College Students' Learning Behavior from the Perspective of Deep Learning
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Chen Jiao and Tianxingzi Gao
Abstract: The purpose of deep learning is to cultivate high-level thinking ability and realize meaningful learning. Its core idea embodies the concepts in cognitive science such as criticism, understanding, integration, transfer, reflection and creation. Based on the perspective of deep learning, this paper analyzes and studies the learning behavior of college students. In the study, we selected 400 students of statistics major in 2018 and 2019 as the research object, and used K-means clustering algorithm in data mining to analyze the number of times students in and out of the library and the types of books borrowed, so as to analyze their learning behavior. This study found that 76.4% of the students in and out of the library were of medium or above in 2018, while 70% of the students in and out of the library in and out of the class of 2019 were medium or above, and the proportion of students borrowing professional books in 2018 was far greater than that in 2019. In addition, with the help of data mining and K-means clustering algorithm, this paper analyzes the academic performance of the two sessions of students from the perspective of deep students, from which we know that the more times we enter and exit the library, the higher the degree of learning effort, the better the academic performance.
Keywords: Deep Learning Horizon, Data Mining, K-Means Clustering Algorithm, Learning Behavior Analysis