Machine Learning Based Big Data Analytics for Education in Curriculum Reforms

With the continuous development of social Internet technology, machine learning plays an important role in different industries, and the current education field is also experiencing the transformation from traditional teaching mode to data-driven intelligent teaching mode. In this paper, we provide an overview of the current status of the application of machine learning and educational big data analytics in education, discuss the commonly used machine learning algorithms and key technologies for educational data analytics, and at the same time, analyse the problems and challenges of curriculum reform, and elucidate the potentials of machine learning and educational big data in the process of solving these problems. In addition, this paper uses machine learning models to analyse students' learning behaviours, and also uses the models for personalised learning path recommendation, intelligent recommendation of teaching resources and other aspects. The application effect of the model in actual teaching activities is partially demonstrated through experimental research, and the effectiveness of the model is verified through data analysis. Finally, this paper summarises the research results and highlights the key role of machine learning-based big data analytics in education in promoting personalisation of education and improving teaching quality. The research in this paper not only provides educators with a new perspective on curriculum reform, but also provides educational decision makers with a reference for data-driven decision making, which is expected to promote the development of education in the direction of more intelligent and personalised education.