Big Data "revolution" education makes exams more scientific

Data, generally refers to the use of scientific experiments, testing, statistics and other means obtained, for scientific research, technical design, verification, decision-making and other purposes of the numerical value. Through a comprehensive, accurate, systematic measurement, collection, recording, classification, storage of these data, and then through rigorous statistics, analysis, testing of these data, we can draw some very convincing conclusions. Large-scale, long-term measurement, recording, storage, statistics, analysis of these data, the vast amount of data obtained is large data. In the production of large data, the need for strict program design, variable control and statistical testing, otherwise the large data obtained is not comprehensive, inaccurate, worthless or small value.

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.

Analysis of large data-assisted teaching reform

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.

Large data technology allows primary and secondary schools and universities to analyze all important information from student learning behavior, test scores to career planning. Many of these data have been stored for statistical and analytical purposes by government agencies such as the American National Center for Education Statistics.

In recent years, more and more network online education and large-scale open network courses turned out, but also to the education field of large data access to 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.

Now, large data analysis has been applied to American public education, which has become an important force in teaching reform. In response to this trend, the Federal Ministry of Education in 2012 participated in a large data program in public education costing US $200 million. The plan aims to improve education through the use of large data analysis. The federal Department of Education spends 25 million of dollars on the budget to understand how students learn at a personalized level. A partial overview of the program's data and cases has been disclosed in the United States Department of Education Technology Office, published April 10, 2012, through education data mining and learning analysis to promote teaching and learning (draft public review).

The United States Department of Education's use of large data is mainly to create a "learning Analysis system"-a joint framework for data mining, modeling and case application. These "Learning analysis systems" are designed to provide educators with more, better, and more accurate information about how students are learning. For example, does a student have a bad grade because he is distracted by his surroundings? Does the failure of the final exam mean that the student does not fully grasp the content of the semester or is it because he has asked for a lot of sick leave? The use of large data learning analysis can provide educators with useful information to help them answer questions that are not very well answered.

So many people ask, can big data save American public education? Bill Gates, the founder and former chief executive of Microsoft, the world's largest computer software provider, said March 7 this year at an education conference in Texas State, the capital of Austin, that using data analysis to teach big data can improve students ' academic performance, Save America's public school system. He says technological advances in education have stalled over the past more than 10 years, and research and development spending is far from enough. Gates confidently believes that the key to the future development of educational technology is data. At the conference, more than 5,000 participants discussed the future of educational data applications.

Large Education Data Market prospects

The poor performance of high school and college students in the United States-high school drop-out rate of 30% (on average every 26 seconds a high school dropout), 33% of college students need to be rebuilt, 46% of college students do not graduate from normal--while the education sector, but also let the education technology companies found a chance to gold In recent years, many educational technology companies have started the market of large data learning and analysis, the competition is extremely fierce.

Some companies in the United States have successfully commercialized the big data in education. IBM, the world's largest information technology and business Solutions company, is working with Alabama State's Mobaire County Public School District for Big Data. The results show that large data plays an important role in school work. When IBM was just starting to work with the school district, the county was facing a severe drop in drop-out rates of 48%, in addition to poor student performance. According to the federal government's "Don't let one Child Left Behind Act" (No Children Lift BEHIND,NCLB), local governments with poor student performance will be punished. In response to this huge challenge, the county has previously built a school dropout indicator based on student data and used it for decision-making at the local level. But IBM believes that this is still not enough to improve the status of the county's distress, the need to use IBM Technical support to re-establish large data, and then using large data analysis to improve the overall performance of all students in the school district.

In the American Education data field, in addition to the leading IBM, there are like "Sivitas learning" (Civitas Learning) such as emerging enterprises. "Sivitas Learning" is a young company focused on the use of predictive analysis, machine learning to improve student performance. The company has established the largest database of school learning in the field of higher education. Through these massive data, we can see the main trends of students ' scores, attendance, dropout rate and retention rate. By using the records of 100多万名 students and 7 million of course records, the company's software allows users to detect the warning signs that lead to dropping out of school and poor academic performance. In addition, users are allowed to discover specific courses that lead to unnecessary consumption and to see which resources and interventions are most successful.

In Canada, the education technology company headquartered in Ontario Prov., "eager to learn" (Desire 2 Learn), is already facing students in higher education, and has launched a large data service project based on their own past academic performance data to predict and improve their future academic performance. The company's new product is called the Student Success System (Student Success systems). "Eager to learn" claims that 1000多万名 college students in Canada and the United States are using their learning management system technology. "Eager to learn" products through the monitoring of students to read electronic curriculum materials, the submission of electronic version of the work, through online communication with students, completion of exams and tests, can let its computational procedures for the continuous and systematic analysis of each student's education data. The teacher is no longer the one that used to show only the results of the students ' scores and assignments, but rather more detailed information such as the length of the readings, so that the teacher can diagnose the problem in time, make suggestions for improvement, and predict the students ' final exam results.

Leading developers such as the American Dream Box Learning (Dreambox Learning) and the "Newton" (Knewton) have successfully created and released their own version of adaptive Learning (re-use Learning) systems that use large data. At the 2012 International Consumer Electronics Exhibition's Higher Education Technology Summit, the world's largest educational publishing company, Pearson Group (Pearson), and the pioneer in adaptive learning, Newton, jointly released the adaptive learning products developed primarily by Pearson Group-"My Lab/Master Master" (mylab/ Mastering). The product provides personalized learning services to millions of students around the world, providing them with authentic and authentic learning data that the school can use to improve their learning effectiveness and reduce their teaching costs. The first product will be used in hundreds of thousands of American students, including math, English, and writing skills development classes.

Newton's founder, CEO Hose Ferreira and President Gregg Tobin of Pearson's Higher education branch attended the "My Lab/Master Master" Conference and presented details of the collaboration, discussing the future of higher education. "Personalized learning is a key point in future education," Tobin said. We integrate the technology of Newton into the product of ' my lab/Master Mastery ', which is the leading trend of the whole industry into the new era of personalized education. "From this fall, Pearson's course materials will be adapted to meet the unique learning needs of each student, with the support of the New Orleans technology," Ferreira said. Students can generate a lot of valuable data that Newton can analyze to ensure that students learn in the most effective and efficient way. This is a new frontier area of education. According to the agreements already reached, the two companies will further expand their cooperation in 2013 to include the fields of university mathematics, university statistics, college first-year compositions, economics and science into their products.

In addition, the "Curriculum Elves" System (CourseSmart), developed by Mcgraw-hill Hill Corporation, headquartered in New York, and by Pearson and other publishing companies based in London, also allows professors to track their academic progress by allowing students to use electronic textbooks , and show the teaching assistants a lot of data information, such as learning participation and academic achievement, but the system does not have the predictive function.

(Responsible editor: The good of the Legacy)