Machine learning in education may seem to be just another buzzword used to force entrepreneurs to dive into their pockets and innovate only for the sake of innovation. However, the truth is exactly the opposite. Companies who have previously used ML see it as a powerful tool that provides various major commercial benefits. What's more, it applies to both well-known businesses with large budgets and potential startups with minimal resources. In other words, every form of organization may benefit from this cutting-edge technology

Anastasiia Dyshkant

Content Marketing Manager


Machine learning in education may seem to be just another buzzword used to force entrepreneurs to dive into their pockets and innovate only for the sake of innovation. However, the truth is exactly the opposite. Companies who have previously used ML see it as a powerful tool that provides various major commercial benefits. What's more, it applies to both well-known businesses with large budgets and potential startups with minimal resources. In other words, every form of organization may benefit from this cutting-edge technology.

This article aims to provide you with a complete review of ML usage in current education so that you can make an educated choice about whether or not to implement machine learning into your company.

Modern Role of Machine Learning (ML) in Education

One of the primary advantages of machine learning in the education business is that it is accessible to almost everyone. People now live in a world that is full of problems, therefore they must be mobile and adaptable to changing circumstances. The modern role of machine learning in education cannot be overstated. Testing, targeted tutoring, and coaching are all ways to improve education and make it as modern as possible.

Here are some instances of Machine Learning in use in today's educational system.

Teacher Task Assistance

It's no secret that spending hours assisting students' work may be exhausting for educators. One of the benefits of machine learning in education is the automation of operations. Grammarly, for example, employs a blend of machine learning and human comprehension. It makes teaching easier and allows teachers more time for self-development. It can also relate to the benefits of machine learning in higher education.

Smarter Data

It is essential to keep students in control, especially in today's harsh society. Smarter data for school operations helps in determining if students are safe. It checks for risky terms on school-issued devices and notifies the administrator. Yes, it does require human attention, as different circumstances may arise.


This is most likely one of the most important advantages of machine learning in online education. A lot of firms currently give students learning, testing, and feedback, so it's not only about evaluation. This technology is extremely useful for students who need to fill knowledge gaps or learn something totally new.

Individualized Learning

Students now demand a more methodical approach, and Machine Learning makes things much easier. On the market, there are an increasing number of programs, games, and software that adapt to the particular needs of a student. As a result, we can see that the function of Machine Learning in education is extremely crucial, as the business is expanding and providing many possibilities. It is your responsibility to use and benefit from them.

Key Benefits of Machine Learning in Education

Improved E-learning through Feedback

Students have the option to provide comments in any online course developed by educators. Personal opinions on course excellence and material improvement may be quite beneficial in guiding student performance and activities. So, basically, AI and ML analyze the received feedback, learn from probable repeats, and quickly notify the educator. Isn't it an excellent technique to determine what works in your course and what doesn't?

Efficient Organization and Personalized Learning Experience

Any educational process may be personalized to each student's needs with the use of Artificial Intelligence (AI) and a cloud-based Learning management system (LMS). Teachers can assign activities to students and monitor their grasp of ideas, as well as test multiple learning methodologies to determine the one that produces the greatest learning results. The days of having one learning program that fit every student without exception are long gone. Students are unique individuals with varying learning views and rates. Thus, machine learning and artificial intelligence (AI) learn from data and aid in providing feedback to teachers. This enables instructors to establish better e-learning techniques for their pupils while also organizing them properly.

Predictions of future career paths

Machine learning in education aids in the analysis of students' performance and capacities. Furthermore, using algorithms, it is simple to determine the pupils' strengths and shortcomings. Consider a college student application and examine performance, instructor comments, and best results. In this manner, the learner will become aware of what he or she excels in and what does not. Thus, AI and ML will analyze student progress and recommend the most successful career route based on course completion. And that might be a beneficial insight for a future professional path.

Grading without bias and stereotyping

Teachers may practice assessing students based on their mood, personal preferences, biases, and non-common logic in schools. As a result, the usefulness of ML/AI lies in a machine's inability to be prejudiced and stereotype students. Students can receive a clear image of how they are progressing in their academics if there are no specific attitudes. In this case, ML and AI will not only evaluate all of the grade-related data, but will also recommend grades to students. If the teacher is not involved, this will increase student equality.

Digitalisation of  learning textbooks

Paperback textbooks may be transformed into online sources such as digital books, videos, forums, and scientific papers using AI and ML. Furthermore, the algorithm may return identical results based on the topic you're researching or the stuff you're looking for. It is quite useful when there are several sources and ML/AI provides a list of the most particular ones you want. This benefit is especially useful in e-learning contexts, where the teacher just assigns the work and the student is responsible for conducting the research.

Advanced analytics

Because current IT systems can do practically any type of analysis possible, machine learning and education are a marriage made in heaven. We've already discussed how ML can analyze content to give students with adaptive learning. However, this is merely one of many methods to benefit from ML's analytical power.

Other methods include the following:

  • Reports of all types (attendance, academic achievement, engagement, certification monitoring, trainer/teacher approval, and so on).

  • Measuring both the quality and quantity of available educational materials

  • Analyzing input data (the number of logins, the amount of time spent on the platform, the students' backgrounds, emails, requests, and so on).

  • Visualizing the information flow to identify current challenges and sources of misunderstanding

Is it possible to provide analytics without including ML? Yes, but the outcome will be less effective and beneficial.

Improved user experience

If there is one thing machines do consistently better than humans, it is the completion of mundane jobs. People get fatigued and distracted. As a result, errors are almost unavoidable.

The educational business is no different. Teachers and staff are required to deal with scheduling, attendance monitoring, assignment collection, and a variety of other time-consuming tasks. ML relieves consumers of this burden and saves them time. Finally, the everyday grind is eased, and the consumers are satisfied.

ML in education is essentially the "magic tool" that removes the majority of the challenges and leaves the audience with the pleasant part. Users connect with technology in the most comfortable way possible, delivering a pleasant user experience at all phases.

This asset is so powerful that 57% of companies use ML and AI specifically to improve the customer experience.

Examples of Machine Learning in Education 

What better approach to show the effectiveness of machine learning in education than to share real-world success stories? We've compiled a list of firms who gambled on machine learning and won big.

Every solution on this list uses ML in a unique way. Even though all of the firms are in the EdTech industry, they are not direct rivals because each has developed its own market niche and target audience.


Grammarly is one of the world's most popular online grammar checkers. This program not only examines your spelling, grammar, and punctuation, but it also checks for plagiarism and assists with overall style and delivery. It's one of the key reasons why the tool is popular not just with students but also with professionals who deal with words.

Grammarly's ML algorithms are always being enhanced as the system takes into account all of the users' behaviors. For example, if the general public regards the automatic advice as incorrect and ignores it, the algorithm will learn and correct itself.

The tool's reasonable accuracy is made possible by a combination of machine learning, natural language processing, and deep learning. As a result, clients receive a helpful virtual assistant who instantly corrects writing errors and is available across several devices (web, mobile).


In comparison to the preceding example, SchooLinks applies machine learning to education in a broader sense. A college and job preparedness platform assists students in properly planning their educational journey and selecting the best professional route based on their preferences, talents, and potential.

The platform analyzes all student-related data in order to give the customer any support that is necessary. SchooLinks, for example, can assist with the following:

  • financial aid calculation

  • determining personality profile

  • college selection

  • part-time job and internship search

  • building a student’s portfolio

  • course planning

  • event scheduling

In this case, ML algorithms handle personalisation by reacting to the student's performance, requests, behavior, and choices.


A well-known worldwide learning platform employs ML algorithms to give students a cutting-edge learning assistant that controls the individual educational journey and assists in overcoming numerous problems that arise along the way.

Quizlet's learning assistant, for example, handles:

  • Building individual study plans

  • Comprehensive progress tracking

  • Smart grading

  • Targeted study sessions

The technology is also continually improving itself because the students' responses are anonymized and used to train the current ML models.

Quizlet is incredibly popular due to its blend of gamification, machine learning, and all of the benefits of adaptive learning. The platform appeals to both young and old people who are prepared to link education with enjoyment.


MobyMax, an award-winning edtech solution, is noted for its creative use of AI and ML in education. The platform earned a reputation for itself by providing schools with a comprehensive adaptable K-8 curriculum as well as a plethora of ML-powered tools to address learning gaps, enhance student engagement, and give teachers with a collection of formative and summative evaluations.

MobyMax distinguishes itself from the competition by developing a multipurpose educational all-in-one hub with four distinct solutions:

  • Real Rewards

  • Differentiated Learning

  • Interactive Class

  • Quick Checker

With thousands of clients and hundreds of awards, MobyMax has established itself as an industry leader because of its well-thought-out strategy.

Final Words

In 2023, machine learning in education gains traction and will completely flourish in the future years. You don't have to be a prophet to see that algorithms will get sharper, faster, and more sophisticated. The potential of machine learning will open up new vistas for EdTech, pushing away traditional teaching approaches and practices.

Of course, this does not imply that every entrepreneur with a business connected to education should invest thousands of dollars on machine learning. It's hardly a miracle cure. However, in many circumstances, machine learning may be highly successful and should not be underestimated.

If you already have an idea and want to apply ML technology into your existing business model/startup, or if you're simply intrigued about the concept, don't hesitate to contact PioGroup software and request a free estimate or consultation. Our professionals would gladly assist you!


Anastasiia Dyshkant

Content Marketing Manager

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