The research theme on AI and education aims at applying some of the IIIA AI techniques to the field of education. It does not aim at completely automating some processes and replacing the human component, but supporting the human through mechanisms like team formation that allow for building more efficient teams, or peer-based assessments that support assessments in massive online courses.
Contact: Carles Sierra
It is always challenging to make predictions about the impact of technology on an economic or social sector. However, all recent analysis make it clear that repetitive tasks, or those with little added value by the humans who perform them, are going to be redesigned to facilitate their automation through the use of Artificial Intelligence (AI) techniques. Banking and commerce are examples of sectors that are undergoing a profound transformation, partly enabled by AI techniques such as chat-bots or personalization systems, leading to a notable reduction in employment. On the contrary, the education sector will continue to need the human component, and permanently, since the school fulfils an essential socializing function for the development of people. This need does not mean that AI is not going to impact educational processes; it has; it does and will continue to do so.
Today we have numerous AI applications, not necessarily developed specifically for education, but which are very useful in the education world. For example, automatic subtitling of videos, tutoring systems that interact in natural language, or the realistic conversion of text to human speech.
AI, in its origins, was already applied to education, in particular personalized education. Adapting the contents to each student is a pedagogical imperative that is difficult for teachers to achieve when the groups are large or the economic resources dedicated to education are limited. Several research groups developed simple systems of personalized education in the 1960s. Today, these systems have reached a remarkable level of sophistication. For example, over the past 15 years, the ALEKS system (aleks.com) developed in the United States has improved the performance of millions of students in mathematics. This system raises problems with an open response, analyses the answer and, thanks to a machine learning system, identifies errors and skills not acquired to explain the error to the student and recommend new problems that help to obtain the necessary skills. This type of system continues to be developed in different countries. The one created by Squirrel AI in Shanghai with more than three million students, and with a great improvement in individual performance is noteworthy (http://squirrelai.com/product/ials). We will no doubt see these systems more frequently over the next decade and covering areas increasingly distant from STEM, where they focus on today.