Open Access

Anish Bhattarai

• In recent years, digital tools in soil science have evolved to modernize and streamline traditional approaches by fostering greater learning engagement and enhancing accessibility. The primary goal of this research is to create an application that intends to facilitate autonomous learning while streamlining data processing, visualization, and reporting for the Bait Lamina Method (BLM). Advanced technologies such as React.js, Tailwind CSS, Vite.js, and several Node.js modules were used to implement essential functionalities. Moreover, to ensure smooth and scalable app delivery, Docker was employed. Furthermore, thorough usability testing was carried out with students from both the school and university to create a sturdy app that satisfies the needs and standards of users. This research utilized a mixed-methods approach to evaluate the app's overall usability, emphasizing efficiency, learnability, dependability, and overall satisfaction. Quantitative analysis included phi coefficient correlation, chi-square testing, and multiple ordinary least squares (OLS) regression to measure overall usability and user satisfaction. Meanwhile, qualitative approaches such as theme and sentiment analysis were used to get insight into user experiences, preferences, difficulties, and ideas for improvement. The study demonstrated that understanding the method is a key driver influencing student satisfaction. Therefore, the Bait Lamina App (BLA) immensely facilitated autonomous learning while speeding up data processing, visualization, and administration for the BLM. However, a few small faults and student comments were integrated into the BLA, which improved its use and satisfaction.