Abstract
Mining a large number of students' behavior data can analyze the differences of students' behavior characteristics. Mining based on students' behavior data can explore the influence mechanism of students' learning enthusiasm, and can provide reference opinions and suggestions for improving students' positive emotions in learning and helping students with poor grades to achieve academic success. The data collected and conclusions obtained by the existing research are not accurate and reliable, and other personality characteristics of students are not fully considered. Therefore, this article studies the influence mechanism of students' learning enthusiasm based on educational big data. It studies the performance of students with good learning enthusiasm in social relations, and mines students’ social intercourse at school based on association rules. It analyzes the regularity of students' behavior and their diligence, and realizes the characterization of students' sustainability and enthusiasm in learning. Combining the differences of behavior characteristics between students with and without learning enthusiasm, this article constructs a learning enthusiasm recognition model and compares it by classification. Experimental results verify the effectiveness of the model.
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More From: International Journal of Emerging Technologies in Learning (iJET)
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