Introduction
The education industry defines the future of a country as it inspires and teaches the youth of tomorrow, who are responsible for building the future of the planet.
With numerous advancements in technology that influenced almost every industry like manufacturing, healthcare, etc, the education industry was also not left behind. Hence, it led to the birth of another branch of education known as EdTech or educational technology.
One of the most important technologies that have influenced the education sector is generative AI. With the help of generative AI in EdTech, the education industry is able to provide personalized educational content to its students, leading to increased understanding and growth.
In this blog, we will understand how generative AI in EdTech is used to provide personalized educational content to students. We will also find out the various applications of the AI in the creation of personalized curriculums and how it enables adaptive learning that helps to meet the specific needs of the students.
Generative AI in EdTech
Before understanding the various applications of AI in personalized learning, let us understand its basic concepts.
What is Generative AI in EdTech?
In general, generative AI includes various advanced AI algorithms that have the capability to create new content in the form of text, images, or even interactive exercises.
With the use of generative AI in EdTech, the AI systems achieve the ability to generate various kinds of learning materials, such as lesson plans, personalized study notes, quizzes, and even entire courses for a learner.Â
Generative AI for education analyzes large datasets that include both the educational content as well as the performance of the student. This helps to create relevant and personalized educational and learning resources for the student. The content that is produced is specifically customized for each learner on the basis of their learning pace, preferences, and abilities.
Why is Generative AI in EdTech Important?
Generative AI in EdTech is beneficial for both students as well as the teachers who use the AI systems to create their teaching strategy and content.
With the help of generative AI, teachers can democratize learning, making it accessible, understandable, and interesting for each student.
In the traditional ways of teaching, which was present before the introduction of technology, all the course materials were made in a standardized manner which basically followed the approach of one size fits all. As a result, students who had a different speed of understanding or learning, either needed to take extra classes or used to learn at a slower speed which often made them disinterested.
Generative AI in education industry helps the students by understanding their different learning styles and speed of understanding and generating a unique, specific, and personalized learning experience for the student as per their needs and preferences.Â
Additionally, generative AI in education also saves up the time of the teachers by automating the process of content generation like class notes, quizzes, etc. This helps the teachers as they are able to improve and focus more on their teaching and mentoring skills while engaging with the students in a more meaningful and efficient manner.
How Does Generative AI Work in EdTech?
Generative AI basically works with the help of advanced algorithms of artificial intelligence, machine learning, and natural language processing (NLP), which further helps it to effectively and efficiently analyze huge volumes of educational data.Â
The AI systems not only learns from all the existing educational content but also the data related to the performance of the students. As a result, the system is able to generate new content in the form of quizzes, exercises, class notes, and lesson plans.
Further, as AI systems have the ability to continuously learn from newer materials, the content generated can be improved, updated, and refined regularly based on the interaction and progress of the student, to ensure the maximization of understanding and growth.
Personalized Curriculum Using AI
A personalized curriculum can be defined as a unique and custom made learning path for a student that is specifically designed to meet all the unique needs, capabilities, and interests of every student. Through generative AI in EdTech, the education industry has achieved the capability to create personalized curriculums as it helps to automate the entire process and make it more efficient.Â
Let us find out the various ways in which we can create a personalized curriculum using AI.
Creating Customized Learning Paths
Generative AI in EdTech has the ability to create customized learning paths for each student by analyzing past performance, learning preferences, and strengths and weaknesses of each student.
For example, there is a student who is excellent in the subject of science but struggles when it comes to mathematics. In such a case, the AI systems will develop a personalized curriculum for the student that would include advanced exercises for science so that he feels challenged and gains more interest, and it will also include additional support in mathematics so that he can come to the level of the entire class and not feel behind or overwhelmed.
As a result, the student is able to identify their areas of improvement and put more focus on it while continuing to improve and excel in their areas of strengths.
Adapting Curriculum in Real-Time
One of the most important benefits of using generative AI in EdTech is that you can update the curriculum in real-time as the curriculum is designed in such a manner.Â
The AI system receives input with respect to the student performance and based on that input as well as feedback, the AI systems can update and modify the curriculum. In such a case, the AI systems adapt in real-time and either add or remove certain topics as well as adjust the difficulty level as required by the student.
For example, if a student is performing exceptionally well in the subject of science, then, the AI systems automatically suggest more advanced topics in the subject of science to keep the student interested and challenged.
Adaptive Learning with AI
Adaptive learning can be defined as a system that uses generative AI in EdTech to adjust the content as well as teaching strategies for a student based on the performance of the learner in real-time. With the help of generative AI in adaptive learning, this process has become more accurate, efficient, and effective.Â
Let us find out how adaptive learning with AI can improve the educational experience of a learner.
Analyzing Learning Behaviour
Generative AI in EdTech uses advanced artificial intelligence, machine learning, and natural language processing (NLP) algorithms in order to analyze the learning behaviour of individuals in real-time.Â
This is done as the AI systems track various aspects of the learning process of the student, such as how long they take to complete a task, the kinds of mistakes they often make, their areas of excellence, and their weak spots. By analyzing such information, the AI systems create adaptive learning experience for the individual based on their specific needs.
For example, if a learner is particularly weak in one area of mathematics, say multiplication, then the AI system will generate additional practice problems for multiplication so that the learner can get additional practice to understand and grasp the concept in order to be good at it.
Real-Time Progress Monitoring
With the help of generative AI in EdTech, both the learners (or students) and educators (or teachers) have the access to real-time progress reports. As a result, the students as well as the teachers can gain valuable insights into the performance of the student, their struggle areas, and the various adjustments that are required to be made to the learning path of the individual.
With timely and real-time insights through constant real-time monitoring, students are able to keep track of their progress with respect to their learning goals.
Conclusion
As per the findings of financial express, approximately 64.87% of educators have recognized the transformative affect that generative AI in EdTech has had with respect to improving learning experiences and personalized education.
Generative AI in EdTech has helped transform the education industry by providing personalized education content that adapts to the specific needs of the individuals in real-time. As a result of personalized curriculum and adaptive learning, education has become more engaging, understandable, accessible, and efficient for the students.
We at CrossML, with our expert generative AI solutions, help the education industry in implementing and integrating AI with education, leading to improved outcomes for the students. Additionally, with our solutions, even the educators can focus on providing better mentorship to the students, leading to better results and understanding of the course materials by the students.
FAQs
Generative AI can improve personalized education by creating adaptive learning paths that are customized as per the needs of individual students, generating personalized content, offering real-time feedback, and adjusting the speed of the course material.
Generative AI creates tailored learning experiences by analyzing student data, their learning preferences, and real-time performance to create customized plans, study courses, and assessments. It has the ability to adjust content dynamically which is based on the strengths and weaknesses of the individual. As a result, it provides a targeted support for more effective, and personalized learning experiences.
Generative AI is shaping the future of EdTech by enabling adaptive and personalized learning experiences, automating content creation, and offering real-time analytics into the progress of the students. This helps to improve learning efficiency and engagement, helping to make education more accessible and customized to the individual needs of the students.
The various future trends that we can expect for generative AI in EdTech include immersive AI learning environments, improved integration with AR/VR, enhanced real-time analytics, and increased adoption of AI adaptive learning systems.
