Education field has seen zillions of evolutions throughout the period of history, from the traditional methods of modern methods and discovery of more effective and student specific approaches.
As we are progressing into the digital age, one of the major shifts is the introduction of Artificial Intelligence (AI) into the educational world, precisely in personalised learning.
AI has the power to polish up education by building learning experiences according to individual needs, personality, and requirements of students, making education more imaginative, efficient, as well as engaging.
In this blog, we are going to explore how AI is shaping personalised learning, the benefits it brings, the challenges it faces, and its implications for the future of education.
Before we delve into all the nitty gritty regarding AI. Let’s first Understand the meaning of Personalised Learning.
So, Personalised learning is an educational approach that focuses on customised learning based on the learner’s strengths, weaknesses,learning rhythm and speed.
In contrast to traditional classroom setup where all students receive the same instruction regardless of their individual requirements, personalised learning seeks to provide each student with a unique learning method to bring out the best in them.There is a kind of level playing field to each and every student.
There are numerous elements which make up for Personalized Learning. Some of them are discussed below in the blog.
Major elements of personalised learning include:
1.Individual centred approaches: Here,The focus lies on individual learner, customising educational strategies to their requirements.
2.Skill-based learning: Students progress through their learning journey based on mastering skills and competencies, rather than adhering to a set schedule.
3.Adaptive learning Schedules: The learning setup is designed to support a variety of learning styles, opening opportunities for students to learn in ways that suit them best.
Now, let’s take a look at the role of AI in personalised learning.
The contribution of AI in Personalized Learning:
AI is the core of the latest discoveries in personalised learning, leveraging data and algorithms for data analysis and adapting to student performance in a dynamic environment.
Al and ML(machine learning)can process large amounts of data from various sources such as evaluating marks, assignments, various activities and past trends to make individualised learning experiences.
1.Data-Drived insights for Individualised Learning Paths:
AI systems have the ability to analyse a student’s performance data to identify patterns and trends.
For instance, if a student is struggling in English communication, AI algorithms can identify this lacunae and adjust the curriculum to focus more on that area.
Similarly ,if a student is doing well in a subject, the AI can recommend more challenging materials to keep them engaged.
This data-driven approach ensures that each student receives the appropriate level of challenge and support, which can result in more efficient and effective learning.
2.Adaptive Learning Environment:
Major contribution of AI to personalised learning is the creation of adaptive learning platforms. These platforms use AI algorithms to consistently evaluate students’ progress and adapt in real time.
For instance, platforms LearnUpon, Grammarly and GPTionary arrange the difficulty of exercises based on the learner’s performance, providing additional support or increasing the complexity of tasks as and when required.
This establishes an ecosystem for more customised learning opportunities that is based on the student’s interests and requirements.
3.Automated mentoring and Feedback Mechanism System:
AI-enabled tutoring systems have the ability to provide personalised assistance to students in areas where they are struggling the most.
Contrary to traditional teaching ,which requires one-on-one sessions with a human teacher or mentor, AI mentors are available 24×7, offering guidance whenever a student needs help.
For example:Systems like Mathly and Pearson’s AI-based tutoring solutions offer step-by-step explanations and feedback on students’ work, guiding them through complex sums and questions.
The immediate feedback provided by AI mentoring systems helps students understand their mistakes and correct them immediately ,which can significantly improve learning results and it can make the system efficient.
4.Natural Language Processing for Personalized Interaction: The next amazing way AI is transforming personalised learning is through Natural Language Processing (NLP).
NLP provides opportunities for AI systems to comprehend and respond to human languages, making it possible for students to interact with the system in a more conversational manner
For Example: Virtual assistants, like Amazon’s Alexa and Apple’s Siri, are already being used in some educational settings to answer students’ questions, provide study guides, or suggest resources based on a student’s inquiry.
The ability to ask questions and receive answers in real time can motivate students to take part in various of their learning experiences.
5.Trend Analytics for Early Intervention:
AI’s predictive analytics capabilities enable educators to identify students who may be at risk of falling behind or dropping out based on the trends.
By analysing patterns and trends in attendance, submissions of assignments, and test marks, AI can predict which students are likely to encounter difficulties in the future.
This allows educators to take preventive measures, providing additional support or resources to help these students stay on track.
Predictive analytics can also identify excelling students who may need more advanced materials to stay engaged and challenged, ensuring each student is getting his/her due attention.
6.Content Creation through AI :
AI has revolutionised the field of content creation, making it possible to develop personalised educational materials. Some AI systems are capable of generating customised quizzes, assignments, and study materials based on a student’s learning pattern and need.
This can save teacher’s time while ensuring that each student receives materials that are individual specific.
7.Virtual Reality (VR) and Augmented Reality (AR) in education:
AI combined with VR and AR, can create immersive and interactive learning experiences that are customised to the individual.
For instance, AI can guide students through virtual simulations that adjust in real-time based on their performance, allowing for hands-on learning in a controlled environment.
This is particularly useful in fields like science and engineering, where students can experiment with complex concepts in a virtual lab without the limitations of physical space or resources.
The Benefits of AI in Personalized Learning:
The integration of AI into personalised learning offers several benefits:
1.Improved Engagement: Personalised learning, powered by AI, can make education more engaging by delivering content that suits the learner’s interests and abilities.
Students are more likely to stay motivated and invested in their learning when the material is relevant and appropriately challenging.Trends have shown to improve the enrollment to such courses.
2.Efficient Learning Outcomes: Offering targeted support and adjusting the difficulty of materials in real time, AI can help students overcome their weaknesses more quickly and efficiently. This leads to better retention of information and improved academic performance. Students don’t have to waste time delving on the things on which they are already good.
3.Increased Accessibility: AI-powered personalised learning platforms can provide support to students with diverse learning needs, including persons with disabilities and special childs.
AI can offer text-to-speech options for students with reading difficulties or create customised learning environments for students on the autism spectrum. This is making education more inclusive and accessible to all learners. This helps in bridging the gap in learning.
4.Time Efficiency for Mentors and Students: AI can perform so many administrative tasks, such as grading and lesson planning, freeing up teachers to focus on more meaningful interactions with their students. Teachers can also use the insights generated by AI to better understand each student’s needs and provide more targeted support to each and every student.
5.More Scalability:A state of art technology like AI has advantages in scalability. AI-driven platforms can deliver personalised education to millions of students simultaneously, something that would be impossible with traditional one-on-one teaching methods.
This makes it possible to provide individualised learning experiences on a large scale, addressing the needs of students in remote or underserved areas.
For Instance: During COVID 19 pandemic it was made possible to provide classes online through the help of AI platforms.
Challenges and Limitations of AI in Personalized Learning:
While the benefits of AI in personalised learning is humongous, there are many challenges associated with it. Some of them are discussed below:
1.Data Privacy Concern:
AI systems rely on vast amounts of data to deliver personalised learning experiences. This raises concerns about the privacy and security of student information.
Ensuring that data is collected, stored, and used in a secure and ethical manner is crucial to gaining the trust of students, parents, and educators. As there are many instances where there was breach of privacy on such platforms.
2.Pre Disposition in AI Algorithms:
AI systems can perform well as and when they are trained. The data used to train AI algorithms may be biased, the personalised learning experience may also be biased, fueling inequalities in education.
There is this need to ensure that AI systems are designed and trained to be as inclusive and unbiased as possible.
3.Lack of Emotional Connect Teacher to Students and Peer to Peer:
Although AI can make the education system altogether more efficient,The introduction of AI in the classroom may lead to concerns about the role of teachers.
While AI can handle many administrative tasks and provide personalised support, it cannot replace the human connection and mentorship that teachers provide.
Educators will need to adapt to new roles that involve guiding students through AI-enhanced learning experiences. Moreover, teachers will require professional development to effectively integrate AI tools into their teaching methodologies.
4.Lack of Infrastructure and Technology:
Access to AI-powered personalised learning platforms requires technology and internet connectivity, which may not be available to all students. The digital divide can add up to existing educational inequalities, leaving some students without access to the benefits of AI in personalised learning.
5.Ethical Concerns : The use of AI in education raises several ethical concerns, such as who controls the algorithms and how decisions about students’ learning paths are made. There is a need for transparent guidelines and policies to ensure that AI is used in a way that benefits all students and promotes transparency and accountability in education.
The Future of AI in Personalized Learning:
As ,AI evolves and plays an even more significant role in shaping personalised learning. Future advancements in AI could lead to more sophisticated adaptive learning systems, capable of understanding not just what students know, but also how they learn best.
AI may also facilitate more collaborative and social learning experiences by connecting students with peers who share similar learning goals or challenges.
Additionally, AI has the potential to create lifelong learning ecosystems where individuals can access personalised education throughout their lives, adapting to their evolving needs and career goals.
As industries and institutions evolve and new skills are required, AI-powered platforms could provide the necessary training and education, making learning more dynamic and responsive to the demands of the the market.
Conclusion:
AI has tremendous potential to revolutionise personalised learning by providing unique educational experiences that meet the unique needs of each student.
By data-driven insights, adaptive learning platforms, automated tutoring, and trend analytics, AI has the potential to improve learning outcomes, enhance engagement, and make education more accessible, inclusive and affordable.
However, challenges such as data privacy, algorithmic bias, and the ethical concerns attached must be addressed to ensure the benefits of AI in personalised learning.
In this age of technology AI is no less than a digital weapon. AI is also a two edged sword which must be utilized with responsibility and accountability.