In the math exam, are the two candidates who scored 90 points exactly the same?
Homework assigned by the teacher: complete questions 1 to 10. Is it really necessary for all students to finish this 10 problem?
A few days ago, the reporter attended the opening meeting of the national educational technology research and planning project "Research on the application of junior high school students' adaptive learning based on data analysis", which was presided over by Xue Haizhi and Yun Tong. Professor Zhang Jianping, director of the Academic Committee of the College of Education of Zhejiang University, director of the Institute of Digital Learning and doctoral supervisor of educational technology, put forward the view that in the Internet age, teachers should not only rely on experience, but also make full use of scientific analysis of learning behavior data.
"I have to admit that we know too little about students." This is the classic slogan of Carnegie Mellon University School of Education, and it is also the most concerned topic in the top ten annual education conferences in the United States. Similar thinking also exists in the field of education in China.
Professor Zhang Jianping believes that artificial intelligence+big data is catching up with human beings in some fields. The application of speech recognition technology is becoming more and more popular, and the accuracy of Chinese speech recognition has reached 97%. However, whether in China or the United States, the promotion and influence of modern information technology on education and teaching reform are still in the primary stage. Effective use of big data to promote the research and application of personalized learning still requires the joint efforts of researchers, technicians and front-line teachers.
For example, according to the traditional teaching model, we will think that students with the same grades have similar abilities. But if we borrow the analysis method of big data, the differences between students will be clearly displayed. If we analyze two candidates with 90 points, we will find that the first student may rely more on excellent logical thinking, while the other student relies on excellent memory. The abilities of the two children are completely different.
Learning analysis based on big data can make education and teaching truly face every individual. Big data allows us to look at students' development more comprehensively and find deep-seated problems that can't be reflected in previous test scores. Teachers can grasp this situation in time, help us fully understand each student's personality and characteristics through new technology, and then assign homework in a targeted manner to help students make up for their lack of ability, thus realizing the dream of teaching students in accordance with their aptitude, which was put forward for more than 2,000 years in that Confucius era.
In teaching practice, teachers should use big data to learn as much as possible about every child.
Take the internationally famous "Knewton" adaptive teaching platform as an example. The teaching resources on this platform can adapt to the individual differences of each student, and we can judge whether the current topic is too difficult, too easy or just right according to the students' learning performance. Change the difficulty of the topic in real time according to the judgment. Students can control their learning progress at their own pace and are not affected by the behavior of other students around them. Then the system will give a feedback to the teacher, tell which student has difficulties in which aspect, and give the overall analysis data of the whole class. If a student does the second question correctly, the system can immediately tell him to skip the fourth and eighth questions, because the second, fourth and eighth questions are all about the same knowledge point. If they are all done, it is a simple repetition. If student B makes a mistake in the third question, the system will prompt him to practice the sixth and ninth questions intensively. This is because based on the analysis of big data, students who make mistakes in the third question are likely to make mistakes in the sixth and ninth questions. Targeted repeated training is very necessary.
Modern information technology has liberated some teachers with innovative spirit, so that they can save a lot of repetitive work and concentrate on completing the core tasks of teachers. This is the technical liberation force. In this sense, no matter how good technology can replace teachers, it just redefines the roles of education and teachers.
In the Internet age, information technology can combine knowledge gathering with personalized recommendation through the deep integration of learning resources, knowledge navigation, recommendation engine and personality evaluation, optimize traditional teaching mode, reduce indoctrination and increase classroom interaction, which is undoubtedly a great progress in education. Therefore, the traditional classroom will realize the functional transformation and become a place to exchange learning results and dispel doubts. Personalized learning of online and offline integration (O2O) can be realized through the mixed mode of online and offline integration.