Application of Improved Deep Learning Algorithm in Modern Education Data Analysis System

With the development of science and technology, the requirements for talent training in the new era have gradually increased, and school education has also paid more attention to the cultivation of students’ innovative ability and problem-solving ability. The modern educational application course is a compulsory course for students majoring in normal education. This paper mainly collects modern education data, conducts research on how to effectively carry out the teaching of this professional course, improve the innovation ability and problem-solving ability of college students, and promote the growth of college students into educational talents who meet the requirements of the education system in the new era. This paper aims to further improve the constructed data analysis mode while verifying the effectiveness of the modern education data analysis system. Through the analysis of data sources such as classroom observations, student interviews, activity evaluations and questionnaires, a modern educational data analysis system based on deep learning algorithms is constructed to help students develop good study habits in the learning process and cultivate students’ higher-order thinking ability, to promote students to achieve a more efficient learning state in modern education. The final results of the study show that the largest number of people who cannot get accurate learning help is 144, accounting for 77.84%, indicating that modern education courses should take students’ personal experience as a priority. In order to trigger learners’ enthusiasm for learning, teachers are suggested doing teaching from solving problems and they should foster learners’ problem awareness.