Adaptive Learning Model and Implementation Based on Big Data

Abstract

The traditional face-to-face education model can no longer meet the needs of further training outstanding talents. Only through the data learning analysis model, we can explore deeply and study the learner's learning process, discover the learning rules, and then provide them according to the characteristics and needs of each student; personalized adaptive learning and learning methods to give full play to the potential of students. This research starts from the connotation and application of data, and the comprehensiveness of the data and the potential big value. Based on data analysis, a personalized adaptive online learning analysis model is constructed from four dimensions: Data and Environment (Who), How and Target (Why). Taking C-language programming as an example, this paper analyzes the structure of learning process based on data and adaptive learning, the visualization of learning process and the empirical effect of learning. The research results show the data analysis of students' learning behavior and knowledge mastery. It can recommend a reasonable learning path and appropriate learning resources, and can provide timely and accurate feedback on the learning effect of students, and provide personalized service intervention, which is conducive to the promotion of teaching and learning.