption of simple, evidencebased digital tools that promote emotional well-being and help bridge gaps in student support systems.

An AI-driven academic path forecasting system is proposed to support data-informed advising and early academic intervention in higher education. In the Philippine context, where delayed graduation, student dropouts and lack of personalized academic guidance persist, machine learning in education offers a scalable and intelligent solution. The system combines three educational data mining techniques: a Long Short-Term Memory (LSTM) network for course sequence prediction, a decision tree classifier for student progress classification as regular or irregular and a K-Means clustering algorithm for grouping students based on academic trajectories. These models are developed in TensorFlow and deployed on a web platform built with CodeIgniter, enabling functionalities such as academic path forecasting, curriculum tracking and real-time risk alerts. Evaluation shows that the LSTM model achieves strong precision and recall in predicting next-term courses, while the decision tree classifier accurately detects off-track students with interpretable decision rules. K-Means clustering reveals meaningful groupings aligned with academic outcomes, further supporting early identification of at-risk learners. Confusion matrix analysis confirms high model accuracy across tasks. By integrating AI into higher education through course prediction, student classification and cluster-based insights, the system offers a practical framework for enhancing student success through targeted academic support.

This study developed the Digital Banks PH Notebook, a mobile application designed to support financial literacy among Filipinos by optimizing savings through high-yield digital banking platforms. The application featured a savings portfolio tracker, interest forecasting calculator, and savings goal management to address gaps in financial planning and savings behavior. Development followed a blended Agile methodology integrating Scrum, Extreme Programming, and Feature-Driven Development, ensuring iterative improvements aligned with user needs. Software quality was assessed using the ISO/IEC 25010 model, while qualitative feedback was analyzed through word cloud visualization to capture user sentiment and key focus areas. Findings indicated that the application effectively enhanced users' understanding of savings strategies and promoted responsible saving practices. The tool successfully connected the opportunities presented by digital banking with the practical requirements of financial education, providing users with actionable insights to manage their savings more strategically. By leveraging agile development practices and rigorous evaluation frameworks, the project demonstrated that technology-driven solutions can play a significant role in advancing financial literacy and supporting sustainable financial behaviors in an evolving digital economy.

This study investigates the integration of generative artificial intelligence (AI) into video production and editing workflows using the Technology Acceptance Model (TAM) as the theoretical framework. Given the creative industry's substantial economic contribution globally and in the Philippines, the research focuses on how video professionals perceive the usefulness and ease of use of AI tools such as Adobe Premiere Pro, After Effects and OpenAI's Sora. A purposive sample of 60 professionals, including editors, motion graphics artists and content creators, was surveyed to assess behavioral intention, user attitude and the influence of external factors on AI adoption. Findings indicate a generally positive attitude toward AI, with many respondents highlighting increased efficiency and automation of repetitive tasks. However, the study also identifies key barriers such as skill gaps, tool complexity and limited training opportunities, emphasizing the need for competency-based training and institutional support. Correlation and word cloud analysis reinforce the importance of enhancing education quality and multimedia learning to support effective adoption. The results confirm TAM's applicability in this context and suggest that with improved accessibility, policy alignment and targeted capacity building, generative AI can significantly enhance creative workflows while supporting the development of employability skills in the digital content sector.

Color is a foundational element in digital design, yet individuals with color vision deficiency (CVD) often encounter significant barriers when engaging with mainstream graphic design platforms. This study explores the ethical and practical implications of designing for users with CVD, focusing on the experiences of Filipino creatives in both professional and academic settings. It aims to uncover common usability challenges, evaluate the effectiveness of existing accessibility features, and propose improvements that reflect user needs and promote inclusive design practices. Employing a qualitative, exploratory methodology, the study integrates word cloud analysis and the Diffusion of Innovation theory to interpret user feedback and assess attitudes toward accessible tools such as colorblind-friendly palettes and vision simulators. Results show strong support for built-in, customizable accessibility features, with many users expressing openness to adoption if these tools are integrated seamlessly into their workflows. The study contributes to the discourse on digital inclusion by presenting an ethical design framework that promotes accessibility as a standard, not optional, element in graphic design platforms.