5 main applications of AI in education

Irina Kolesnikova
July 31st, 2022

The concept of different use cases of AI in education

Educational leaders, thinking of efficiency growth, may find that artificial intelligence (AI) could provide a personalized approach, and happier students, thus gaining more traction and better results. The pandemic proved that idea right and brought AI in education as well as in many other fields to bloom.

As everything was remote, it appeared that although teachers’ presence was vital, technology would change how they do their jobs for the better. AI in education is not just enhancing the teachers’ jobs but also revolutionizing the way students learn. But don’t picture yourself in the rise of the machines: AI systems usually take care of the repetitive and time-consuming tasks, leaving the most creative (and complex) challenges for humans.

1. Personalized learning

Personalized learning, tailored for specific students’ interests, abilities, knowledge levels, and talents, provides deeper involvement. Thus helping students stay motivated and be more successful and empowering their voices and choices. That is why personalized learning and adaptive learning that leverages AI to provide individualized support and personalized learning experiences are among the biggest trends in education.

With artificial intelligence, students now have a personalized approach to learning programs based on their unique experiences and preferences, incorporating adaptive learning for a more tailored educational journey.

Moreover, students with special needs can get more with personalized AI-based recommendations. AI is giving them more attention than teachers can provide, which is a win-win scenario. AI’s capability to create adaptive learning paths ensures that personalized lesson plans and course recommendations are dynamically adjusted based on individual student progress, offering a truly customized learning experience.

Personalized use of AI is probably one of the most significant achievements in education as learning is more comfortable, smoother, and cut across personal knowledge.

An example of AI-driven personalized learning paths: the National Project of Estonia.

personalized education path

This project aims to implement AI-driven solutions to personalize learning paths by using their and other students’ data points created throughout their studies.

AI can adapt to each student’s level of knowledge, preferred style of learning, speed of learning, and desired goals, so they’re getting the most out of their education.

Moreover, AI-powered solutions can analyze students’ previous learning backgrounds, identify weaknesses, and offer courses best suited for improvement, providing many opportunities for a personalized learning experience.

Teaching the teacher

Just as AI can plan students’ lessons and personalize their learning courses, it can also recommend improvements to teachers’ plans. Through this, teachers can expand their view on their subject using the best material from other tutors without additional effort. In addition, each educator can also contribute with their best materials and provide unique expert knowledge to the network to help students understand the subject better.

For course updates or development, artificial intelligence can provide teachers with a detailed picture of subjects and learning materials to be reviewed. Thus, teachers and professors can improve their courses to address the most common knowledge gaps or challenge areas before someone falls too far behind.

Identify classroom weakness

As already mentioned, AI in education is not meant to replace teachers. Instead, it’s meant to add some superpowers.

Artificial intelligence can assist the teacher’s work in a classroom to identify some weaknesses or gaps. For example, artificial intelligence can detect when some students miss specific questions or topics. The teachers will be notified; thus, they will know which of their students need explanations and the subject of such explanations and can give them in a more personalized manner.

Such predictive systems, also known as early warning systems, can identify if and when students are in danger of not reaching their goals. For that, nearly 50% of the public high schools in the US and 90 percent of colleges use an early warning system to track student grades, attendance, and other factors. Moreover, these AI systems are reliable as they use precise performance data — such as attendance — to predict students’ progress in studies, allowing teachers to intervene early.

Finally, there are voice-based AI solutions or, in other words, speech recognition algorithms. For example, these systems are the backbone of tools such as Siri or Alexa. Those algorithms have recently been explored as ways to diagnose reading issues. Besides, NLP technologies can also grade student reading scores more accurately than traditional formulas do, such as the Flesch-Kincaid Grade Level test.

2. Task automation in education

The Telegraph survey claims that teachers spend up to 31% of their time planning lessons, grading tests, and doing administrative work. These iterative tasks could be delegated to artificial intelligence: using supportive automation tools, teachers can streamline manual processes, receive more time for personalized focus, and use AI-recommended materials to learn the core competencies.

Administrative and organizational tasks automation

AI in the education sector can ease the professors and teachers‘ most common duties, which are managing the classroom environment as well as numerous organizational and administrative tasks, such as filling out the necessary paperwork, making a student progress report, and organizing resources and materials for lectures, etc. If done manually, they require much work.

Luckily, the processes can be automated or at least semi-automated using natural language processing solutions. Artificial intelligence, in those cases, could go through the fields of a report, partially or fully prefilling them. As artificial intelligence automates those tedious tasks, it provides the teachers with the possibility to spend more time with each student.

Automated test grading and homework evaluating

Old news: an educator spends considerable time grading homework and tests. New world: AI steps in and speeds up the grading process.

Although machines can already grade multiple-choice tests, they are also ready to assess free text written responses. For instance, they are drawing the teacher’s attention to specific places of an essay while at the same time offering recommendations for how to close the gaps in learning. There is much potential for AI to create more efficient enrollment and admissions processes.

For example, admission offices of higher education institutions applying artificial intelligence can reduce biases in testing systems and provide educational institutions with diversity. Moreover, with AI systems, the admissions process can become faster and more personalized. Colleges and universities using artificial intelligence for administrative activities can provide customizable experiences for students during the admissions process, including visa processing, student housing selection, and course registration.

One subfield revolves around the technology already mentioned above: natural language processing. This technology is capable of processing and grading written essays. For example, students can use spell-checking or plagiarism detection apps to improve their writing before it is submitted for the assessment.

Usually, those apps provide actionable advice on how to improve the text. Moreover, artificial intelligence can not only look for the exact word-to-word content but also can assist you in finding content that is paraphrased or re-worded or lacks the arguments to cover your point of view. Popular online educational platforms allowing unlimited participation, such as Coursera and Udacity, have also integrated AI scoring to analyze essays within their courses, thus improving student performance.

plagiarism scan report example
A vision-based artificial intelligence called AI image recognition is also an important field that can help with assessment. For example, instead of an educator manually grading a math equation a student wrote, the student can snap a picture of the equation and send it to the teacher. Or the teacher could do the same snap and then let a machine grade it.

AI for education - computer vision for tests
Source: GradeCam blog

3. Smart content creation

AI in education can assist with the content that will make teaching and learning more comfortable. Starting with question-answer pairs that could be used for texting or training, and ending with complex study environments.

Example: Duolingo

AI in educations: Smart content creation

Digital lessons

AI can analyze a big topic and then divide it into smaller, easy-to-grasp parts; make study guides or digital textbooks from those pieces, all within the framework of digital learning. Exercises as a part of these digital lessons could also be produced with the help of AI: computer vision can be used to take the necessary parts from learning materials, and natural language processing algorithms afterward can be trained to create different types of learning materials: fill-the-gap questions, flashcards with definitions, multiple and single choice questions.

Information visualization

To perceive information, students can lean on AI-powered simulations, visualizations, and study environments. Moreover, those educational environments are integrated with AI-based stealth assessment. It means that the process of assessments is integrated seamlessly into the environment so that the student is unaware of being assessed.

4. 24/7 educational and administrative assistance

It is usual for students to look for extra help after class hours. However, teachers don’t have the time for all their students.

AI in education: algebra chatbot

If you haven’t met the “teen and algebra” situation yet, you could ask any parents who have struggled with that. Probably, they will be the most excited about the potential of AI to support their children when they are fighting algebra home tasks.

For example, a virtual learning assistant or a chatbot could help. Although chatbots cannot replace human educators, AI tools can still provide feedback on students’ tasks, thus improving their skills during after-school instruction.

It can be a personalized one-on-one learning experience with the answers to urgent or not-so-clear questions at all hours of the day. At the same time, an educator can spend precious time on other tasks.

AI-powered chatbots can swiftly assist student learning by providing answers to their most frequently asked questions. Conversational artificial intelligence (the one that mimics human interaction) can bring a win-win result: time-saving for tutors answering questions, as well as for students reducing a waiting time for a response to their questions or searching the answer through the learning materials.

Several AI-powered chatbots were specifically built for the education sector. They support students round the clock by answering their queries, and thanks to machine learning getting more and more effective over time. In addition, chatbots provide accessibility for all students, anytime and anywhere, allowing each student to learn at their own pace, providing focused, result-oriented and personalized learning.

5. Inclusive and universal access to education

AI in education opens up new possibilities for students who need to learn at different levels, who want to learn a subject unavailable in their school, or who are unable to attend school.

Moreover, educational classrooms can become globally available to all students through AI tools, even to those who have visual or hearing impairments or speak different languages. For example, with a PowerPoint plugin such as Presentation Translator, students have real-time subtitles for everything the lector says.

Accessibility checkers help educators increase access for low-vision students. Artificial intelligence and computer vision machine learning can define what is in an image and generate a caption. Then, using natural language generation, the technology allows machines to speak human language, describing the picture. Such machine learning technology saves much time with auto-captioning on images, as well as being much more likely to make the content accessible.


The impact of AI on the education market is profound, revolutionizing education and driving significant financial growth.

Well-designed artificial intelligence in education allows both teachers and students to take advantage of the technology that can facilitate and raise the quality of educational processes. Artificial intelligence in education can provide a wide variety of ways to use this technology, creating engaging tools, such as intelligent tutoring, stealth assessments, games, and even virtual reality. All these AI-powered tools can help tutors to guide students to better knowledge and academic results, developing their critical thinking skills.

However, the basis of the educational system is always good teaching and human interactions: AI-powered education tools and bots provide (and will hopefully increase the helping capacities) support with routine and repetitive tasks, letting teachers spend their time on creative and more important things.

ai plan execution

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