McKinsey reported that 71% of students found machine-learning-powered teaching assistants helpful.
So, if you still think of classrooms as traditional setups with rows of students using the same textbook and a teacher delivering a standard lecture at the front, we have news for you!
Modern classrooms are evolving thanks to technology like AI and machine learning. These models can supplement the learning processes to improve student engagement and performance. This means that they can significantly reduce the burden of administrative tasks while also boosting efficiency. It’s an excellent tool for helping accelerate operations, especially at educational institutions. Machine-learning-based models have been used in e-learning platforms for students to help personalize and adapt study materials to individual student needs.
What is Machine Learning (ML)?
Machine learning (ML) is a subset of artificial intelligence (AI). So, AI is basically a computer program or algorithm that mimics human intelligence, i.e., it performs specific tasks so humans won’t have to – we call this automation. This can include solving problems, making decisions, or even just recognizing patterns. However, the fundamental difference between artificial intelligence and machine learning is that machine learning is not a stagnant computer program. Instead, it can learn, improve, and adjust its performance in response to new information, i.e., it’s still training or “learning.” So, the algorithm is continually developing and adapting during its interactions with the user. For example, Grammarly is an AI writing and proofreading assistant based on machine learning, and it improves its suggestions over time by adapting them to your specific writing style. Another example is how YouTube or TikTok use watch history and interests to personalize recommendations and show only relevant ads to users.
How Can Machine Learning Be Used in Education?
Before diving into the benefits of machine learning, let’s consider the role of machine learning in education. How can machine learning be used in education to improve learning outcomes?
We know that machine learning models are really good at recognizing patterns and that they can adjust based on new information. They can also work autonomously like AI models. In the context of education, this means:
- Identifying learning difficulties
- Recording and classifying learning behaviors
- Personalizing study materials
- Predicting learning outcomes
- Identifying struggling students
These parameters create an adaptive learning environment, which can significantly improve higher education. But the use of machine learning in education doesn’t end here – it can automate administrative tasks, too, which would take a HUGE burden off of educators. Use case examples of machine learning in education could include grading and assessment automation tools, smart assignment assistant tools, and adaptive learning platforms for teachers.
Even so, one of the biggest benefits of machine learning in online education is the concept of personalized learning. ML models will observe student learning behaviors and adjust to support these behaviors. So, for an online learning platform, this could mean identifying gaps in student understanding, creating personalized schedules, or providing smart recommendations tailored to the student. This would ensure that students can stay on top of things without becoming too overwhelmed.
5 Benefits of Machine Learning in Education
ML algorithms make predictions and decisions, which are refined over time. Using AI and ML models can significantly help improve teaching and learning processes. The benefits of machine learning in education include:
#1 Personalized Learning
Personalized learning means study materials and instructions are customized to suit each student. ML allows students to play to their strengths and weaknesses rather than mindlessly reviewing standard textbook material. This is especially important for online learning platforms for students because ML helps to personalize content recommendations. The traditional practice of all students using the same study materials regardless of their learning behaviors is a problem. It gives certain students an advantage, while most end up clueless. On the flip side, machine learning ensures that every single student gets the attention and study material(s) they need to reach the expected level of understanding. And it’s so much easier for students to study when their diverse learning behaviors are considered. Besides this, college students with learning disabilities can also benefit from machine learning because it can help accommodate their unique learning behaviors.
#2 More Effective User Experience
Traditional classroom learning is not ideal for most college students. Even in online learning settings, where students can study at their own pace, most students still struggle to grasp concepts. It’s not that they don’t want to learn or that they’re not working hard enough – the truth is that their learning behavior doesn’t match the mode of instruction. They’re trying to learn, but their brain isn’t accepting the information. So, they can spend hours trying to make sense of this information, or they can go find additional study materials to understand the topic from a different perspective – and that’s not easy either!
Statistics indicate that the average college student spends around 8 hours a week looking for learning materials. That’s 8 hours of unproductivity! Most college students are working part-time jobs or balancing multiple commitments simultaneously. So, they really can’t afford to spend so much time looking for study materials. They need an educational system that adapts to them and enables them to learn better and faster – and ML is the way to go!
#3 Improved Curriculum
Another major benefit of machine learning in education is that it can help improve the course curriculum. The model records how students interact with course content and what materials are helpful. Educators can then use this information to adjust the course contents for the next term. They can also identify gaps and adjust the difficulty for specific components to accommodate more students. So, ML can help improve standard curriculums to make them more student-centered, ultimately generating better learning outcomes.
#4 Improved Retention
Improved retention is yet another benefit of machine learning in education. The role of machine learning in education is to facilitate personalized learning experiences for students. This means considering unique learning behaviors and accommodating them to ensure that all students can understand the material as well as they are supposed to. So, if the learning material makes more sense to students, they can understand better, faster, AND retain the information for longer! But that’s not all!
When students can retain information longer, they’ll perform better in assessments and get better grades. This means that they’re less likely to drop out of college, which, in turn, helps student retention.
So, the use of machine learning in education has a two-fold benefit in terms of retention at the student and institutional levels.
#5 Faster Learning
Machine learning delivers personalized learning experiences, which means students can make more sense of the material since it’s tailored to their needs! So, instead of reading and re-reading the same material, the right resources allow students to understand the content more easily – meaning they’ll need to spend less time studying. And that’s amazing from a college student’s perspective, because less time studying means better time management and a slightly lesser strain of their never-ending responsibilities!
How Can You Use Machine Learning at Your Educational Institution?
The use of machine learning in education is definitely shaking things up at educational institutions. In fact, machine learning might be indispensable in the educator sector in the near future. So, now that you know how machine learning can be used in education, it’s time to start thinking about implementing adaptive learning using ML.
At SimpliTaught, we use artificial intelligence and machine learning to help educational institutions deliver personalized and adaptive learning experiences to college students. Discover how we can help 100% of your students graduate successfully right here!
