10 Real-World Machine Learning Solutions Transforming Education

‍What is Machine Learning?

Machine learning refers to a group of tools and techniques that enable computers to learn and adapt without explicit programming. It involves using algorithms to assist development of modern EdTech solutions for intended tasks. 

By analyzing sample inputs, the machine-learning algorithm can predict and execute tasks exclusively based on the learned pattern and not upon a preset programming instruction. Machine learning can be a saver in many situations where strict algorithms are not an option. It can learn the method from patterns previously used and apply the learnings.

One machine-learning application we have encountered is how our email providers help us deal with spam. Spam filters employ an algorithm to identify and remove junk emails from your junk mail folder. Several e-commerce firms also utilize machine learning algorithms and various other IT security devices to avoid fraud and increase the performance of their recommendation engines.

While the world of technology keeps evolving, the field of education is also changing. The advancement of machine learning has lifted the educational industry to new heights. Every institution strives to produce students who are ready for the modern world. 

Benefits of Machine Learning in the Education Sector

Machine learning doesn't replace teachers; instead, it serves as a powerful tool that equips educators with valuable data to create tailored learning plans that integrate gamification, diverse learning strategies, and analytics-driven decisions, ensuring that every child's unique needs are met.

Below are the most significant benefits of machine learning for education.

1. Precise Assessment

Educational experts often report an unbalanced grading system in educational institutions. Teachers might consider factors not relevant to students' learning. Artificial intelligence services for the EdTech industry help institutions and schools develop a more accurate assessment system and tool. 

For instance, approximately 60 thousand schools in Australia have been testing an automatic essay scoring system to reduce teachers’ workload and rapidly evaluate essays on multiple parameters like structure, style, and content. 

2. High Customization

Machine learning helps in creating customized learning experiences for the students to meet their different learning style and the rate at which they learn. With ML solutions like content recommendations, and adaptive learning systems, teachers can fine-tune their courses according to the weaknesses and strengths of each student. These systems can dynamically adjust the content and difficulty level to improve the student’s learning and performance. 

They also offer feedback based on their performance or recommend content to help them understand concepts better. With this level of customization, educational institutions can customize courses and teachings for students coming from diverse backgrounds and learning abilities. 

3. Personalized Feedback for Learners 

It is difficult for teachers to assess each student’s performance, answer their queries, and give them personalized feedback, especially in classes with a high number of students. Machine learning, however, can solve the problem. 

It can provide real-time feedback to the students during online tests and assessments, helping them understand their mistakes and correct them on the spot. 

Through adaptive feedback mechanisms, ML solutions can provide improved feedback on learners’ performance. They can even offer customized feedback based on the learner's style. For example, students who learn faster from visuals than text-based can receive graphical feedback while analytical learners can get subjective feedback. 

4. Predictive Analytics

ML can benefit education by predicting students' behavior, level of engagement, and emotional state, and help teachers provide custom support to everyone. For example, it is possible to determine the student's intent to leave the class, the cause of the student's lack of motivation, or the student's desire to take an additional course.

5. Better User Experience

AI can more efficiently accomplish monotonous tasks than humans. Scheduling, monitoring attendance, and managing assignments are all part of the work at schools and universities. Machine learning solutions can save their time and energy on such mundane tasks. 

For example, a student management platform can automate administrative tasks such as managing student enrollment, attendance tracking, and report generation. It also streamlines student onboarding by providing virtual tours and guidance on school resources and staff. All this automation not only boosts student management but also reduces the administration's workload so that it can focus on important tasks. 

6. Large Audience and High Level of Inclusion

Online learning platforms cater to millions of people worldwide and offer a variety of classes. Machine Learning (ML) significantly improves accessibility and diversity by offering sophisticated features like translation and transliteration in real-time. These features make educational materials accessible to diverse audiences, even those who are not native speakers, without the need for expensive consultants.

Furthermore, ML makes learning more accessible by providing information in various formats, including audio, video texts, and interactive presentations. The variety of formats allows disabled students to participate in learning actively. If you are a business or institution looking to develop online learning platforms for a global audience, partnering with an ML software development company having experience in the education sector will ensure accessibility and implementation of all desired features.

7. Automating Administrative Tasks

One of the main advantages that machine learning can bring to education is the ability to automate routine administrative tasks. ML can handle tasks like sharing course guidelines, making lessons, and educational materials, and handling huge amounts of paperwork. Automation is not only time-saving but also lets educators concentrate on the most important things: providing quality instruction and interacting in direct contact with the students. 

8. Predicting Career Paths for Students

Machine learning tools can offer useful insight into the capabilities and weak points, allowing them to identify potential career paths. By analyzing student performance, teacher feedback, and other pertinent data, the ML algorithms can identify the most suitable career and academic trajectories for students. For instance, ML can assess students' performance and suggest areas where they excel by providing a personalized learning experience. Through this, educational platforms can direct students to their desired career path, providing them with an understanding of their goals and future possibilities.

9. Bias-Free Grading and Evaluation

Contrary to human teachers who can give bias grading due to differences in beliefs about the culture, AI systems ensure an impartial and fair assessment. Assessment tools that use ML assess students' performance solely on data, removing the influence of stereotypes and assumptions. 

This leads to a more objective evaluation process, giving students a real assessment of their academic performance. In addition, ML can suggest grades and provide insight into student performance without personal bias, thus promoting equality in the educational process.

10. Digitizing Textbooks and Learning Resources

Machine learning is changing the face of the traditional educational system by digitizing textbooks and transforming them into interactive learning resources, including videos, online forums, tutorials, and study guides. Digital transformation makes it much easier for students to access and engage with educational materials. 

The ML algorithms also offer students personalized results when researching or searching for information. This feature is particularly beneficial for online education, as students typically have to work on their own. Digitization of books, assisted by the most cutting-edge ML solutions, can enhance learning by making it more interactive and personal.

Examples of ML-Powered EdTech Solutions and Apps

There are numerous applications of machine learning in the realm of education. Examples of this include:

Grammarly

Grammarly is a grammar-checking and plagiarism detector tool used by more than 30 million daily users, including students and teachers. The platform is built on deep learning, machine learning, and natural language processing. It utilizes global data to enhance suggestions, get acquainted with the writing style, and detect common mistakes.

SchooLinks

Compared to Grammarly, SchooLinks uses machine learning to improve education in a broad sense. It is a college and job-ready platform that helps students organize their educational path and choose the best career path based on their needs, abilities, skills, and talents.

The platform examines the data of all students to provide the user with any assistance needed. SchooLinks, for instance, can help with the following issues:

• Calculation of financial aid to the students
• Determining student’s personality profile
• College selection
• Part-time jobs and search for internships
• Creating a portfolio for a student
• Course planning
• Event scheduling

ML algorithms handle personalization in this scenario by responding to the student's actions, behavior, and preferences.

MobyMax

MobyMax is known for its unique use of AI and ML to enhance education. It earned a name for its ability to provide schools with an extensive, flexible and adaptable K-8 curriculum and a variety of ML-powered programs to help address learning gaps, increase students' engagement, and provide teachers with a set of summative and formative evaluations.

MobyMax differentiates itself from competitors by constructing a multi-purpose, all-in-one hub with four distinct solutions:

• Real Rewards
• Differentiated Learning
• Interactive Class
• Quick Checker

With many clients and prizes, MobyMax has established itself as a market leader because of its well-thought-out strategies.

Duolingo

Duolingo makes learning new languages as easy as playing games. It has more than 500 million active users participating in language activities that include French, Spanish, Japanese, and many more. Utilizing machine learning and data, Duolingo has implemented adjustments to the course by considering the subtleties of different languages. The result is that Duolingo surpassed a $4 billion valuation and became one of the most downloaded applications in the world.

Riiid Labs

Using AI and machine learning technologies in education, Riiid Labs provides students with an "Exponential Learning Experience." The platform collects information by providing micro-interval tests and tracking students' behavior during tests. It then uses its AI tutor and AI coach to provide in-depth guidance and prompt reinforcement to ensure students remain engaged and retain knowledge throughout learning.

Osmo

Osmo blends physical and online worlds by allowing children to play virtual games using tangible games. The technology of Reflective AI is activated whenever children connect the Osmo Reflector to their tablets and allow the device to feel the physical pieces included with every game kit. Although Osmo sells individual products via its website store, the company has impressed teachers and now displays its products in over 30,000 classrooms.

Querium

If you find science and math among the more difficult subject areas, Querium has developed a digital learning platform. Students using Querium's platform can benefit from StepWise AI, which functions as a master tutor, is accessible 24/7, and offers instant feedback on the mistakes made and possible next steps that students can take. Instead of continuing on an uncorrected course, students can quickly identify and correct their mistakes.

Kidaptive

Organizations and teachers can monitor each student's progress using Kidaptive's Adaptive Learning Platform. Machine learning algorithms drive this cloud-based computing platform, which examines a variety of instructional materials to provide the complete image of the student's growth and personal preferences. In turn, teachers can determine each student's strengths and weaknesses and tailor their lessons' content to meet the individual's needs.

Thinkster Math

For kids who require assistance in math, Thinkster combines AI and machine learning tools and provides personalized math instruction. Students begin by taking an exam and then receiving a comprehensive report that reveals what they are good at and where they can improve. After that initial step, students work with a tutor who will design a custom curriculum. They also complete math worksheets online, which include tutorial videos.

Cognii

Cognii's AI-powered virtual assistant for learning provides virtual tutoring, rapid assessment of open-ended questions, and review and study tools. Machine learning is utilized to improve and personalize education and learning, which allows Cognii to play an important part in shaping the direction of learning. Cognii currently has more than $1 million in total funding.

Future of Machine Learning in the Education Sector

Online learning has revolutionized the educational sector and eliminated many challenges from conventional classroom-based education. It is the next stage in the development of education technology designed to enhance teaching and learning further.

The report from Verified Market Research indicates ML is a promising technology for the education market. The research shows that deep learning and NLP were estimated at $1.1 billion worldwide in 2020 and projected to increase by $21.52 billion by 2028.

Recent studies have predicted a major increase in the use of AI/ML in education, predicting an increase of $21.52 billion by 2028. Microsoft also reveals that the majority of 99.4% of surveyed teachers believe that AI/ML technology offers competitive advantages to their schools within the next few years, with 15% describing AI as well as machine-learning in education as a powerful technology.

Final Words

Machine learning is a fast-changing field of education, and its possibilities continue to expand. As the algorithms get smarter, more sophisticated, and more efficient, the traditional teaching method is evolving to provide a more customized and effective learning experience. ML has opened new opportunities for students, educators, and institutions in everything from predictive analytics to automating administrative activities. Educational businesses should invest in ML programming or AI product development, which could result in innovations that enhance students' engagement and performance.

Integrating these technologies requires careful preparation and coordination between tech experts and educators, but the benefits are evident. When we embrace ML today, schools can help shape their future learning environment and provide programs tailored to each student's needs, ultimately improving the educational experience for all students. The future is now, and it's the right time to harness the potential of machine learning in the education sector.