3 Ways Machine Learning in EdTech is Changing the Education Industry

From machine learning algorithms to Artificial Intelligence (AI) driven assistants, the education industry is experiencing some high-end transformation and will more likely to witness some more inclusion of AI applications in the coming years. 

In a true sense, machine learning is adding some significant value to the education sector as never before. It is a technology that is evolving leaps and bounds and making an indelible mark in the education industry. 

Without any further ado, now it is time to comprehend what Machine learning is all about. It is an extended application of artificial intelligence, machine learning (ML) provides a system to learn from experience without being programmed to perform a particular task. 

Basically in a most succinct way, it is a learning system that evolves over time. So the companies involved in Edutech focus on more technologies and exploring new avenues of innovation in education, the phenomenon of machine learning is helping those companies to differentiate themselves. And undoubtedly, with some advancements in ML, this trend will continue to change the education industry forever. 

Applications of Machine Learning in the Education Industry

  • A way forward to Predictive Analysis 
A way forward to Predictive Analysis

We all witnessed the time when “old school” teachers had opinions about a student’s future based on favoritism. That trend of analysis most likely ended up in reduced morale of young minds who thought themselves less worthy or less intelligent than others.

Here predictive analysis comes into play and replaces favoritism with “proof-eccentric” data. By harnessing the complex algorithms of machine learning in EdTech, the predictive analysis analyzes the whole past and the present data to make predictions about future results. 

Predictive analytics encompasses a variety of statistical techniques from data mining, predictive modeling, and machine learning, that analyze current and historical facts to make predictions about future or otherwise unknown events.” ~ Wikipedia

So basically, how is this helpful? Students who are likely to drop out or score less than the bar can become the main focus of the teachers. Anyways, the prime focus of any education curriculum should be on the students who feel left out or unattended. 

To be more productive, predictive analysis brings attributes to many educational institutions by letting them combine what they already knew with new innovative methods. These technology-enabled methods then empower teachers and authorities to frame proactive strategies for the bright future of the students. 

For Instance: Hamilton County successfully tracked students’ performance with predictive analysis software IBM SPSS, and managed to keep their students’ growth on track. The success came in the form of a graduation rate that boosted up to 10 %. 

The data ultimately helped in:

  • Developing an effective student retention system
  • Creating 360-degree profile views of students 
  • Revamping the entire enrolment management 
  • Enhancing student scores and overall performance
  • Process Efficiency with more result orientated analytics backed programs 

Educators require a better system that does all the job for them and lets them focus on some pressing concerns, i.e., imparting knowledge to the masses. The memory simply belongs to the oblivion when teachers struggled to maintain separate logs for their students. 

Now machines powered by AI & ML have taken over the load by systematically organizing content and managing the entire gamut of activities related to teaching and student analyses.

MarketsandMarkets estimates the global EdTech and smart classroom market size is expected to grow from USD 85.8 billion in 2020 to USD 181.3 billion by 2025, at a Compound Annual Growth Rate (CAGR) of 16.1% during the forecast period.”

Another area of education where ML has made a mark is to bridge the gap between 

students and teachers. A student doesn’t have to run behind the teachers for appointments as the automated system will do that for them based on the student and the teacher’s routine schedules.

Example: Netex Learning is a machine learning-enabled web platform that lets tutors design curriculum for the day. The best part is that teachers already get the leverage to design the teaching plans around content that include videos, audio, personalized assignments, and even discussion portals.

The results of applying machine learning in the education industry:

  • Reducing administrative burdens significantly
  • Lets students and teachers focus on what matters
  • Introduces interactive and exciting learning methods
  • Revolutionizing Learning with Smart Tutors
Revolutionizing Learning with Smart Tutors

The traditional lectures are distant entities from practicality and real-world implications. So there has always been a void for renovation and that is exactly what is introduced by machine learning technology. 

“Smart tutors” is a quintessential development that is slowly and steadily making its mark in the world of education. The lectures are being transformed into video tutorials, flashcards, smart guides, educational apps, and everyday assessment quizzes.

One element that stands out is that students and teachers get 24/7 accessibility to virtual educational sources. 

Another form that the smart tutor system is taking, comes in the form of virtual tutors. For your education institution, this could be the best take on being labeled as a true“EdTech” body that embraced machine learning.

Example: Virtual teachers in the form of robots are teaching the kids in Singapore. The robots are capable of reading stories, giving assistance with simple math problems, and helping introverted kids to evolve in a much better way.

Results of embedding smart tutors:

  • Staying one step ahead in your competition
  • Adding virtualization to your educational body
  • An opportunity to boost students’ performance

Next year Prediction

“It is expected that artificial intelligence in U.S. Education will grow by 47.5% from 2017-2021 according to the Artificial Intelligence Market in the US Education Sector report.”

Organizations using AI In Education To Enhance the Classroom:

Conclusion

This is it! Machine learning in the education industry still has a long way to go. All your education department needs is to understand the time’s demand, so that everyone comes forward and appreciates your efforts.

The major factors driving the growth of the EdTech and smart classroom market include increasing penetration of mobile devices and easy availability of internet users, growing demand for EdTech solutions, the impact of the COVID-19 pandemic, and growing online teaching-learning models to keep running the education system.

So, ditch the old learning ways and embrace machine learning that would work for the best like our developed app videobomb.

The first step starts with looking up machine learning-equipped businesses that can help you build a workable ML model.

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