5 Major Benefits of Machine Learning in Education

Machine Learning for Education: Why It’s Important 

Although Machine Learning uses are becoming extremely common across many industries, their impact on education is especially important, as these technologies align with  UNESCO’s goal of “quality education and lifelong learning opportunities for all by 2030,” contributing to the sustainable development of youngsters worldwide. So, what is ML in education?

ML innovations reduce costs and allow personalized learning and offer numerous benefits for remote areas and regions with low educational standards. With ML, both teachers and students can stay updated with the latest developments and research – not relying on outdated paper materials or facing shortages of human resources. 

Moreover, ML gives opportunities for learners with special needs, ensuring true inclusivity and equal access to education for everyone. Given these benefits, the market for ML in education is growing quickly and is expected to reach $55.3 billion by 2032.

Now, let’s move beyond theory and explore real-world examples of how ML is benefiting the education sector.

How is Machine Learning Used in Education?

Now people are living in a world where there are a lot of challenges, so they have to be mobile and flexible according to different circumstances. As we’ve mentioned before, one of the main benefits of ML in the education industry is that it is available basically for everyone. 

What does ML stand for in education today? The modern role of ML in education is hard to underestimate. Testing, individualized tutoring, coaching – everything works for improving education and making it as modernized as possible. Here are a few examples of Machine Learning usage in the modern education system.

Teacher Task Assistance

It’s not a secret that it’s quite draining for teachers to spend hours assisting students in work. One of the advantages of ML in education is the automatization of the processes. The programs such as Grammarly use a combination of ML and human understanding. It eases the task for teachers and gives them time for self-development. It also can refer to the advantages of ML in higher education. Overall, ML can assist teachers by:

• grading assignments and quizzes
• generating detailed feedback on students’ work
• handling routine tasks such as tracking attendance 
• organizing lesson plans based on curriculum standards
• sending updates and reminders about assignments

Smarter Data

It’s quite important to keep students in check, especially in today’s world full of threats. Smarter data for school operations helps monitor if students are in safety. It scans concerning keywords on school-issued devices and alerts the administrator. Sure, it also involves human consideration, as there can be different cases. That’s how ML can help with data analysis:

• monitor school-issued devices for concerning behaviors
• alert administrators about potential safety issues
• analyze patterns to find risks
• support decision-making with data insights
• improve security response protocols

Testing

This is probably one of the most essential benefits of ML in online education. A lot of companies nowadays provide learning, testing, and feedback to students, so it’s not just about assessment. This technology is quite helpful if a student needs to fill the gaps in knowledge or learn something completely new. ML can help with:

• providing feedback on student performance
• identifying areas where students need support
• offering learning resources to address gaps
• adapting testing methods to match learning styles
• tracking progress over time

Individualized Learning

Now students require a more deliberate approach, and Machine Learning is what makes things a lot easier. On the market, there appear more and more programs, games, and software that are adapting to the individual requirements of a student. That’s how ML can support individualized learning:

• customize content to fit each student’s learning style
• adapting programs and games based on individual progress
• make real-time adjustments to materials
• create a more engaging learning experience

Start your EdTech project with Inoxoft! Contact us.

5 Key Benefits of Machine Learning in Education

Machine learning doesn’t take the place of teachers; rather, it’s a supportive tool that offers valuable data to help educators customize learning for each student. Let’s explore some of the most significant advantages of ML in education:

Improved E-learning Through Feedback

In any online course created by educators, students can leave their feedback. Personal opinions on course excellence and material enhancement can be really helpful in managing student performance and activity. 

So, basically, AI and ML interpret the received feedback, learn about possible repetitions, and notify the educator immediately. Isn’t it a perfect way to know what works in your course and what isn’t working the way it should?

Efficient Organization and Personalized Learning Experience

With the help of Artificial Intelligence (AI) and a cloud-based Learning Management System (LMS), any educational process can be personalized to every student’s need. Teachers can give students tasks and monitor their understanding of concepts, test different learning approaches, and find one with the best possible learning results. 

The times when one learning curriculum suited every student without exception have long gone. Students are individuals with different learning perceptions and paces. Thus, ML and AI learn from the data and help in giving feedback to teachers. This allows educators to set up better e-learning practices for their students as well as organize them logically.

Predictions of Future Career Paths

Applying machine learning in education helps in analyzing students’ performance and capabilities. To add, with the help of algorithms, it is easy to understand what are the student’s strengths and weaknesses. For example, let’s take a college student application and analyze performance, teacher feedback, and best results. 

This way, the student will become aware of what he’s/she’s great at and what’s not. Thus, AI and ML will process student progress and suggest the most effective career path based on the level of subject completion. And, that might be a successful insight for a future career choice.

Grading Without Bias and Stereotyping

Sometimes, at schools, teachers may unintentionally allow personal factors like mood, preferences, or biases to influence their grading. For this reason, the benefit of ML/AI is in the inability of a machine to be biased and stereotype students. 

With no specific attitudes, students can get a clear picture of how they are proceeding in their studies. Here, ML and AI will not just process all the grade-related data but also suggest grades for students. If the teacher isn’t going to be involved, this will add to student equality.

Digitizing Learning Textbooks

With the help of AI and ML, paperback textbooks can be transformed into online sources like digital books, videos, forums, and scientific articles. What’s more, the algorithm may show you similar results based on the topic you’re studying or the material you are trying to find.

It is quite handy when there are numerous sources and ML/AI gives you the list of the most specific ones you need. This benefit is especially convenient in e-learning environments, where the teacher gives only the task and the research falls on the student’s shoulders.

Unlock the benefits of ML for your business! Reach out to us and learn more.

Machine Learning Use Cases in Education

Now that you understand the benefits and ML’s meaning in education, let’s explore some real-world examples of ML-powered EdTech software that educational institutions are already using.

Adaptive Learning

We’ve learned that ML predictive analytics can customize learning experiences to meet each student’s unique needs. Several eLearning platforms use this technology and track learning factors (exercise completion time, time spent on the platform, logins, and test scores) to assess student performance, engagement, and learning patterns, and even predict future learning results.

For example, the MobyMax platform uses ML to adjust learning activities in real time and help students plan personalized study programs. These tools also offer educational programs for students with specific needs, such as those with autism.

Instant Translation

Language barriers? No problem. Real-time translation, powered by Natural Language Processing (NLP), makes educational content more accessible than ever. Neural machines can provide affordable, high-quality real-time translation and localization for accurate and natural-sounding learning materials.

Tools like Microsoft Azure Translator and Presentation Translator can translate video lessons, papers, and other types of eLearning content in just a matter of seconds for more comfortable and better learning.

Inclusive Education

ML and AI solutions are making inclusive education a reality, making sure that everyone, regardless of their background or abilities, has a fair shot at learning. Whether students have different learning styles, disabilities, or come from diverse backgrounds, ML helps create an educational environment where everyone can thrive.

Voiceitt is one tool leading the charge. It uses ML to understand and translate speech from people with speech disabilities into clear text, making communication easier, so these students can fully participate in class.

Detecting Students at Risk

Every reputable educational organization wants students to succeed. Many now turn to ML to spot students who may be at risk of dropping out, allowing them to take action before it’s too late. ML handles this complex task by analyzing academic records, attendance, behavior, background, and demographic details. This data helps teachers identify struggling students and step in at the right moment.

One example comes from Illinois, where the State Board of Education has developed an early warning system for high school students. This system uses ML not only to flag students at risk but also to offer teachers practical advice on how to help them get back on track.

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Machine Learning Applications in Education

After learning about the benefits and use cases, you’re probably wondering what ML use is best for your business and what solutions you can create to unlock even more opportunities. Here are some examples.

Intelligent Tutoring Systems

Intelligent tutoring systems, powered by ML, can guide students through complex subjects, offer tailored explanations, feedback, and support, adapt to each student’s learning pace, and help them overcome challenges, boosting their confidence along the way.

For educators, intelligent tutoring systems make a scalable solution to offer personalized education without a 1:1 teacher-to-student ratio, leading to better retention rates and academic performance, which improve the institution’s reputation to attract prospective students and investors. According to statistics, by 2030, 50% of colleges will offer personalized AI tutors to students.

Grading and Assessment Tools

Say goodbye to endless hours spent grading! ML grading tools can automatically evaluate assignments, quizzes, and tests, delivering instant and accurate feedback. This not only saves educators time but also provides students with the immediate feedback they need to improve their work.

Using AI-powered grading tools, schools, universities, and educators can also reduce administrative burdens and operational costs. Moreover, with the help of AI, institutions can allocate more time to curriculum development, leading to a richer educational experience.

Language Learning Applications

Learning a new language can become a truly enjoyable experience with AI-driven language learning apps. These applications are getting increasingly popular, with the market projected to reach $16.63 billion in 2031. AI apps adjust lessons to the user’s skill level, focusing on areas where a student needs improvement. Through interactive exercises, speech recognition, and real-time feedback, users can master new languages faster and with greater confidence.

For businesses, investing in ML-driven learning apps can mean faster employee training and improved communication in a corporate environment. At the same time, educational institutions can attract more students with a modern language learning solution that outperforms traditional methods.

Personalized Content Creation Tools

Creating educational content that resonates with every student is challenging, but technology can help simplify the process. Tools that personalize content based on student data can generate materials that match individual needs and interests. This approach keeps students engaged and makes learning more relevant and enjoyable.

When institutions use personalized content creation tools, they can offer more targeted educational materials, which improves student satisfaction. This level of customization not only boosts learning outcomes but also helps institutions stand out in a competitive market.

Adaptive Learning Platforms

Education is not one-size-fits-all, and adaptive learning platforms embrace this reality – especially in North America, where the market for adaptive learning is growing day by day. These platforms use ML to assess student performance and tailor lessons in real time. Whether a student needs more challenging material or additional support, the platform adjusts to their needs.

For institutions, adaptive learning platforms provide a way to accommodate diverse learning styles and paces, leading to more efficient use of teaching resources.

Gamified Learning Solutions

Research shows that 90% of people believe gamified learning is more effective than traditional methods. Why is that? With game elements like points, badges, and leaderboards, these ML solutions motivate students to stay engaged and compete with themselves and others. Gamification taps into students’ natural desire for achievement and rewards, making the learning process more interactive and enjoyable.

For organizations and schools, investing in these solutions can result in higher completion rates for training programs and a more positive perception of their educational offerings.

How We Can Help You to Apply ML for Your Educational Project

If you are interested in starting an educational project, Inoxoft will be happy to become your reliable partner for EdTech software development. We build diverse products, with ML and AI being the core of our expertise, including:

• AI/ML-powered applications
• Learning management systems
• AI chatbots and tutors
• Generative AI solutions
• School management systems

and more!

We also provide free consultation, if you’re generally interested in ML in EdTech and AI in web development. Contact us and begin your journey with us!

Case Study: Developing a Career Mapping Platform 

Our client, an entrepreneur from the USA, believes that matching people’s skills with the right jobs is a key to career satisfaction. She wanted to create a solution that would help people find work they enjoy and succeed in.

Recognizing our deep expertise in AI and extensive experience in the EdTech sector, she approached us for cooperation. After discussing goals and expected results, together we developed a web platform and a mobile app that use Machine Learning and Data Modeling capabilities. Our solution gathers real-time data to match job seekers with careers that fit them best. 

The ML model analyzes career data and personal information to suggest potential career options, ranking them from best to least suitable. It also predicts career paths, identifies the skills needed, and provides expert advice through video chat.

As a result of this wonderful cooperation, our client now benefits from a solution that’s attracting more users who want to find a new way to explore and navigate their careers. The same can be done for the educational sector to evaluate students’ strong and weak points. 

Conclusion

Machine Learning and education go hand in hand. ML algorithms can help schools and educational institutions simplify administrative work and make learning more enjoyable for students. 

However, many organizations still stick to traditional methods and are slow to adopt new technologies. This gives you a significant opportunity—by using machine learning, you can set yourself apart from those who don’t want to change! So, if you’ve been thinking about integrating ML into your organization, now is the time to act.

We at Inoxoft have over 10 years of experience in custom software development and can handle projects of any size or complexity. We focus on our clients’ needs, creating solutions that fit your specific goals, and bringing you desired results. In the past decade, we’ve completed more than 230 projects, helping companies achieve digital success.

We can help you too—just reach out and tell us about your project.