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Big data subverts your common sense of family education
1. How can big data be applied in primary and secondary education?

Of course.

At present, all countries in the world make decisions based on common sense and educational experience, and evidence-based teaching is an ideal form of future education.

The subject's thinking is excellent, and it is naturally feasible to predict students' learning situation through past grades and exam performance. It is only through standardized tests (uniformly assigned homework or exams) that students' understanding of the course is tested, so the feedback is actually very single and narrow.

Therefore, although test scores are very important, at the level of big data, we need more dimensions of data for combined analysis in order to get more specific and accurate results. If there are only changes in students' grades, only one report can be generated as a teacher's performance appraisal, but it can't produce the improvement of teaching quality that the subject hopes to get.

Like now, various online courses are developing rapidly, which allows students to collect small feedback in teaching in time. With the increase of communication channels between home and school, the system of students' performance at home can also be understood by parents. Incorporating multi-category data into the analysis scope and analyzing these data in the form of big data can reshape the whole learning process of students, and in addition to the results, it can also accurately get the learning details and status of each student. This can be said to be very convenient.

2. What is big data, and what conveniences and opportunities does it bring to human life?

Driverless cars, personalized teaching materials for students, computers for editing news ... Recently, at the "First Seminar on Innovation and Media Change in the Age of Big Data" held in Beijing, experts suggested that big data would bring subversive influence to our lives.

From "driverless" to "mobile office", a self-driving car has just completed a trip across the United States recently. This blue car started from San Francisco, took 9 days, passed through 15 states, traveled 3,400 miles, and finally arrived in new york.

Along the way, 99% of the driving is done by the car itself, and only on urban roads can there be manual intervention. Zhang Jiupeng, general manager of Volkswagen brand of Porsche Automobile Holding Group, is not surprised.

He revealed at the big data era seminar that Porsche successfully achieved long-distance driverless driving last year. Now the car is equipped with computers and all kinds of communication equipment, and it cooperates with China Unicom, from "unmanned driving" to experimental "mobile office".

"The future office is no longer confined to one place, but a mobile family." Zhang Jiupeng said that the traffic jam from home to the company may be 1 hour or even longer, so many drivers are very upset.

Now you can set the expected destination and make the car driverless. There are all kinds of foldable office supplies in the car, so people can do things in the office, such as video conference, document review and countersigning.

Zhang Jiupeng said that in addition to "driverless" and "mobile office", big data has brought other conveniences to car users. If you want to maintain your car, you need to drive it to a 4S shop or repair station. Now this method has undergone a qualitative change.

People can find someone to maintain their car at home through mobile APP or phone; You can also view the driving trajectory of the car through the APP, including the driver's appearance characteristics, the interior environment, and related data such as time consumption, fuel consumption, power, driving time and mileage. What convenience does the era of big data bring to people's lives? From user data matching to precision marketing, "Big data is becoming the core and most valuable content of the future media itself, which can help users achieve personalized customization."

Wang Lixin, a professor at Beijing University of Posts and Telecommunications, said that through the progress of IT technology, accurate and intelligent matching of information between the supply and demand sides can be achieved at a cost close to zero, thus bringing mankind into the era of "self-economy". For example, Wang Lixin said, "The production cost of a refrigerator is about 1200 RMB, and the final profit is only in 38 yuan.

If I use big data to make money, my slogan is' free refrigerator'. Then add two functions to the refrigerator.

One is to add an information scanning system, and the other is to install a router in the refrigerator to send all consumption data to the enterprise cloud database. "Consumers don't have to go to the mall to buy things, they call the company directly, and some people deliver them to consumers, and their commodity prices will be cheaper.

There are also free predictions about the shelf life of food in the refrigerator. "For example, if you have a meeting here, your mobile phone rings and the text message says,' Master, stop talking. I am the fourth bottle of yogurt in your refrigerator. If you don't drink it within two hours, the shelf life will expire.

Wang Lixin said that through the big data collected, it is clear at a glance what food was bought at home and how much milk was drunk in the refrigerator. Then, according to this demand, manufacturers of beverages, dairy products, etc. can be notified to reduce the prices of goods purchased from these enterprises through consultation. "In this case, if a family spends 2,000 yuan a month to buy food in the refrigerator, and only earns 10% through big data, it is 200 yuan, and the manufacturing cost of the refrigerator can be recovered in six months.

Do you want to sell refrigerators to make a net profit in 38 yuan, or do you want to make a net profit of 10,000 yuan or 20,000 yuan in the next decade? The key is to collect data, accurately match, and strive for reverse charges from companies and platforms, always representing the interests of users and making them free! "Wang Lixin said. What convenience does the era of big data bring to people's lives? Li Lin, deputy general manager of Chinese online such as personalized teaching and "Robot News", believes that big data is conducive to personalized teaching support.

"Through data analysis, accumulation and mining, it is conducive to the personalization and accuracy of teaching and learning. In addition, students can be diagnosed and fed back at any time according to the problems in their learning process, and provide students with teaching guidance materials that meet their personality. "

Luo, Executive Dean of School of Journalism and Communication, China Youth University for Politics, put forward "robot news", that is, with the popularity of big data, the news industry has become a machine to do most of the work, and the machine can even act as an editor. "Data news is different from traditional news production methods.

Traditional news production integrates reports through journalists and editors. Now, many of our news clues, data mining and integration are done by computers.

Some computers have templates written by reporters. As long as you enter the corresponding keywords, you can produce different news. Big data can also help predict the box office of movies, so as to choose scripts, actors and so on.

Li, a researcher at Tsinghua University Media Research Laboratory, said, "At the end of last year, we set up a new media division, which is mainly to predict the box office of upcoming or on-going movies and help filmmakers to subdivide the word-of-mouth and audience psychology. We provide data support for filmmakers and distributors by collecting data for analysis and comparison. "

Zhong, director of Pony Pentium and president of Junshe Culture, said that in the past, the way of choosing film themes was "particularly simple and rude", that is, directors and production company bosses could shoot whatever they wanted. Now, with the advent of the era of big data, it is more based on the preferences and needs of the audience and the expertise of the creators to find a balance point to choose the theme.

"In the past, when combining film and television works, including creative teams and actors, the choice was judged by experience. All the film and television companies robbed several A-list stars. But the real grab is not necessarily the best market effect, only a clearer audience preference.

Through big data analysis, our current actor matching will be more scientific than before. This is an article about the convenience brought by big data. The landlord needs to know about big data and can go to the data circle forum.

3. What has the intelligent analysis based on big data subverted?

Therefore, players in the industry who can control the development pulse of the industry in advance through big data intelligent analysis will take the initiative in the market and competition. Let's take a look at what intelligent analysis based on big data has subverted.

Social life will change and change. Different from oil and other industries, IT industry can bring new value-added products to human society. Similarly, the intelligent analysis of big data will not directly bring new specific products.

This is because information can really generate social value after it is used, so big data analysis, as information technology, is an intermediate industry. The basics of human social life are food, clothing, housing and transportation, and technology will eventually serve these traditional needs, but in different forms.

New technologies sometimes change the service model of traditional industries, just as Internet advertising is to traditional media advertising. When Internet services emerged, advertising gradually changed from the traditional industry to the new Internet advertising industry, thus creating almost 99% Internet players. New technologies sometimes change the efficiency and effectiveness of services. For example, Weibo is now used as a monitoring tool.

Compared with traditional media, this service mode has changed the efficiency of information dissemination and the scope of information audience, and this seemingly weak feature has become an advantage in the current social environment because of the weak centralized control of the media. The essence of intelligent analysis based on big data is the service efficiency and effect of digital society, and the important premise of its realization is digitalization.

With the development of information technology, people's service systems for food, clothing, housing and transportation will be digitized one after another, including retail, logistics, departments and catering systems. The virtual world and the physical world fit together, and the virtual world carries a lot of service delivery processes, so people can enjoy services without going to the scene. Once this big industrial background is formed, the problem of efficiency and effectiveness will become the most critical competitiveness of the whole industrial service.

In other words, the ultimate cost competition of service is that whoever has the highest efficiency and the best effect under the unit cost will become the king. Especially when the constraints of physical time and space are weakening, every player in the industrial chain may face global competition.

In a broader competitive environment, big data will change the operating mode of enterprises and enhance their adaptability, judgment and efficiency. Therefore, the great value of big data is more reflected in promoting industrial change and transformation than creating new products.

It is expected to solve the problem of artificial intelligence. Selling big data is not simply following the trend, but focusing on solving the expansion and growth of artificial intelligence. Traditional artificial intelligence has gone through a long course of decades, and the changes in the past three decades have been particularly slow.

This is because although traditional artificial intelligence can solve any given problem and scenario, it is embarrassing that it is impossible for people to enumerate all the examples and parameters in advance, so it is difficult to copy the existing models and algorithms of artificial intelligence across systems. Many scholars and industry elites have given intelligent analysis based on big data a beautiful vision, that is, once a digital society is formed, everything in life can be described based on data.

These described information will become the basis of wisdom growth and decision-making judgment. If the computer can find out the learning rules and methods behind it, it can reflect the cross-domain expansibility of human intelligence in the virtual world of the computer and make fuzzy judgments.

More importantly, such an analysis system will have the unprecedented basic ability of artificial intelligence-learning ability, and can continuously increase its intelligence according to the changes of environment (data), and even be extended. Theoretically speaking, once the machine has the learning ability, the computer system will have the typical characteristics of people-creativity.

If we follow this idea, intelligent analysis based on big data will further replace the work that must be done by people in the traditional service system, especially the most expensive part. For example, there is a Spanish learning software "Domingo", which can teach students in accordance with their aptitude.

In the past, this was usually done by the human brain. However, there is still great uncertainty about whether the intelligent analysis of big data can really reach the height of dreams, and it will take time to form a fully digital society.

User's ability to portray and shape competitive advantage In our IT industry, with the passage of time, technologies will converge, product forms will converge, and basic service methods will converge, so costs will inevitably converge. In this way, the price war of industry players is difficult to maintain for a long time, which will inevitably force the service providers at the top of the industrial chain to differentiate mainly in "service".

The essence of service is "whether the user's needs can be truly judged timely and accurately", and the basis of this judgment is "the user's ability to portray". When the IT back-office system can accurately judge when, where, who, what to do and what to do, all services will be targeted, not only achieving the lowest cost, but also achieving the best results.

In this regard, the intelligent analysis of big data is most likely to subvert the user-oriented product and service market. No matter what kind of service, whether it is selling things or advertising, as long as the service object is "people", intelligent analysis of big data can provide the best recommendation, thus improving the quality of service. However, from the current research, the technical competition of products and services has returned to the original point, and data itself has become the source of competitiveness.

This situation will eventually change. In fact, analysis, modeling and interaction are inseparable, and only a system with feedback and continuous learning can realize the representation of users.

If a product or service is compared to a car, big data analysis can be regarded as an engine, and data is like essential gasoline in the engine. Therefore, the control of data and the characterization of users will inevitably become the inevitable strategy and technical layout strategy for players who provide services to end users in the industrial chain, and the operation of data assets may also become a new trend and trend.

Due to the restriction of economic conditions, the labor cost of replacing labor-intensive services by machines varies greatly in different regions and industries, which directly leads to the differences in services in different regions. But in the long run, it can be done by machines.

4. Ten popular science knowledge with data

There are 1, 65438+ million auditory nerve cells in the human ear.

2. There are about 6.5438+million olfactory cells in human nose.

3. The human brain has 1000000000 nerve cells.

4. The human body produces 100000000 new red blood cells every day.

5. Each eye contains about 65.438+0.2 billion rod cells.

6. The melting point of gold is relatively high, reaching 1063 degrees.

7. There is an average of 1 g of gold in every 300 tons of rocks in the crust.

The land area of China is 9.6 million square kilometers.

The average distance between the moon and the earth is 384,400 kilometers.

10, and the monthly nuclear temperature is about 1000 degrees.

1 1, the moon is about 3476 kilometers in diameter.

5. What impact does big data have on future education?

As an important part of social subsystem, education is also deeply influenced by the arrival of big data.

In the teaching management of foreign universities, the mining of educational data has also become an important way to improve the teaching management level and teaching quality. American schools can predict the enrollment rate of students with 85% accuracy through the analysis of student data.

[4] Under the influence of current social transformation, there are many problems in education in China. Through the emerging big data technology, the formulation of educational policies, the formulation of learning programs and the evaluation methods will undergo revolutionary changes. 1. permeates the core link of education, and there is a philosophical dialectical relationship between education and society. On the one hand, talents who can change and create the world are trained through education; On the other hand, education is deeply influenced by current social atmosphere, national system, economic situation and cultural tradition.

At present, education is deeply influenced by industrial society. From the middle of18th century, the whole world began to be influenced by the industrial revolution, the expansion of the market and the requirements for work experience and technology, which put forward new requirements for the quality of the labor force. Practical ability has replaced the emphasis on personal cultural literacy learning in the past, and whether it can solve problems has become a symbol of measuring talents.

This view of talents has a great influence on education, which can be seen from the popularity of American pragmatic philosopher Dewey's educational thought. The arrival of the era of big data will completely change this educational concept that has lasted for nearly three centuries.

Alvin toffler, a famous American futurist and one of the most influential social thinkers today, put forward an educational place to entertain the future in his book The Influence of the Future. He predicted that the future education will face service and innovation, so the boundaries of home-school education, educational space design and future-oriented schools will become a trend. [5] The ability to solve practical problems, as one of the talents' abilities in the era of big data, will gradually fade out from the logical starting point of education. Discovering knowledge, finding connections and summarizing laws will become important requirements for talents in the era of big data.

In the era of big data, teachers will focus on exploring students' learning-related performance and the most suitable methods for students' learning, rather than relying on conventional ability tests. Teachers analyze what students know and what is the most effective way to learn.

Through the analysis of online learning tools, we can evaluate the duration of students' online learning behavior and how students can quickly acquire electronic resources and master concepts. [6] From the actual situation in China, the formulation and implementation of educational policies are all top-down, which is conducive to the authority of policies and the efficiency of implementation, but the disadvantages of neglecting teaching and students' reality are also objective.

In the era of big data, through the analysis of educational data, it will be possible to find out the teaching, learning, evaluation and other situations that are in line with the actual situation of students and teaching, so as to formulate and implement educational policies in a targeted manner, and thus formulate more practical educational strategies for students. 2. Reconstruction of teaching evaluation methods For a long time, teaching evaluation activities have mainly focused on the evaluation of teachers by schools and higher authorities according to the lectures and students' test scores, or the evaluation of students by teachers according to their test scores, homework scores and classroom performance.

[7] Teaching evaluation activities promote teachers' teaching and students' learning, but the details need to be improved. For example, in teaching activities, which teaching method is the best and the easiest for students to accept depends on what students' learning habits are and what learning method is the easiest to master knowledge. The summary of these details may require a lot of practical experience, and short-term teaching evaluation is difficult to achieve. Big data technology obtains personalized teaching behaviors, habits and methods by analyzing the long-term behaviors of teachers and students.

We have to admit that we know too little about students. Similarly, we may know too little about teachers.

With the arrival of big data, teaching activities can be evaluated, analyzed and improved through technical aspects. First of all, the way of teaching evaluation is no longer empirical, but the law of teaching activities can be found out through a large number of data.

For example, the new generation of online learning platform has more parts of behavior and learning induction. By recording learners' mouse clicks, we can study learners' activity trajectory and find out how different people react to different knowledge points, how long it took, and which knowledge points need to be repeated or emphasized.

[8] For learning activities, the effect of learning is reflected in daily behavior. What knowledge is not mastered and what problems are most likely to make mistakes become the direct result of analyzing each student's individual behavior. Secondly, students can be evaluated in many ways, not just in a single dimension of knowledge mastery.

The evaluation of students should be diversified, especially through data analysis, we can find the changes of students' thoughts, mentality and behavior. For example, in the same dormitory, contact information is deleted from each other, or no data is generated from each other, then there must be something wrong with the relationship between classmates. Take care of students' psychology and behavior through data analysis.

If we analyze students' recent emotional state through text analysis and information grabbing, many tragedies may be avoided. Even if it is a single dimension to master knowledge, there are many factors, some of which are good memory and some are strong logical thinking ability. Through big data technology, we can analyze the characteristics of each student, so as to find advantages, avoid disadvantages and correct bad thoughts and behaviors.

Thirdly, teaching evaluation jumped out of the circle of result evaluation and realized process evaluation. Traditional teaching evaluation is mostly about teaching and learning, focusing on results.

In the era of big data, the process of education can be recorded by technical means. Now some schools have implemented electronic textbooks. If we can record homework, classroom words and deeds, teacher-student interaction and classmate interaction, and collect these data, we can not only discover the characteristics of students, but also worry about how to write the final evaluation.

3. Innovating the teaching thinking of educators Traditional education is that most education authorities and educators think that some factors are very important to teaching activities through research on teaching experience and their own summary, so they have repeatedly emphasized them. But some experience is unscientific, and common sense sometimes affects people's judgment.

Apple, for example, found that the increase in notebook computer sales was common sense.

6. How is big data used in the education industry?

1, change of center of gravity

In the era of big data, teachers' job is no longer simply to impart knowledge, but to diversify the output forms of knowledge and pay attention to students' personality characteristics. Turn unified and collectivized teaching into teaching supported by information technology. In other words, under the premise of understanding students' cognitive ability and knowledge structure, knowledge is transferred, integrated and imparted.

2. Meet the demand accurately

To meet the needs of users accurately here is to send educational information to users in need in time. For example, if a student wants to have English training in the near future, the information about English training will be delivered to the student in time. According to the user's study habits and living habits, there will be an intelligent data matching, so that the information and information received by users are exactly what they need.

3. Accurate advertising

In the era of big data, users' behavior habits can be easily inferred through some data analysis. Some education and training institutions can lock users and place advertisements through data analysis. For example, the frequency at which users turn on their mobile phones and their habitual behaviors within a certain period of time. Through big data, you can accurately deliver your own advertisements to users in need.

In addition, the development of the Internet and big data has also brought us opportunities to develop our personality, which can be said to be of great significance in pedagogy. Those so-called students who are not good at learning, if they have certain specialties in a certain aspect and also play their specialties, are no longer standardized education.

Big data technology can track and pay attention to the teaching and learning process of teachers and students on the education platform, record the digital traces of teachers and students' classroom performance and after-school behavior, and provide the most direct, objective and accurate evaluation of educational results for educational management institutions, schools, teachers and parents by capturing micro-behaviors in educational activities.

It can be said that the application of big data in the field of education is an inevitable trend of contemporary education development.