4 ways machine learning in EdTech is transforming education

Updated: Mar 29

Amid all the technological advancements in the digital age, how humans interact professionally and personally is changing, and the education industry is no exception. Among these changes, the EdTech industry is witnessing a significant transformation with the induction of artificial intelligence and machine learning applications, but what exactly is machine learning?


The EdTech industry is witnessing a transformation with the induction of AI and machine learning applications.

What is Machine Learning


The terms artificial intelligence (AI) and machine learning (ML) are often used interchangeably, but there is a difference. AI refers to computers doing things that we usually expect only humans can do, such as Apple Inc.’s Siri holding a conversation or Google creating cars that drive themselves. On the other hand, machine learning is an extended application of artificial intelligence in which computers learn from data and experience rather than being programmed to follow an explicit set of instructions. In short, it is a learning system that evolves from experience.

The education industry has seen the emergence of different SaaS (software as a service) platforms using machine learning algorithms such as TurnItIn or Grammarly. Machine learning is also beginning to become more popularized using current EdTech tools mentioned in a previous article, such as text-to-speech software and audio transcription.

In this article, we will discuss four ways machine learning enhances EdTech.

1. Predictive Analysis

One of the most pertinent machine learning EdTech tools is its ability to make more accurate predictions of student performance. Previously, teachers could only base predictions for student outcomes on their limited experience of students’ class performance, which could often be found on favoritism.

With machine learning, data sets of students’ cumulative records can be analyzed. They will predict which students are more likely to achieve academic success, which students are likely to drop out, and even predict students’ scores on standardized exams such as the ACT or SAT.

With predictive analytics, educators will be given more accurate information on which students require more academic attention and will be able to provide more accurate resources for each student to help them excel in the classroom.


2. Increased Efficiency

On a much broader scale, machine learning in the form of artificial intelligence can relieve many unnecessary burdens put upon teachers and administrators. ML can increase classroom efficiency by completing tasks for educators, such as classroom management, scheduling appointments, and even helping teachers design curriculum. With new advancements in EdTech ML, teachers will introduce new interactive and exciting learning methods.

In turn, educators are free to focus on the actual education of their students, as well as other tasks that cannot be achieved by AI and that require human interaction.

3. Personalized Learning

Not only does ML’s ability to design curriculum help improve classroom efficiency, but it also has the potential to create individual lesson plans catered to the needs of each student.

Personalized learning is the educational model where students guide their learning at their own pace. This may even include students making their own decisions about what to learn in some cases. This model allows students to be more creative without worrying about standardized grades, as ML can differentiate between peers based on individual needs. Companies such as Content Technologies Inc. use AI to create customized textbooks that fit the needs of specific courses and students. 

Personalized learning models provide learners with the academic freedom needed to succeed. This cannot happen if all students are provided with fixed content and tasks that don’t consider their specific learning needs.

4. Robot Teachers

Though it may be considered an extension of customized learning, the emergence of ML in the form of actual teachers deserves its own category. The development of robot teachers, or “smart tutors,” is slowly making its mark in education.

ABii stands only fifteen inches high and has dazzling, purple lights for eyes.

This is probably the most ambitious and controversial ML technology and is included in this article because it is one of the most radical ideas in AI.

There have been efforts to turn this pipedream into a reality, including in 2016 with introducing the K-5 education classroom assistant ABii from Van Robotics. This intelligent robotic tutor personalizes math and reading lessons while having fun social interactions with the young students. Today, ABii is used in over 30 US States, England, Germany, Qatar, and the United Arab Emirates.


Conclusion

These are only 4 of the many ambitious potential benefits of machine learning. Smaller-scale ML algorithms such as text-to-speech and audio transcription functions are just the beginning for EdTech. With the impact of the COVID-19 pandemic on education in conjunction with a push to increase the availability of hardware technology, the demand for EdTech solutions is higher than ever, and ML will continue to play a major role in its growth.

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