Research on Learning Efficiency Improvement Strategies of Public English Perspective Based on Ant Colony Algorithm

Abstract

A ground-breaking smartphone app called EngageLearnPro was created to improve learning efficiency improvement strategies in the context of public English education. With the use of cutting-edge technologies like Ant Colony Optimization (ACO) and Long Short-Term Memory (LSTM), this app creates a dynamic and captivating method of language learning. Intelligent sequence modeling is made possible by the combination of LSTM and allows for customized learning paths that adjust based on the progress of each individual user. On the other hand, ACO maximizes the app’s decision-making processes, improving the overall effectiveness of language learning techniques. The decision to use a mobile app environment for this initiative was made in light of the fact that smartphones are widely used and can provide education to a wider range of people. By utilizing the interactive and user-centric qualities of mobile devices, EngageLearnPro makes sure that learning happens naturally in users’ everyday lives. By combining LSTM and ACO technologies, a customized and adaptive learning experience is provided, accommodating a wide range of learning styles. EngageLearnPro offers an inclusive, cutting-edge, and effective platform with the goal of closing the gap in public English education. We hope to transform language learning by combining the best features of LSTM and ACO into a mobile application that is not only efficient but also fun and available to students of all backgrounds and ability levels.