Revolutionising learning experience with AI

In this article, DANIEL ADAJI explores how AI enhances learning outcomes, its potential challenges, and the future possibilities for students and educators

Integrating Artificial Intelligence into education has become a transformative trend, reshaping how students learn and teachers deliver instruction.

AI offers dynamic, personalised, and adaptive learning experiences that traditional teaching methods often lack. In the digital age, where information and technology are at the heart of development, utilising AI in education is crucial for improving learning outcomes across all levels—basic, secondary, and tertiary education.

Laying the foundation of AI in basic education

Personalised learning

In the early stages of education, where students are just beginning their learning journey, personalised learning can make a significant impact. AI algorithms assess individual students’ strengths and weaknesses through continuous data analysis, adjusting lessons to suit each student’s learning pace and style.

For instance, platforms like DreamBox and Smart Sparrow use AI to personalise mathematics and literacy education for young learners, providing targeted interventions when a student is struggling with a concept.

Intelligent tutoring systems

AI-powered Intelligent Tutoring Systems can replicate one-on-one instruction, which is often unavailable in overcrowded classrooms. These systems, like Carnegie Learning or Squirrel AI, are designed to monitor students’ progress in real-time, offering explanations and hints when a student hits a learning block.

At the primary level, this helps students build foundational skills in subjects like reading, writing, and arithmetic without relying solely on teacher intervention.

Special education support

AI also plays a crucial role in supporting children with learning disabilities or special needs. AI tools like Voiceitt and Talkitt help children with speech impairments communicate effectively, while other AI-powered systems offer tailored learning experiences for students with autism, dyslexia, or ADHD. This inclusion and accessibility enable all students to benefit from education tailored to their unique challenges.

Gamified learning

AI-driven gamification tools are used in basic education to make learning more engaging. By integrating AI into educational games, students in their early years can engage with educational content in a playful yet informative way.

For example, AI-powered apps like Kahoot adapt quizzes and learning materials based on student performance, keeping young learners motivated and interested in learning through reward-based gaming experiences.

Building knowledge and skills with AI in secondary education

Adaptive learning platforms

In secondary schools, AI helps address the diverse learning needs of students through adaptive learning platforms. These platforms adjust the difficulty of the content based on the student’s understanding of the subject.

For instance, systems like Knewton and Edgenuity analyse how a student performs in quizzes and assignments, using this data to adjust future lessons to suit their learning progress.

Intelligent feedback mechanisms

One of the most important benefits of AI in secondary education is the ability to provide real-time feedback. Traditional methods of assessment often involve delays, especially in large classrooms. However, AI tools can assess and grade assignments instantly, giving students immediate insights into their performance.

This instant feedback allows students to correct mistakes promptly, improving learning retention. Tools like Turnitin and Grammarly provide students with immediate feedback on writing assignments, helping them improve their grammar, structure, and content quality.

Enhancing STEM education

AI is a powerful tool for enhancing learning in Science, Technology, Engineering, and Mathematics. AI-based virtual labs allow students to perform complex experiments without needing physical lab equipment.

For example, Labster and PhET Interactive Simulations offer AI-powered virtual labs, allowing students to engage in simulated scientific experiments, even in resource-constrained settings. These tools make learning more interactive and accessible, especially for schools with limited resources.

AI and language learning

Learning new languages becomes more effective with AI-powered language learning platforms. Tools like Duolingo use AI to adapt language lessons based on user proficiency, helping students develop language skills at their own pace. AI-driven translation apps and speech recognition tools can also provide students with real-time assistance in mastering pronunciation and grammar, giving them a more comprehensive understanding of foreign languages.

Shaping future leaders and innovators with AI in tertiary education

Personalised learning pathways

In tertiary education, students typically have more autonomy in shaping their educational experience. AI assists in creating personalised learning pathways, helping students design their curriculum and choose courses based on career goals, academic strengths, and interests.

AI tools like Coursera and edX provide students with recommendations for courses that align with their learning progress and future aspirations, while platforms like Cortex Learning assist universities in designing AI-powered curricula that meet the needs of individual learners.

Intelligent course assistants

AI-powered chatbots and virtual assistants have become common in tertiary institutions, offering on-demand academic support. These virtual assistants help students by answering questions, explaining complex topics, and assisting with administrative tasks like course enrollment.

For instance, platforms like Jill Watson, an AI-powered teaching assistant at Georgia Tech, help students access relevant materials, provide answers to frequently asked questions, and guide them through assignments, freeing up time for professors to focus on more complex teaching tasks.

Automated grading and assessment

With large volumes of students, grading and assessments can be a time-consuming task for professors. AI-driven grading systems offer a solution by automatically assessing student work, particularly in objective subjects like mathematics and science.

Even in more subjective areas like writing, AI tools such as Gradescope assist educators in grading essays, providing consistent and unbiased feedback. This not only speeds up the grading process but also allows students to receive timely feedback on their performance, which can help improve future work.

AI in research and innovation

AI is revolutionising research in tertiary institutions, helping students and researchers access and analyze vast amounts of data. AI-driven research platforms like Iris.ai assist students in finding relevant academic papers, while tools like Zotero and Mendeley help manage research citations.

Additionally, AI plays a critical role in more complex scientific research, enabling students to use AI algorithms for data analysis, pattern recognition, and simulation modelling in disciplines like engineering, medicine, and economics.

Cross-cutting benefits of AI in education

Promoting lifelong learning

AI-powered platforms make education more accessible for learners of all ages. For adult learners or professionals seeking to upskill, AI offers flexible, on-demand learning through Massive Open Online Courses and online learning platforms.

AI tools like LinkedIn Learning and Udemy analyse user behaviour and learning preferences to recommend relevant courses, allowing learners to continuously update their skills in response to evolving industry demands.

Accessibility and inclusivity

AI has the potential to break down barriers to education, especially for marginalised and differently-abled students. AI-powered assistive technologies like screen readers, speech recognition software, and real-time captioning tools make learning more accessible to students with disabilities.

For example, Microsoft’s Immersive Reader assists dyslexic students in improving their reading comprehension by converting text into spoken words. This inclusivity ensures that all students, regardless of their abilities, have equal opportunities to succeed in their educational journey.

Data-driven decision making

For educators and policymakers, AI-driven data analytics offer critical insights into student performance, helping improve decision-making in curriculum design and teaching strategies. By analysing large datasets from student assessments and engagement metrics, AI can identify learning trends, predict student success, and suggest areas for improvement in teaching methods. This helps educators make informed decisions about which teaching techniques or interventions are most effective.

Bridging global educational gaps

AI has the power to bring quality education to underserved regions, where access to skilled teachers or educational resources may be limited. Through AI-driven online platforms and virtual classrooms, students in remote or resource-poor areas can receive the same quality education as those in more developed regions.

AI-powered translation tools can also help overcome language barriers, making global educational content accessible to non-native speakers.

Challenges and ethical considerations of AI in education

The integration of AI in education has opened up new possibilities for personalised learning, efficient management, and improved educational outcomes. However, along with the opportunities, AI presents several challenges and ethical concerns that must be addressed to ensure its responsible and equitable use in educational systems.

Data privacy and security

One of the most pressing concerns surrounding the use of AI in education is data privacy and security. AI systems often require the collection and analysis of large amounts of student data, including learning behaviours, performance metrics, and personal information. While this data is crucial for providing personalised learning experiences and tracking student progress, it also raises significant privacy concerns.

Sensitive information, such as health records or demographic details, may be vulnerable to unauthorised access, misuse, or data breaches.

Educational institutions have a responsibility to implement stringent data protection measures to safeguard this information.

Compliance with regulations like the General Data Protection Regulation in Europe or similar privacy laws in other regions is critical. These regulations are designed to protect the privacy of individuals and ensure that organisations handling personal data do so with appropriate levels of security.

Additionally, institutions must work to build trust with students and parents, ensuring that they understand how their data is being used and what protections are in place. Ethical concerns also arise regarding consent and transparency—students and their families must be fully informed about what data is being collected and how it will be used to make informed decisions.

Human educators’ roles

As AI systems become more sophisticated, their role in classrooms has expanded from administrative support to more complex tasks like grading assignments, providing personalised tutoring, and even predicting student performance.

However, this growing reliance on AI has raised concerns about the diminishing role of human educators in the learning process. AI systems may excel in analysing vast amounts of data and delivering personalised content at scale, but they cannot replicate the emotional intelligence, empathy, and mentorship that human teachers bring to the classroom.

Human educators provide moral guidance, motivation, and emotional support to students, which are critical aspects of the learning process that AI cannot yet replace. For instance, a student struggling with anxiety or a difficult home environment may need personalised encouragement that only a human teacher can provide.

The challenge, therefore, is to strike a balance where AI enhances, rather than replaces, the role of human educators. AI should be viewed as a tool that supports teachers in their work, allowing them to focus on areas where human interaction is most valuable.

Rather than replacing teachers, AI can help reduce their workload by automating administrative tasks and enabling more personalised attention for students who need it most.

Inequity in access to AI technology

While AI promises to revolutionise education, it also has the potential to exacerbate existing inequities. Not all schools have the infrastructure, funding, or technical expertise required to implement AI-driven tools.

This digital divide is particularly stark in low-income or rural areas, where students may already face significant barriers to educational resources. Without equitable access to AI technologies, students in disadvantaged areas could fall further behind in an increasingly technology-driven world.

Governments, educational institutions, and private organisations must collaborate to ensure that AI resources are made available to all students, regardless of their socioeconomic status.

This includes investing in infrastructure, providing training for teachers on how to effectively use AI tools, and offering financial assistance to schools in underprivileged areas. Additionally, public policy should focus on reducing barriers to access and creating a more level playing field for all students.

Ethical AI use in assessment

AI-powered assessments offer the potential for more objective, data-driven evaluations of student performance. However, there are also ethical concerns about bias and over-reliance on machine-generated results.

AI algorithms are only as good as the data they are trained on and if the training data is biased or unrepresentative of diverse student populations, the resulting assessments may unfairly disadvantage certain groups.

For example, students from different cultural backgrounds, learning styles, or even socioeconomic statuses may not fit neatly into the patterns that AI systems expect, leading to inaccurate or biased assessments.

Additionally, there is the risk that educators may become overly reliant on AI-generated results, prioritising them over more holistic evaluations that take into account the whole student.

AI assessments should be viewed as one tool among many, and human oversight is essential to ensure that students are being evaluated fairly.

To address these concerns, it is critical to develop AI systems that are transparent, explainable, and regularly audited to prevent bias. AI should be used as a complement to human judgment, not a replacement.

AI holds immense promise for improving education, but its challenges and ethical considerations must not be overlooked. Addressing concerns around data privacy, the role of human educators, inequitable access, and ethical AI use in assessment will be crucial to ensuring that AI enhances rather than detracts from the learning experience.

By fostering responsible use of AI and ensuring that it is implemented with equity and fairness, educational institutions can create a future where technology empowers all students to reach their full potential.