FEU Institute of Technology

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Conference Paper 401 Publications

Discover all conference paper published by our researchers
Development of a Smart Financial Tool for Computing High-Yield Savings in Digital Banks to Advance Financial Literacy Through a Blended Agile Methodology

TENCON 2025 - 2025 IEEE Region 10 Conference (TENCON), (2026), pp. 528-532

Conference Paper | Published: February 18, 2026

Abstract
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.
Ethical Design Framework for Enhancing Accessibility in Graphic Platforms for Colorblind Users

TENCON 2025 - 2025 IEEE Region 10 Conference (TENCON), (2026), pp. 1476-1480

Conference Paper | Published: February 18, 2026

Abstract
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.
Integrating Generative AI into Creative Workflows: A TAM-based Investigation of AI Adoption in Video Production and Editing

TENCON 2025 - 2025 IEEE Region 10 Conference (TENCON), (2026), pp. 199-203

Conference Paper | Published: February 18, 2026

Abstract
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.
A TAM-Guided Mobile Solution to Support Mental Wellness in Higher Education

TENCON 2025 - 2025 IEEE Region 10 Conference (TENCON), (2026), pp. 1230-1234

Conference Paper | Published: February 18, 2026

Abstract
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.
Leveraging Microsoft Copilot to Generate Instructional Content for Social Engineering Awareness in Digital Learning Environments

2025 International Workshop on Artificial Intelligence and Education (WAIE), (2026), pp. 321-326

Conference Paper | Published: February 17, 2026

Abstract
As social engineering threats continue to evolve, equipping learners with the skills to recognize and respond to digital manipulation has become a critical component of digital citizenship education. This paper explores the use of Microsoft Copilot—an AI-powered assistant—as a tool for generating instructional content that enhances awareness of social engineering tactics within digital learning environments. By integrating Copilot into the instructional design process, educators can rapidly produce scenario-based learning modules, phishing simulations, ethical discussion prompts, and adaptive assessments tailored to diverse learner profiles. The study presents a framework for human-AI collaboration in content creation, emphasizing pedagogical alignment, personalization, and scalability. Through case examples and prototype lesson plans, the paper demonstrates how Copilot can support educators in developing engaging, context-aware materials that foster critical thinking and digital resilience. This approach not only streamlines curriculum development but also positions generative AI as a strategic partner in advancing cybersecurity education across formal and informal learning contexts).
CyberSAFE: A Gamified Web Platform with Analytics to Promote Cybersecurity Literacy Among IT Students

2025 International Workshop on Artificial Intelligence and Education (WAIE), (2026), pp. 287-292

Conference Paper | Published: February 17, 2026

Abstract
In the digital age, cybersecurity awareness is increasingly vital, especially for information technology (IT) students who will eventually design and manage secure systems. This paper presents CyberSAFE, a gamified web-based platform developed to enhance cybersecurity literacy through interactive modules, quizzes, and analytics dashboards. By integrating gamification with digital pedagogy principles, the platform promotes engagement, tracks learning progress, and identifies knowledge gaps in real time. A developmental-evaluative research methodology was employed, using pre- and post-tests, survey data, and system-generated analytics. Results indicate that students demonstrated measurable gains in cybersecurity knowledge, supported by positive perceptions of the platform’s usability, content relevance, and motivational impact. On a 5-point Likert scale, mean survey ratings exceeded 4.5, reflecting high acceptance and perceived effectiveness. These findings suggest that CyberSAFE can improve cybersecurity literacy while contributing to the Sustainable Development Goals (SDG 4: Quality Education and SDG 9: Industry, Innovation, and Infrastructure).
AI-Driven Gamification for Cybersecurity Literacy in Higher Education

2025 International Workshop on Artificial Intelligence and Education (WAIE), (2026), pp. 95-100

Conference Paper | Published: February 17, 2026

Abstract
Cybersecurity literacy is increasingly vital in higher education, yet traditional teaching methods often fail to sustain student engagement. This paper introduces Aegis Academy, an AI-driven gamified learning platform that uniquely integrates adaptive feedback mechanisms with game-based elements to enhance cybersecurity awareness and skills. Unlike existing systems, Aegis Academy combines real-time personalization, rolebased analytics, and modular gamification tailored for academic settings. A pilot study involving 100 students and 20 instructors demonstrated significant improvements in phishing awareness (+22 %), overall scores (+18 %), and module completion rates (87% vs. 64%). Students rated the platform highly for engagement and learning impact, while instructors reported strong pedagogical alignment and usability. The platform supports Sustainable Development Goal 4 (SDG 4) by promoting inclusive, equitable, and engaging digital education. These findings suggest that Aegis Academy offers a scalable and effective model for cybersecurity instruction in higher education.
Allie’s Misadventures: Policies Sound Ridiculously Close to Fallacies (A 3D single-player action-adventure game that teaches defenses against false arguments and disinformation)

2025 International Workshop on Artificial Intelligence and Education (WAIE), (2026), pp. 80-85

Nicole Kyle De Leon, Alec Dreyson Dela Cruz, ... Nika Ella Enriquez

Conference Paper | Published: February 17, 2026

Abstract
Allie’s Misadventures: Policies Sound Ridiculously Close to Fallacies” is a 3D single-player actionadventure game designed to combat misinformation by teaching players how to detect logical fallacies. Players assume the role of Allie, a bioroid journalist investigating media broadcasts and statements in a world dominated by disinformation. By infiltrating media towers under the King’s control, players learn to cross-examine and challenge deceptive arguments. The game aims to enhance critical thinking skills and reduce susceptibility to false information.
Harnessing Large Language Models for Personalized Education: Opportunities, Challenges, and Implications for SDG 4

2025 International Workshop on Artificial Intelligence and Education (WAIE), (2026), pp. 472-476

Conference Paper | Published: February 17, 2026

Abstract
The rapid advancement of large language models (LLMs) such as ChatGPT, Claude, and Gemini presents new opportunities for personalized education. These AI systems are capable of tailoring learning experiences, providing instant feedback, and supporting self-paced study. However, questions remain regarding their pedagogical effectiveness, ethical implications, and alignment with educational goals. This study explores the opportunities and challenges of integrating LLMs into personalized learning environments in higher education. Using a mixed-method approach that combines experimental use of LLM-based tutoring with surveys and interviews of students and educators, the research evaluates their impact on engagement, learning outcomes, and inclusivity. Findings are expected to contribute to the discourse on AI in education while supporting the United Nations’ Sustainable Development Goal 4 (Quality Education), particularly in promoting inclusive and equitable access to learning opportunities through emerging technologies.
Enhancing the Neighborhood Median Pixel Method Accuracy with Weighted Landsat-8 OLI Image and Spectral Indices

Proceedings of the 2025 6th Asia Service Sciences and Software Engineering Conference, (2026), pp. 15-20

Abraham T. Magpantay Abraham T. Magpantay & Proceso L. Fernandez

Conference Paper | Published: January 21, 2026

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Abstract
The Neighborhood Median Pixel Method (NMPM) classifies land cover by summing per-band scores across 10 input features from Landsat-8 Operational Land Imager (OLI) data – bands 1 through 7 alongside three widely used index images: NDVI, NDWI, and NDBI. These features are typically treated equally within the classification framework, assuming uniform informational value across all bands and indices. However, indices such as NDVI, NDWI, and NDBI are specifically designed to highlight spatial properties of their respective land cover classes—particularly in urban settings—and are therefore expected to carry more relevant information for specific classification tasks. In this study, we experimented with different weighting schemes and found that giving greater emphasis to the indices led to a modest increase in overall classification accuracy, achieving an average overall accuracy of 0.9475 compared to 0.94 of the original implementations for the equal-weight baseline and other weighting strategies with a 9x9 neighborhood size. The results demonstrate how a targeted methodological innovation in image processing—assigning greater weight to highly relevant features—can enhance the reliable and efficient classification performance of the NMPM. This contributes to more accurate land cover mapping, particularly in complex urban environments, and supports data-driven development planning and resource management.

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