Exploration of Personal Big Data in Blended Learning

With the development of information technology, the application of big data in the field of education has been deepened, and blended learning has been popularized in teaching process. In blended learning, teacher can't remember every student in the process of learning in all details, resulting in methods of emotional subjective evaluation can only be used on the evaluation process of teachers to students. Without doubt it cannot describe their real behavior performance objectively and fairly. In view of this problem, this paper studies personal big data of blended learning, through the establishment of a large data model of personal learning, and analysis of these data, so as to provide a basis for objective evaluation. According to the data of teaching in software engineering course as an example, through the analysis of classroom video of the teaching process, gets the expression and action of learners in class in usual, and sees it as a factor of reflection of seriousness degree of the students listening in class, and it can reflect the attitude of students in a sense. This experiment shows that learning process of big data have a relatively objective evaluation to students, it can also show students' behavior history, so as to spur students to improve these behaviors consciously.