EdTech is transforming thanks to AI and machine learning

Introduction

A rapid transformation has been witnessed throughout the education landscape in recent years, thanks to cutting-edge technologies including Artificial Intelligence (AI) and Machine Learning (ML).

By 2025, 126 billion U.S. dollars is expected to be generated by the global AI software market.

As every other industry reaps the benefits of Artificial Intelligence and Machine Learning, the education industry is no different. Increasingly, machine learning and artificial intelligence are adding value to the education industry as never before. In the education industry, cutting-edge technologies are transforming the industry, and most market players are fully aware of how they are impacting the industry.

Artificial Intelligence: What is it?

Machines with artificial intelligence (AI) are capable of replicating intelligent human behaviors, such as analyzing and making decisions. Natural language processing (NLP), robotic process automation, and machine learning are just some of the applications backing up the AI market.

AI is everywhere in today’s digital landscape, from smart voice assistants on mobile devices to industrial robots to automated parking systems.

Let’s take a closer look at machine learning and its applications now that you understand what AI is.

Machine learning: what is it?

A learning system that evolves over time, Machine Learning is an extension of artificial intelligence in which systems can learn from experience without being programmed to perform a particular task. It is an extension of artificial intelligence. The use of machine learning in education is helping companies differentiate themselves from their competitors as they focus on leveraging new technology and exploring new possibilities.

Machine learning algorithms shall continue to shape education’s future for years to come with advancements in machine learning algorithms.

There are three types of machine learning models:

1. Managed

Using supervised machine learning algorithms, we can form decisions based on the knowledge we have already gathered. A system like email filtering, for example, detects unwanted emails automatically and puts them into spam folders based on the collected data.

2. Observed without supervision

In unsupervised classification, data are not formally classified or labeled prior to being used for training. This type of machine learning algorithm defines data based on their structures, features, and densities, among other attributes.

3. Unsupervised

A semi-supervised machine learning algorithm helps classify some of the unlabeled data with the help of labeled data in cases where some data can be labelled, but only part of it can be classified.

There are many applications of machine learning in the education industry as well, including predictive analysis and data mining. Machine learning is being used in many industries these days, from entertainment to e-Commerce.

In the field of education, AI and machine learning are becoming increasingly important

AI and machine learning have brought remarkable changes in the education landscape, from improved learning experiences for students to streamlined educational operations. There are multiple scenarios where machine learning has transformed the face of education.

The education sector can benefit greatly from the use of machine learning (for students and teachers). Those interested in learning how machine learning can be used in education should know that AI and artificial intelligence can be used in countless ways to improve the school administrator, staff, student, and parent experience while streamlining daily school operations.

Machine learning and artificial intelligence are showing their true potential in the edtech sector, so in case you were wondering what machine learning can do for education, here are some answers!

Artificial intelligence and machine learning are used in edtech in the following ways:

1. Predictive Analysis in a Step

Students’ futures were once based on favoritistic opinions of “old school” teachers. As a consequence, young minds felt that they were a little less than others. Predictive analysis replaces favoritism with “proof-eccentric” data in this case. By analyzing both the past and the present data to make predictions about future outcomes, predictive analysis is taking advantage of machine learning in education.

A predictive analytics technique is a combination of data mining, predictive modeling, and machine learning techniques used to predict future events with current and historical data.

In this way, teachers can pay attention to students who have a higher chance of dropping out or scoring lower in the future. This helps all players in the education industry understand where their power lies and how to maximize it.

Specifically, predictive analysis enables educational institutions to use their existing knowledge and combine it with new knowledge, allowing them to create proactive strategies for the betterment of their students.

By using IBM SPSS predictive analysis software, Hamilton County managed to maintain their students on track, leading to a 10% increase in graduation rates.

In addition to helping with:

• Retaining students effectively
• Views of students’ 360-degree profiles
• Enrollment management system overhaul
• Scores and performance of students can be improved

2. There is no such thing as a distant dream when it comes to process efficiency

Gone are the days when teachers had to maintain separate logs for their students and instead could focus on imparting their knowledge to the masses. Educators need a system that takes care of all the work for them so they can concentrate on a bigger cause, i.e., imparting their knowledge to the masses.

One of the major benefits of machine learning in education has been the systematic organization of content and management of teachers’ daily curriculum.

There is no doubt that teachers teach well, and the results of students show incredible improvements as a result.

In education, machine learning also plays an important role in bridging the gap between students and teachers. By using an automated system based on the routine schedules of both students and teachers, a student doesn’t need to be late for appointments.

The Netex Learning web platform, powered by machine learning, lets tutors create curriculum on a daily basis. It’s even better that teachers are already able to design teaching plans around videos, audio, personalized assignments, and discussion portals that already include video, audio, and personalized assignments.

Machine learning in education produces the following results:

• Efforts to reduce the administrative burden
• Facilitates student and teacher focus
• Introduces interactive learning methods that are exciting and engaging

3. Smart tutors revolutionize learning

Machine learning technology brings a new sense of practicality and real-world implications to traditional lectures. There has always been room for improvement, and that is exactly what machine learning does.

Video tutorials, flashcards, smart guides, educational apps, and regular assessment quizzes are now becoming the staples of the smart tutoring movement, transforming lectures into video tutorials, flashcards, smart guides, and educational apps.

A major advantage of this system is that students and teachers have 24/7 access to virtual educational resources. A second form of the smart tutor system is virtual tutoring. This is a great way for your institution to be labeled as a true “edtech” company that embraces machine learning.

Using robots, Singaporean kids can read stories, solve simple math problems, and develop in a much more positive way with the help of virtual teachers.

A smart tutor embedded in a lesson produced the following results:

• Keeping your competition at bay
• Your educational institution can benefit from virtualization
• Students’ performance can be boosted

AI and machine learning have proven to be a blessing for the education industry due to the development of technology, which has enabled endless machine learning use cases.

The EdTech industry uses AI & ML in three popular ways

Learning by doing

With over 300 million subscribers and a $2.4 billion market cap, Duolingo is a language learning app founded in Pittsburgh that utilizes machine learning algorithms to improve its language teaching process.

The app uses machine learning to analyze the user data and personalize the language learning experience based on AI and deep learning algorithms.

University of Cambridge

Coursera was established in 2012 as an AI-powered application that provides online degrees, certifications, and online courses in a variety of subjects through collaboration with universities and educational institutions. With Coursera, students can watch lectures in advance and focus on discussions and interactive learning during class. This is ideal for “blended learning.”

This app is free, open, and flexible, and it includes various features including mobile notes, customized reminders, transcripts, on-demand video lectures, and much more.

Insightful

The Brainly app receives around 350 million monthly users, offering an ideal peer-to-peer learning platform for students, teachers, and parents.

A large number of teachers and students use the app, which makes learning more enjoyable and convenient.

Conclusion

Education administrators have been able to make their job easier, smarter, and less stressful with the impact of machine learning on the education industry. Aside from this, artificial intelligence and machine learning for school students has also gained traction as the technologies provide students with an improved and smart learning experience.

Ed-tech has been uplifted to a whole new level with the incredible combination of AI & ML. In order to manage educational operations, traditional methods have become obsolete, and people are switching to automated platforms backed by the latest technologies. So machine learning and education still have a long way to go. To make everyone come forward and appreciate your efforts, your education department needs to understand the time’s demand.

Therefore, in the educational industry, ditch old learning methods and embrace machine learning applications. There are many agencies in the digital ecosystem that can build machine learning applications and tools. Having a clear idea of how machine learning is changing education, the first step is to seek out businesses equipped with machine learning that can assist you in developing an AI & ML model that will work for you.