Research on Sentiment Analysis and Theme Mining of MOOC Course Reviews Based on SnowNLP-LDA

In recent years, with the rise of large-scale models, artificial intelligence technology has reached new heights, attracting widespread attention across various industries. Scholars hold differing views on the development of technologies in artificial intelligence. Under the theoretical framework of educational leadership, based on the broad audience and diverse course offerings of MOOCs (Massive Open Online Courses), the largest online education platform in China, this paper explores the emotional attitudes of online learners towards AI education courses and conducts topic mining of MOOC courses, aiming to provide guidance for the improvement of AI education courses on MOOC platforms. This paper collects and processes unstructured course review data, constructs a SnowNLP-LDA to perform sentiment analysis and topic mining on the review text. The study finds that the majority of online learners exhibit a positive attitude towards AI education, showing active interest in topics such as course content design, development trends, life impact, learning methods, classroom teaching, and technical learning. However, a minority of learners express concerns and negative evaluations regarding aspects such as course content quality, significance of development in the era, external factors influencing course learning, and the organization paradigm of teaching resources. Thus, AI education courses on MOOC platforms can focus on improving teaching methods, instructional effectiveness, course quality, and learning modes to address these concerns and criticisms.