A Study on the Influencing Factors of Online Learning Procrastination of English Learners Based on Artificial Intelligence

Abstract

In order to deeply analyze the causes of English learners’ procrastination in e-learning and its influence on learning effect, an artificial intelligence (AI)-based method is designed to analyze the influencing factors of procrastination. By using K-means algorithm, this method divides learners’ online learning procrastination into two categories: active procrastination and passive procrastination, and collects corresponding learning state data samples. Then, taking into account various factors, including students, teachers, and the environment, we identified 11 key factors that may contribute to learning procrastination. Then, using the artificial intelligence-based procrastination factor ranking analysis model and the cuckoo search algorithm-trained XGBoost model, we trained multiple decision tree models to learn and predict the association between these influencing factors and different procrastination types of learning states. The experimental results show that after the application of this method, through in-depth analysis of the phenomenon of procrastination in students’ online English learning, different types of procrastination and their influencing factors are successfully identified, and an effective intervention model is designed based on the analysis results, which significantly improves students’ learning efficiency and provides strong support for the intervention of procrastination. It is proved that this method has certain significance for the accurate analysis of learning delay factors and effective intervention of procrastination in English e-learning.