Big Data sounded the Horn of education

In recent years, as big data has become a buzzword in the Internet's information technology industry, education is increasingly thought to be an important area of application for big data, and it has been boldly predicted that big data will revolutionize education.

"12 years of hard to cram, only for jinbangtiming!" "Every year the college entrance examination affects the minds of the examinee and the parents without counting, the end of the college entrance examination is naturally someone happy people worry, recently a netizen spit in Shanghai, he never thought is this year's Shanghai composition title" Freedom and Freedom "and Baidu Big data prediction of the probability and composition of the topic" freedom ", the similarity is quite high, Prior to a classmate to remind him to pay attention to him but he questioned and ignored, now regret??

Baidu's college entrance examination composition prediction hit a lot of provincial test results, no doubt for the future big data changes and subversion education and other traditional industries left a greater space for imagination.

Unlike traditional education

Better "aptitude"

In education, especially in school education, data has become the most significant indicator of teaching improvement. Usually, these figures refer mainly to exam results. Of course, it can also include enrolment, attendance, drop-out rates, graduation rate, etc. For the specific classroom teaching, the data should be able to explain the teaching effect, such as the accuracy rate of students ' literacy, the correct rate of work, the performance rate of various development--actively participate in the classroom science of hands, answer the number of questions, duration and correct rate, teacher-student interaction frequency and time. Further specifically, for example, each student to answer a question the length of time spent, the different students on the same issue on the length of the difference between how much, the overall answer to the correct rate of the specific data through specialized collection, classification, collation, statistics, analysis to become large data.

Let's take a look at the traditional educational models: ringtones, classes, standardized classrooms, unified teaching materials, and time-programmed assembly-line scenarios?? In this mode, the score is everything, a class of dozens of people, using the same teaching materials, the same teacher class, after class layout the same homework. However, the students are very different, it is impossible to truly "teach according to their aptitude." But the big data education will present another characteristic: the flexible schooling system, the individualized counseling, the community and the family study?? And this, the relationship between people (teachers and students), will be through the relationship between people and technology to achieve, as the current Spring festival, not through text messages, telephone, video, micro-letter, but also back to 20 years ago riding a bike door-to-door a half hour of the era? Large data age, whether you agree with the technology to enrich the human feelings, technology, let us never back to the past.

With the development of technology, large data in the field of education has been more and more widely used, the school has the available, high-quality mass of data gradually become a reality, but how to carry out information mining, to bring more potential for future education, the educational researcher's imagination poses a challenge.

In recent years, more and more network online education and large-scale open network courses turned out, but also made large data in the field of education to obtain a broader application space. Experts point out that the big data will set off a new educational revolution, such as the reform of students ' learning, teachers ' teaching and the ways and means of making educational policies.

The ultimate goal of large data analysis in the field of education is to improve students ' academic performance. Students with excellent grades are good for school, society and the country. Students ' homework and exams have a series of important information that is often overlooked by our regular research institute. By analyzing large data, we can find these important information and use them to provide personalized service to improve students ' performance. At the same time, it can improve the students ' final exam results, the usual attendance, drop-out rate, graduation rates and so on.

The road is long and it's still going up and down and searching

How many teachers can really understand students? Little。 In most teaching and research activities, how to judge the quality of a classroom? More is the expert esthetic type--Teacher's link design whether layer by layer progressive, raises the question whether is effective, the link establishment and this section activity goal whether conforms, and so on. And the students ' experience in this class, most of the time is completely neglected, even when paid attention to, and often is "represented"--the participants will assume the students experience according to their experience, and the student's real experience, but no strong technology and data sources can provide analysis and empirical.

The advent of the big data age gives us the opportunity and the ability to make up for or change the deficiencies in our current education.

How did we get to know the students in the past? We collect and analyze the teaching process and the students ' learning situation, including the students ' overall academic level, physical development and physique condition, social emotion and adaptability development, satisfaction to the school and so on. These data are obtained in periodic, phased assessments. The data reflects the results of education, the students ' learning status, physical health and mental health status, and the subjective feelings of the school.

Big Data has the ability to focus on the microscopic performance of each individual student-when he opens the book, when you hear something, smile and nod, how long did you stay on a topic, how many times have you deserted in different subjects, and how many classmates will initiate active communication with each other??? The production of these data is entirely procedural: the process of the classroom, the process of the assignment, the interaction between the teacher and the student. These highly personalized data are generated by the actions and phenomena that occur at every moment, and are stored in full records. Through the integration of these data can enlighten us: How should the classroom design to meet the psychological characteristics of students? Does the course attract students? Which student needs individual instruction? How is the teacher-student interaction way popular??? Most importantly, the collection of these data requires only a certain amount of observation technology and equipment, the students can complete without self-knowledge, does not affect the students any day-to-day learning and life, is the most natural, the most authentic data.

Therefore, in the field of education, large data in addition to embody all the macro functions of traditional data, but also collect and analyze detailed micro-personalized data, the advantages of large data display. Traditional data vs. large data: The traditional data annotation macroscopic, the whole education condition, the big data can also analyze microcosmic, the individual student and the classroom condition, uses in adjusts the education behavior and realizes the individualized education; traditional data mining methods, collection method, content classification, collection standard, etc., have existing rules, complete methodology, Large data can also be mined without forming a clear method, the path, and the novelty of judging criteria; traditional data comes from periodic, targeted assessments, the sampling process may have systematic errors, large data from the process of the real-time behavior and phenomenon record, the third party, technical observation sampling method error is less The traditional data analysis requires the talent, expertise and facilities are more common, easy to access, large data mining needs of the talent, professional skills and equipment requirements, and practitioners need to be innovative and data mining inspiration rather than the step-by-step.

Using the present more mature information technology facilities, the students ' personal data in the learning activities are recorded and accumulated in high density and frequency, thus providing abundant data resources for the quantitative analysis, which can provide us with a lot of accurate data. These data can provide us with a more comprehensive and profound understanding of students and their learning to support, so that we have to do in the past can not do things, become a reality.