Abstract
With the rapid development of big data in my country and the large-scale promotion of English MOOC courses in recent years, students’ autonomous learning has become more and more important. Autonomous learning by students is not only conducive to improving students’ course performance, but also an important development factor for students’ lifelong learning and sustainable development. MOOC impacts the traditional English curriculum and teaching mode. Some students’ basic qualities are generally poor, their learning goals are not clear, the learning methods and objectives are not correct, and they lack active learning motivation and the ability to solve problems independently. It is an urgent task for us to improve students’ learning motivation. The purpose of this article is to study the motivation of students’ autonomous learning in English MOOC teaching based on big data analysis. Based on the relevant theories of educational psychology, this thesis describes the internal connection between the English MOOC teaching model under big data and the theory of learning motivation. This article makes a preliminary discussion on how to effectively combine English MOOC teaching under big data with learning motivation theory, so as to improve students’ autonomous learning motivation. This paper proposes a comparative analysis method to compare traditional teaching and MOOC teaching to analyze its influence on students’ learning motivation. This article puts forward the theory of interaction and autonomous learning. Finally, a variety of manifestations are adopted, and the comparison trend chart is intuitively displayed to users. Experimental research shows that the survey results show that the experimental class score is 25.5, while the traditional class is 19.30, both of which do not reach 90% of the total score, indicating that the students’ motivation for learning English is insufficient. Using the teaching model of English MOOC teaching based on big data analysis helps to improve the overall student’s learning motivation level. According to the experimental results, it has increased by 16.6%.
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