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Four Uses of AI in Education

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The invention of artificial intelligence (AI) has transformed every walk of life. A wide ranging tool that enables us to rethink how we look, analyze, and process data, with AI, the future is here. One of the sectors that has been slow to implement this radical tool is the education system.

Here is a look at the four ways in which AI can transform the education system.

Personalized Learning

The current education system operates under the principle of equality. The idea is that everyone has access to the same materials and lectures, and a standardized test determines the temporary ability to master the required skill or content.

The thing is individual students differ in natural talent, abilities, and intelligence. This results in differences in learning, marked in areas such as understanding technical terms, the ability to memorize them, and link them to memory.

AI can allow us to account for this individual difference in knowledge acquisition. Using AI, extensive sets of data can be aggregated for each student (or group). By pulling this student data into one place, educators will be able to produce reports, predictive data analytics, and visualizations in real time and feed them into their classroom workflow. With time, this can allow teachers to know exactly what an individual student needs to succeed.

Understanding the stages of learning

Most scholars agree that the early childhood years set the stage for adult success. In psychology, early childhood is understood in terms of behavioural psychology. Studies looking to understand childhood cognitive development are usually small in scale and the experiments cannot be replicated. In addition, these studies are often difficult to generalize.

Neural networks can provide a basis for verifiable and easily disseminated study of child language development. Training neural networks to simulate early childhood development during key development stages will allow us to more effectively verify new learning theories and frameworks. These theories can then be used to better inform primary school curricula and radically alter the education system.

Digital School Systems

A large component of the education system is administration tasks. School systems produce insane amounts of data. Using data-driven AI, school systems can manage school and student data together and save it the form of large databases. Such algorithms can help ministries and schools make informed decisions that will increase the quality of educational outcomes and reduces the costs of administration.

Visual-Linguistic Interaction

In early childhood, children develop an understanding of themselves by considering and imitating their environment. To acquire new skills, children imitate their parents in their movements, how they walk, eat, or by repeating specific words, or laughter.

This method of learning requires not only effort and concentration from the child but also an understanding of the Visual-Linguistic interaction. This understanding allows parents and caretakers the ability to offer the child what they need to learn in the early stages.

One style of AI that follows the same primitive method is known as imitation learning. Imitation learning is about leveraging human data for good. With the development of AI techniques, robots can now work in a primitive style, reading and understanding a child's interaction, gestures, and movements, and processing them to help the child to learn. Leveraging imitation learning will help create a generation of children who can acquire knowledge better and faster.

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