1. A Study on the Blended Mode of College English Teaching based on Modern Educational Technology

With the rapid development of information technology, more and more network technologies and electronic devices are used in the classroom, and the teaching methods are more diversified. The core of the college English blended teaching model is to emphasize the combination of online learning and classroom learning effectively. It is necessary to pay attention to traditional face-to-face teaching methods and to utilize rich network resources. This blended mode can benefit students' learning efficiency and self-learning ability, and can improve the teaching effect, which is worthy for further discussion and application [1]. This paper explores the definition and advantages of blended teaching, and discusses how to apply it in college English teaching from the aspects of technical equipments, teachers and students.

2. An Online Education Data Classification Model Based on Tr_MAdaBoost Algorithm

With the rapid development of network information technology and the wide application of smart phones, tablet PCs and other mobile terminals, online education plays an increasingly important role in social life. This article focuses on mining useful data from the massive online education data, by using transfer learning, relying on Hadoop, to construct Online education data classification framework (OEDCF), and design an algorithm Tr_MAdaBoost. This algorithm overcomes the traditional classification algorithms in which the required data must be restricted to independent and identically distributed data, since online education using this new algorithm can achieve the correct classification even it has different data distribution. At the same time, with the help of Hadoop’s parallel processing architecture, OEDCF can greatly enhance the efficiency of data processing, create favorable conditions for learning analysis, and promote personalized learning and other activities of big data era.