As the application field of artificial intelligence expands, AI technology has been considered as one of the important ways to change the existing education scene.
When we looking it from a bigger picture, teaching, management, and evaluation are the three main application directions for AI in education.
To be more specific, image recognition technology can liberate teachers from checking homework and marking grades. Through speech recognition and semantic analysis technology, it can assist teachers in oral test and correct students’ English pronunciation. Through human-computer interaction technology, it can assist teachers to answer questions for students.
Most importantly, the combination of AI technology and education is likely to enable educators to realize their dream of “teaching students according to their personalities”, thus truly improving the quality, efficiency, fairness, and other core issues of education that faced.
Of course, it is not an easy thing to teach students in accordance with their personalities in a large quantity. Thus the precision matching will require the support of the data annotation industry.
AI technology promises to transform education from “one teacher VS multiple students” to “one teacher VS one student”, but how to collect and use the data becomes a big problem. Through the application of artificial intelligence technology in all aspects of education, comprehensive data of various types of students can be collected.
These data will be annotated and processed by a data annotation platform to meet the needs of relevant algorithm analysis requirement and enable machines to have cognitive abilities, so as to plan learning paths for students based on their situations and realize the purpose of personalized education.
The specific applications of data annotation in the FIELD of AI education are mainly as follows:
- 2D bounding box
label out the teachers and students
label out humans on this picture
Above data involves privacies such as faces, so data security is an important factor to be considered in the process of labeling.
Take bytebridge.io Technology as an example. In the specific labeling process, bytebridge.io will protect data from data leakage through asymmetric encryption and storage, and at the same time support private cloud deployment to avoid potential data risks.
In the information age, cultivating innovative talents is an important task of the current education system.
The natural language processing ability, data collection, and analysis ability of artificial intelligence can be used to analyze students’ learning behavior, and customize learning methods suitable for students according to their strengths and weaknesses, to achieve real one-to-one personalized teaching and cultivate more innovative talents for the society.