Analyses of Online Learning Behaviour Based on Linear Regression Algorithm

With the rapid development of online education, analysing students' online learning behaviour is crucial for improving learning outcomes and optimizing teaching strategies. This paper constructs an online learning behaviour analysis model based on the linear regression algorithm, exploring the impact of different learning behaviour characteristics on learning outcomes. Through data preprocessing, feature extraction, and model training on data collected from the learning platform, key influencing factors such as study time and interaction frequency were identified. The results show that effective management of learning behaviours and the design of personalized learning paths can significantly enhance learning outcomes. Finally, based on the analysis results, this paper proposes specific suggestions for optimizing online learning platforms, providing theoretical support for personalized teaching.