Analysis of Intelligent Personalized Learning Mode in Big Data Era

Abstract

With the advent of the era of big data, a new generation of intelligent information processing technology develop rapidly and vigorously, which has greatly promoted the innovative reform in the concept of education and teaching. The aim of this research is to promote learning efficiency and teaching precision through using big data technology and intelligent means. An intelligent personalized learning mode is built, which mainly including four aspects: academic analysis, intelligent push, individual feedback, multiple evaluations. The mode can conduct in-depth mining and analysis of student data, enrich students' off-class learning resources, intelligently push students' individual learning feedback in real time, and conduct multiple evaluations for each student. Consequently the mode completely changing the deficiency of the traditional learning mode, including one-sided cognition of each students, insufficient learning resources, lack of real-time feedback and single learning evaluation. The mode can form an intelligent and efficient personalized learning environment based on making the overall learning process quantifiable, real-time feedback, and evaluable.