Research on Group User Portrait of Online Education Platform Based on Big Data

With the rapid development of big data,online education can use big data technology to achieve personalized and intelligent education as well as improve learning effect and user satisfaction.In this study,the users of The Open University of China online education platform were taken as the research object,their user behavior data was collected,cleaned,and analyzed with text mining.The RFM model and the improved K-Means algorithm were used to construct the user portrait of the platform group and the needs and preferences of different types of the users were analyzded.Chinese word segmentation was used to show the key words of different types of users and the word cloud of their using frequency.The focus of different user groups was determined to facilitate for the follow-up course recommendation and precision marketing.Experimental results showed that the improved K-Means algorithm can well depict the behavior of group users.The index of silhouette score was improved to 0.811 by the improved K-Means algorithm,from random uncertainty to a fixed value,which can effectively solve the problem of inconsistent results caused by outlier sample points.

The Impact of Personalized Learning Path Design on Online Education Platforms on Students’Self-Learning Abilities

The study investigates the impact of personalized learning path design on students’self-learning abilities(SLA)within online education platforms.Employing a mixed-methods approach,the research examines the effectiveness of personalized learning through quantitative surveys and qualitative interviews with a diverse sample of online learners.The findings indicate that personalized learning path design significantly enhances students’self-efficacy,engagement,and satisfaction,leading to improved SLA.The study’s conceptual model and empirical data support the hypothesis that personalization in learning environments fosters self-directed learning skills.The discussion highlights the implications for educational practice,emphasizing the need for online platforms to prioritize personalization and for educators to adapt their teaching methods to support diverse learner needs.The research also acknowledges limitations and suggests future directions,including longitudinal studies and expanded participant demographics.The study concludes that personalized learning path design is a promising strategy for online education platforms to empower learners and promote lifelong learning skills.