Machine learning is becoming more prevalent in the modern classroom as teachers make the shift to blended learning. Students often enjoy the more modernized version of lessons that allow them to learn at their own pace. Even teachers can enjoy the more personalized aspect of machine learning. However, many are beginning to wonder if everything about these machines is truly beneficial for our students. It seems that there are just as many limitations to learning this way as there are benefits.

It’s time to take an objective look at the real advantages and disadvantages of machine learning. When we can face the truth about what this holds for our children, we may be able to better balance our expectations.

Benefits of Machine Learning

It’s hard to overlook personalized education as the most prominent advantage of machine learning. Students can work on material that suits their unique capabilities and advance to more difficult content when they are ready. Not only do students benefit from this unique approach to learning, but teachers can save a great deal of time. They no longer have to create lesson plans that cater to students of all abilities and grade levels.

The advantage of machine learning also shows up in the automatic grading system. This presents the opportunity for completely unbiased grading that can’t be influenced by the teacher’s relationship with any student. It saves teachers time and gives a more realistic overview of a child’s achievements in school.

Machine learning can also help educators to look toward the future. By analyzing their data in the system, patterns will quickly emerge that show where the student’s primary weakness is and if they will need more help. If the issue is academic, the computers can provide a form of virtual tutoring. However, it can also indicate if a student is at risk of dropping out or receiving greater disciplinary action.

Limitations of Machine Learning

The major downside to machine learning is that we are taking personal interaction away from the students. This can dramatically impact their ability to make friends and present themselves well in the workplace over the years ahead. Social skills still need to be emphasized even while using machine learning.

As helpful as it can be to allow the computer to grade student papers, it isn’t always going to be effective. Educators will still need to plan to grade essays and other items the old-fashioned way. Computers lack the ability to assess items that don’t have a specific technical requirement associated with them. They can easily grade multiple choice but struggle with the more time-consuming essay assignments.

Of course, many schools are evaluating the advantages of machine learning due to the inherent cost. It can be quite expensive to purchase all new equipment and programs to make personalized learning an effective solution for educators and students. This can be one of the biggest limitations to machine learning.

The Final Answer

Machine learning definitely presents a number of advantageous features for students and their teachers. The possibility of a personalized education that can save time for teachers and help to predict a student’s future success is invaluable. However, we still have a long way to go. Educators won’t want to jeopardize the social skills of their students, and they must consider if their school district can afford the equipment. Schools will have to decide how to balance out the features that mean the most to them and how they can afford to implement them.