the advantages of artificial intelligence applications in education are vast and varied. Here, everything can be considered to be beneficial if we are thinking of anything, for example a computer program, that can efficiently perform any task that would normally rely on the intelligence of a human. Based on the state-of the art research in this area, we outline nine areas in which AI methods can bring added value for both learning and teaching activities .The first benefit concerns automated grading which simulates the behavior of a teacher to assign grades to the answer sheets submitted by the students. It can assess their knowledge by processing and analyzing their answers, giving feedback and recommending personalized teaching plans.
Secondly, intermediate spaced repetition aims at knowledge revision when someone is just about to forget. It is worth noting that Polish inventor PeterWozniak introduced the Super Memo application, which is based on the effect of spaced repetition. The app keeps track of what a user is learning, and when he/she is doing it. By applying AI techniques, the application can discover whena user is most likely about to forget something and recommend revising it.
Thirdly, feedback loops for teachers, aided by machine learning and natural language processing techniques, improves the quality of student evaluations. For example, a chatbot can collect opinions via a dialog interface similarly to a real interviewer but with a small amount of work required by the user. Moreover, each conversation can be adapted according to the student’s personality and provided answers. A chatbot can even formulate the reasons for particular opinions.
Fourthly, to support teachers in their classroom work, one can put into use virtual facilitators. For instance, at the Georgia Institute of Technology on Knowledge-Based Artificial Intelligence (KBAI) class, students were introduced to a new teacher’s assistant named Jill Watson (JW) , who has been operating on the online discussion forums of different offerings of the KBAI class since Spring 2016. JW autonomously responded to student introductions, answered routine, frequently asked questions, and posted announcements on a weekly basis.
In the fifth place, Watts introduced chat campus based on the IBM Watson cognitive computing technologies . In brief, students at Deakin University have asked IBM Watson 1600 questions a week to learn the ins and outs of life on campus and studying in the cloud. Within 12 months of implementing Watson, due to the enhanced quality of the student know-how at Deakin, this ground-breaking solution has handled more than 55,000 questions from students. Furthermore, the school is progressing its use of Watson, broadening its capabilities and teaching the system to understand new sources of information. Personalized learning is the sixth example of AI applications in the education sector. In general, it refers to a variety of educational programs in which the pace of learning and the instructional approach are customized and eventually optimized for the needs of each learner [70]. In particular, the content is tailored to the learning preferences and specific interests of each student. The seventh example—one of the most promising—is adaptive learning (AL).While the traditional model of classroom education, continues to be very much one-size-fits-all, on the contrary, AI-powered AL systems are designed to optimize learning efficiency. For example, Yixue Squirrel AI (Yixue) collects and analyses students’ behavior data, updates learner profiles, then accordingly provides timely individualized feedback to each student
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