Construction of an Agricultural Training Effectiveness Assessment Model Based on Big Data

Abstract

This research presents an Agricultural Training Effectiveness Assessment Model (ATEAM) leveraging enormous information analytics methods to assess the adequacy of agrarian preparing programs. By coordinating different information sources counting member socioeconomics, and preparing substance, and relevant components, ATEAM gives an all-encompassing system for evaluating preparing adequacy. Through tests and comparative examinations, ATEAM illustrates prevalent prescient precision, clustering quality, and by and large adequacy assessment compared to conventional strategies and related works. Particularly, ATEAM accomplishes an exactness rate of 87.3%, an Outline Score of 0.72 for clustering, and a Mean Squared Error (MSE) of 0.012 for member fulfilment rating expectation. This model empowers partners to create data-driven choices for program optimization and asset assignment, contributing to feasible rural advancement and upgraded nourishment security. The study underscores the transformative potential of huge information analytics in rural preparation, highlighting the significance of leveraging progressed analytics strategies to address complex challenges and drive positive results.