Analysis of students’ aversion to learning based on hash algorithm under multi-source heterogeneous data

Abstract

The research is based on multiculturalism, adopts multi-source heterogeneous data collection technology to realize the data collection and processing of influencing factors, and introduces multi-language variables based The attribute decision-making scheme is used to give weights to the influencing factors, and the multiple regression analysis model is used to realize the calculation of the degree of influence. In the collection and preprocessing of students’ relevant data, the study used the hash algorithm to reduce the interference of multiple sources of heterogeneous data to the analysis results. The result analysis shows that the aversion to learning among upper primary school students is influenced by various factors. Among them, with the increase of cultural diversity in the teaching process, students’ learning fatigue will increase to a certain extent, with the highest score reaching 37.8 points, and the correlation coefficients between each factor and students’ aversion to learning all reach 0.6. The above results show that under the influence of multiculturalism, students in the upper grades of elementary school are prone to learn-weariness. Therefore, it is necessary to propose effective mitigation strategies in teaching, so as to improve the quality of primary school teaching and provide a guarantee for follow-up education.