In the future, the transformation of education by big data and artificial intelligence will continue to ferment.
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Bill Gates once predicted, "In five years, you will be able to get the best courses in the world for free online, and these courses are better than those offered by any university."
Now it seems that although not every online course can be better than university courses, online education has become a reality. According to industry estimates, the number of online education users in China is over 100 million, and the market scale is several hundred billion yuan, so online learners have benefited a lot.
Not only has online education become a new outlet, but at the same time, with the blessing of big data and artificial intelligence, related applications in the education industry are entering the deep water period, and the form of modern education is quietly changing.
Big data +AI empowerment education
At present, big data +AI is empowering all walks of life, and education is no exception. Intelligent technologies such as face recognition and speech recognition have been applied to Chinese, English, music and other disciplines, providing more intelligent and personalized solutions for education.
From the perspective of teaching process, big data+artificial intelligence can diversify the form and content of education from teaching, learning, evaluation and management.
give lessons
"I have to admit that we know too little about students." This is a classic saying of Carnegie Mellon University School of Education, and it is also a common topic in the field of education.
For the generation after 80s, 90s and earlier generations, all students have received production line education from primary school to university. A generation of students use the same set of textbooks, and one teacher is responsible for each subject and passes the same set of standards, because personalized private education is still an extravagant hope.
Now, big data and artificial intelligence can help realize adaptive education and personalized teaching easily. In terms of teaching methods, smart classroom can provide teachers with more abundant teaching methods, full-time interaction and application-oriented teaching. Teachers no longer just have a textbook in class, but can access a large number of high-quality learning resources in the background at will and show them to students in various forms.
For example, the application of speech recognition and image recognition in education has greatly improved the teaching experience of teachers and students. For an English sentence, you can take a photo with your mobile phone and upload it to the cloud. The system will read this sentence with appropriate tone and intonation according to a large number of phonetic materials, and it can also be combined with phonetic evaluation technology to make students follow this sentence, and the system will make an evaluation and read it repeatedly.
At the same time, through the combination of virtual reality, augmented reality and big data, the educational scene can be restored as much as possible, so that students can love and enjoy learning, and the learning effect can also make a qualitative leap. For example, Google is creating a teaching application "realistic teaching" by introducing AR and VR technologies, and quietly changing the way of classroom activities.
In the teaching process, by collecting and analyzing the data generated in the process of students' daily study and homework completion, teachers can accurately understand each student's knowledge and assign homework for each student in a targeted manner, so as to achieve the effect of teaching students in accordance with their aptitude.
In addition, robot teaching will become a trend in the future. In a class of more than 300 people at Georgia Institute of Technology, Jill Watson, an artificial intelligence robot teacher, worked as a teaching assistant for a month, and she would reply to emails as soon as possible, and her tone was not mechanical, so no one found out that she was actually a robot.
study
For students, in the learning process, on the one hand, big data technology can be applied to make knowledge maps and make learning plans according to the relationship between knowledge points; On the other hand, data mining technology can help to further analyze students' individual learning level and establish a matching learning plan. AI system can determine how to provide students with personalized supplementary guidance to help them learn efficiently and avoid sea tactics.
For example, the exam questions that used to take three hours to practice may only take half an hour to master the knowledge points that really need to be mastered. Then, by applying big data and artificial intelligence, students' academic performance can be continuously evaluated, and exercises suitable for each student can be recommended in a targeted manner, saving time, but achieving better learning results.
At the same time, using image recognition technology can further improve learning efficiency. Now, students can take photos of textbooks or homework topics through mobile phones, analyze photos and words, and show the corresponding points and difficulties. Subsequently, online classes, encyclopedia links, PPT and PDF files uploaded by teachers provide more possibilities for autonomous learning, and the whole process is collected and processed by machine learning and natural language processing technology.
In addition, online education is in full swing. By providing flexible and diverse course forms such as video teaching, riddles and games, as well as high-quality and rich course content, learning is not limited to a certain time and place, and learning plans can be arranged flexibly and effectively.
Among them, as far as programming is concerned, more and more children learn through online education. For example, programming cats rely on artificial intelligence and data mining systems to provide a graphical programming platform for 6~ 16-year-olds and push differentiated courses for different students. By using graphical programming language to create games, software, animations, stories and other works on the platform, students can improve their logical thinking ability, task decomposition ability, interdisciplinary integration ability and teamwork ability simultaneously.
Testing and evaluation
In traditional education, exams and evaluations can be said to consume teachers' time. Nowadays, with the maturity of big data, character recognition, speech recognition, semantic recognition and other technologies, large-scale automatic correction and personalized feedback are becoming a reality.
By applying big data and artificial intelligence, teachers only need to scan the papers that need to be marked, and they can count and display the number, average score, highest score, and the most concentrated wrong questions and corresponding knowledge points in real time, which is clear at a glance and convenient for comprehensive real-time analysis.
If you need to analyze hundreds of thousands or millions of test papers, you can also quickly check and check all test papers with similar goals through accurate graphic recognition and massive text retrieval technology, and quickly extract and mark test papers that may have problems to help realize intelligent marking.
In this regard, Iflytek can be said to be at the forefront of the industry. Its spoken English automatic assessment, handwritten character recognition, machine translation and composition automatic marking technology have passed the appraisal of the Ministry of Education, and have been applied to automatic marking of spoken English and composition in college entrance examination, senior high school entrance examination and academic level in many provinces and cities across the country.
operate
If most learners only pay attention to the "learning" part, then school education needs to further analyze the data of educational behavior and do a good job of management outside teaching. Through intelligent technology, fully considering the campus management needs including academic affairs office, student affairs office, school office, school affairs office and other departments, schools can further collect, record and analyze teaching and learning and their related educational behaviors, better outline the real form of education and teaching, and effectively promote teaching informationization.
At present, some colleges and universities have established functional applications such as student portrait, student behavior early warning, student family economic situation analysis, student comprehensive data retrieval, and student group analysis. , to help better distinguish the potential of students in the direction of professional study or employment, so as to provide students with personalized management and training programs.
For example, in the face of diverse course selection needs, how to arrange courses reasonably has become an urgent problem to be solved. Without artificial intelligence, teachers often need several weeks to arrange courses, which cannot guarantee students' satisfaction. Now the artificial intelligence algorithm is used to arrange courses. Students only need to submit their own courses, and the system can quickly arrange courses in combination with courses, classrooms and teachers, which greatly improves the efficiency and student satisfaction.
In the field of education, this is only the beginning, and the transformation of education by big data and artificial intelligence will continue to ferment. In the future, we will personalize education with big data and empower education with artificial intelligence, and make full use of high-quality teaching resources to teach students in accordance with their aptitude while doubling the educational production capacity.
In this regard, we should not only look up at the starry sky, but also look down to earth. As the educator Mr. Ye Shengtao said, education is agriculture, not industry. Not only does education need a development process, but children also need growth time like crops. Big data and artificial intelligence will become important nutrients and auxiliary forces during their growth.
The picture comes from the internet.
Editor: Huang
Proofreading: Wang Hongyu
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