Information literacy is a basic ability for college students to adapt to social needs at present, and it is also a necessary quality for self-learning and lifelong learning. It is an effective way to reveal the information literacy teaching mechanism to use the rich and diverse information literacy learning behavior characteristics to carry out the learning effect prediction analysis. This paper analyzes the characteristics of college students' learning behaviors and explores the predictive learning effect by constructing a predictive model of learning effect based on information literacy learning behavior characteristics. The experiment used 320 college students' information literacy learning data from Chinese university. Pearson algorithm is used to analyze the learning behavior characteristics of college students' information literacy, revealing that there is a significant correlation between the characteristics of information thinking and learning effect. The supervised classification algorithms such as Decision Tree, KNN, Naive Bayes, Neural Net and Random Forest are used to classify and predict the learning effect of college students' information literacy. It is determined that the Random Forest prediction model has the best performance in the classification prediction of learning effect. The value of Accuracy is 92.50%, Precision is 84.56%, Recall is 94.81%, F1-Score is 89.39%, and Kapaa coefficient is 0.859. This paper puts forward differentiated intervention suggestions and management decision-making reference in the information literacy teaching process of college students, with a view to adjusting the information literacy teaching behavior, improving the information literacy teaching quality, optimizing educational decision-making, and promoting the sustainable development of high-quality and innovative talents in the information society.Our work involving research of the thinking and direction of the sustainable development of information literacy training proved to be encouraging.

Under the epidemic situation, it is more and more important to improve college students' information literacy.In this paper, we are the first to propose an information literacy improvement model for college students based on smart learning environment. On the basis of previous studies and literature analysis, we describe the elements of the smart learning environment for the cultivation of college students' information literacy.These elements, which we summarize as CIAP, consist of four aspects: conceptual level, intelligent level , action level and process level.Based on CIAP,we propose a new blended learning model to improve college students' information literacy sustainably. The first is to expand learning resources by special topics; The second is to create a learning environment intelligently; The third is to clarify the interactive learning activities; The fourth is the innovative mutual learning process; The fifth is the timely verification of learning feedback; The sixth is the multiple optimization of learning evaluation.We have carried out targeted experiments to test the validity of the blended mode.Through the concrete empirical study of college students majoring in engineering technology in Chinese university, it is concluded that there is a statistically significant difference between the post-test data of the experimental class and the control class.The results prove that the blended learning based on smart learning environment proposed in this paper has a significant effect on the cultivation of information literacy of college students.This paper discusses the spiral development of information literacy enabled by the smart learning environment. Our work involving studies of the thinking and direction of the sustainable development of information literacy training proved to be encouraging.

No abstract

No abstract