Harvest Horizon: A 2D Farming Simulator Reflecting Realistic Agricultural Practices in the Philippines Using the Implementation of Cellular Automata Algorithm
Year: 2025
Type: article
Abstract: : This study addresses the issue of students understanding the complexities of farming by developing “Harvest Horizon”, a 2D farming simulation game designed to serve as both an educational tool and an engaging interactive experience. The game employs the Cellular Automata algorithm to model realistic plant growth behavior in response to environmental conditions. The research follows an iterative Game Development Life Cycle (GDLC) methodology and is developed using the Godot Engine with GDScript for algorithm implementation, Adobe Photoshop and Aseprite for asset refinement, and Figma for user interface prototyping. The game is assessed based on the ISO 25010 software quality model. The evaluation involved two respondent groups: gamers with at least six months of gaming experience across various platforms, and technical experts with academic and professional backgrounds in computer science, information technology, or game development. Findings indicate that Harvest Horizon effectively engages players in cognitive processes such as sustained attention, cognitive flexibility, working memory, and pattern recognition through its interactive farming mechanics. The game received an overall weighted average mean interpreted as “Strongly Agree.” These results affirm the game’s capacity to deliver an immersive educational experience while adhering to essential software quality benchmarks. This study highlights the potential of game-based learning as an innovative approach to agricultural education. The successful integration of cognitive engagement and technical excellence underscores the viability of Harvest Horizon as a supplementary educational tool for those seeking to revitalize interest in farming among younger generations.
Language: English
Subfield: Developmental and Educational Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4410092686