UPLB ICS Peak One

Challenges in academic record management and communication at Goa Science High School, including lim- ited student grade access and informal teacher interactions, prompted this study. This paper presents AcadBridge, a web- based system designed to address these issues. AcadBridge offers a secure centralized database, performance visualization tools, and a structured messaging system. Developed with user- centered design, the system underwent rigorous security and usability evaluations—assessing effectiveness, efficiency, and sat- isfaction—with students, teachers, and administrators, aligning with established ISO 9241-11 usability standards. Evaluation results demonstrated high effectiveness, with users successfully completing all assigned tasks. High efficiency was also observed, with most tasks completed in consistent times and without any errors. User satisfaction was outstanding, as measured by the System Usability Scale (yielding an average score of 87.42), and core features like data visualization and messaging also received very high satisfaction ratings (average 4.40 out of 5). AcadBridge provides a comprehensive solution, significantly improving transparency, streamlining academic administration, and fostering better communication for the school community.

Artificial intelligence research in games have seen an upward spike of interest in recent years. Game AI research has been looking to utilize new modern AI technologies such as machine learning to implement in their games. However, there are many difficulties with this for most developers as it requires a substantial amount of time, effort, and money to train good models for their games. Utility systems or Utility AI for games are a very popular design architecture for game developers. It allows a flexible and adaptive way of modeling behaviors for non-playable characters. However, this system is limited by being rigid in its utility functions and actions taken among others. This research explores a modified version of the utility system by adding adaptability to the utility functions to change behaviors over time during runtime as players progress through a game. A co-operative farming game was developed, called Growing Together, which was made with Unity and used an AI agent using the adaptive utility system to play with the player. The effectiveness of the adaptive utility system was tested by twelve participants. The adaptive utility system has shown that it is capable of adapting to player actions and changing its own behaviors to co-operate with the player effectively. The game was also found to be quite enjoyable by the participants although the AI agent trained by the system was said to be capable of improving but can also easily learn mistakes and unwanted behavior. The game’s limited gameplay features limited the potential of the adaptive utility system. Future research is recommended to use a similar system in more complex games to further explore the system’s capabilities and player experience with the system.

With an estimated 28 million PC gamers in the Philippines, gaming presents a promising opportunity to engage learners in the study of the traditional Filipino writing system, Baybayin. This study explores the potential of game- based learning as a tool for teaching Baybayin through the development of Baybay, an educational typing game created using the Godot Game Engine and GDScript. As a typing game—a genre that involves players to correctly enter letters or words using a keyboard—Baybay aims to reinforce learning through interactive and engaging gameplay. To assess its effec- tiveness, a Pre-Test and Post-Test methodology was employed, alongside the System Usability Scale (SUS) to evaluate the game’s usability. The results revealed a statistically significant improvement in post-test scores compared to pre-test scores, indicating that Baybay is effective as an educational tool for teaching Baybayin. Additionally, the SUS results showed above- average usability, suggesting that the system is well-designed and user-friendly.

The unique and delicate growth pattern of sugar- cane crop necessitates accurate monitoring and growth stage classification, particularly on harvest-ready sugarcane crops, for effective crop management, resource management, and yield maximization. This study introduces the HR-SAGE application (Harvest-Ready Sugarcane Assessment via GIS and Earth Obser- vation), a web-based application designed to detect, visualize, and classify sugarcane crops into their four growth stages across the Philippines at 10m spatial resolution using the GEDI-Sentinel- 2 global sugarcane map by Di Tommaso et al. and NDVI data from the Sentinel-2 dataset. The application utilizes Geospatial computation in identifying verified sugarcane pixels, vectorizing them into centroids, classifying them into growth stage depending on NDVI characteristics and cumulative tall canopy months (nTallMonths), and visualizing them in an interactive GIS map is done by the application using Google Earth Engine (GEE). The sugarcane pixel detection, the vectorization process, as well as the growth stage classification using NDVI and nTallmonths were validated and approved by agricultural engineering expert Dr. Moises Dorado of the College of Engineering and Agro-Industrial Technology, UPLB, with all of the methods being scientifically grounded. Results showing a great level of user satisfaction with the UI’s simplicity and details were assessed using the System Us- ability Scale (SUS) and an in-depth qualitative and comparative survey. Expert review further attested to the scientific validity of the pixel-level detection, classification logic. The study proposes potential improvements in the future, such as processing cloud- covered images, using predictive models, and verifying the local fields with agriculture experts. HR-SAGE provides a scalable, user-friendly, and scientifically grounded solution to sugarcane growth monitoring in the Philippine sugarcane industry.

PigPal is a mobile application designed to enhance record-keeping in smallhold swine farms. The system supports offline functionality and includes modules for managing pig and herd profiles, health and weight records, inventory, transactions, and farm events. It also allows role-based access for owners and workers. Usability was evaluated through two rounds of System Usability Scale (SUS) testing. In the first round, the app received an average SUS score of 82.5 from Owners (n=14) and 85.83 from Workers (n=6), with an overall average of 83.5—classified as “Excellent.” Feedback led to several improvements, including a ’Forgot Password’ feature, language selection, and expanded worker capabilities. In the second round, SUS scores rose to 94.29 (Owners) and 89.17 (Workers), averaging 92.63. These results indicate an increase in user satisfaction and demonstrate the system’s effectiveness in improving digital record-keeping in small-scale pig farming.