Research on visualization methods of online education data based on IDL and hadoop

The research and development of Big Data, Cloud Computing, IoT and other new technologies, provide a strong technical support for vigorously promoting construction of online education. By using the Hadoop distributed file system (HDFS), MapReduce, Sqoop, HBase and other function modules of Hadoop, it can be easy to do normalized processing of massive education data which obtained from different online educational platforms. At the same time, education data can be quickly converted into graphic images, such as line drawing, contour map and grid surface map and so on, by using interactive data language (IDL) to program. These images provide a more scientific and intuitive method of researching on educational data. Experiments show that the visualization of massive education data will play an important role in the process of helping government to carry out scientific, educational decision-making, teacher to launch effective teaching activities and student to improve the efficiency of personalized learning.