Potential Use Cases of AI in the Education Sector

Potential use cases of AI in the education sector are already changing the face of education

Potential use cases of AI in the education sector are already changing the face of education and might be utilized to assist students in studying come with opportunities. It is also feasible that can be modified for each learner. Artificial intelligence technologies are altering education as they become more prominent in everyday life.

Potential Use Cases of AI in the Education Sector:  

Differentiated Instruction: An AI system can monitor how a student completes a task, how long it takes, and whether or not they are successful. If the learner is having difficulty, the system can assist; if the student is succeeding, the system can provide tougher problems to keep the activity interesting. This sort of real-time feedback is frequently challenging to provide for a single student, let alone an entire class or university. AI adaptive learning systems have been proven to make adjustments to the learning environment, information, and challenges swiftly and dynamically to help learners learn more and progress faster. The system can comprehend mathematical rules and adjust its approach to challenges it has never faced before by following directions from a human supervisor. The system can also identify regions where it had to make numerous attempts before getting at the proper answer, mark those for teachers as spots where human students may become confused, and highlight strategies the system utilized to arrive at the correct answer more quickly.

Intelligent Textbooks: Stanford researchers have been constructing and testing a prototype of an intelligent textbook, dubbed Inquire. It is an iPad software that tracks students' focus and attention while they read by seeing how they interact with the app. The interactive text provides explanations of essential terms that students may access by touch or mouse, as well as the ability to mark and annotate while reading. The textbook can also propose questions regarding the subject and ideas for further investigation that is tailored to each student. It may modify the text's reading level and include additional photographs, videos, and resources to assist pupils to grasp what they're studying.

Improved Assessment: educational assessment is concerned with how an instructor determines whether or not a pupil is learning what is being taught. Traditional evaluation essays, multiple-choice examinations, and short-answer questions haven't altered much in a century. Artificial intelligence can change this by discovering patterns in learning that individual instructors or administrators may not see. Reach Every Reader, another assessment initiative led by the Harvard Graduate School of Education, MIT, and Florida State University, develops educational games for parents to engage with their children while teaching them to read. In some of the games, adults and children take on the roles of characters from real-life circumstances. These games can assist parents and teachers in determining if their children are reading at the right grade level and getting them back on track if they are not.

Personalized Learning: When students' interests and goals dictate learning, this is referred to as personalized learning. The instructor serves as a facilitator, while the student determines the what, why, and how of learning. Individualized education customized to each student's specific interests is possible using artificial intelligence systems. AI adaptive learning systems may detect when a learner is failing and then give more or alternative support to assist them in succeeding. As the student demonstrates mastery of the topic or skill, the AI tool assigns progressively tougher activities and resources to further push the learner.