AI technology is rarely out of the news these days. From chatbots to image generators, we now have a wide range of tools at our fingertips, many of which have useful applications in education. One of the key ways AI can make educators’ lives easier is by helping deliver fully personalized learning that can motivate, engage, and help students make more progress. However, as AI becomes more prevalent, many now recognize there can be ethical and practical pitfalls. As a busy educator, you may also lack time to research the latest technologies.
So, how can you bring tech-driven personalized learning to your school in a way that balances the risks and benefits? To help cut through the noise around AI, we’ve put together this guide on how AI personalized learning can benefit your students and some easy ways to get started.
Although forms of artificial intelligence (AI) have been around for some time, the technology race has ramped up over the last few years, with a range of exciting tools and frequent updates bringing new developments to an increasingly wide audience. The impact on education is already significant and certain to expand in both scope and scale.
The biggest shift so far is down to AI’s ability to make administrative tasks quicker and more efficient. EdTech solutions like the TAO assessment platform can automate grading and data analysis, saving valuable teacher time.
Generative AI tools can also help produce lesson plans, as well as new texts for reading, math exercises, test questions, or feedback comments in just a matter of minutes. Students can also interact with AI in the form of a helpful guide to support them in working through problems. AI programs can additionally help schools collate and analyze data about student performance more efficiently.
However, we must acknowledge the limitations to date. For many educators, embracing AI means building new tech skills and navigating uncertainties around generative AI’s accuracy and potential biases. Schools may also have concerns about students becoming overly reliant on AI and feel trepidation around how to use it in an ethical and balanced way.
Studies show that personalizing learning for each student can promote higher academic performance and enhanced motivation. This makes sense: personalized learning tailors teaching materials for each student’s level and needs, aims to make subject content highly relevant, and gives students agency in making choices and working at their own pace.
One common method is to group students according to level and need, and assign different tasks for each group. You might also give students a menu of exercises to choose from—I always liked using a “spice level” metaphor to help them pick their own level of difficulty. Asking students to set and review their own goals, or complete regular surveys of their interests, can also help make learning feel more personalized.
However, preparing multiple exercises and different resources for each class can be time-consuming and difficult to sustain. Giving students more agency may be more motivating, but it also requires you to be everywhere in the classroom at once so you can respond to queries. That’s where AI can significantly reduce stress for teachers, giving you more time to focus on supporting students.
Different types of AI technologies can support personalized education. These include:
Machine learning is a technology that enables AI software to learn from datasets and improve over time. This is important for education as it means the platform can respond to student input and provide meaningful support without needing explicit programming in each level of study.
This allows the AI software to understand and respond in natural, human language, rather than code. This is important in the classroom, as it lets students interact with platforms through written or spoken language, enabling them to chat or ask questions as they would with a teacher.
An adaptive system can adjust the level of difficulty, content, and style of teaching and assessment material as students move through it. It can respond based on how the students answer questions in real time.
Using AI for personalized learning comes with some risks and challenges:
The benefits of using AI to power personalized education can include:
Personalized material meets students at the right level to avoid boredom (when it’s too easy) or overwhelm (when it’s too hard). Plus, interactive AI features make students feel motivated through close support and the sense of having a personal tutor standing by them.
Getting immediate and targeted feedback also quickly addresses misconceptions, and students build responsibility for their learning by improving their work. Delivering this digitally makes it possible to be even faster and more reactive than if you had to run around the classroom!
You no longer need to spend hours creating multiple versions of the same exercise or setting and marking test questions to get an idea of student progress. AI frees up educator time by rapidly generating materials, guiding students through adaptive pathways, and giving them explanations.
You can then spend more time giving 1:1 support to those who need it, observing student behavior, or diving into data to inform your next lesson.
Whether you’re collecting data from an AI-enhanced assessment platform or feeding digital assessment data into a learning management system with AI features like Schoology, new tools can help you analyze student performance in moments.
You can identify trends in student progress over time or find out which students are at risk of underperforming. This can help you make data-driven decisions without needing to crunch numbers.
While you can use AI in many exciting ways for customized learning, here are a few notable examples.
The latest wave of generative AI tools from OpenAI (ChatGPT), Anthropic (Claude), or Google (Gemini), among many other examples, can whip up worksheets and tasks in moments.
Just prompt the AI with the type of task, the different levels (even 1 per student if you really want to get personalized), and any other requirements, such as length and format. Or, create multimedia materials like images and videos that can help make your teaching feel more creative and relevant.
Generative AI tools and chatbots can be a great way for students to seek support and feedback without needing to come to you. This gives them more agency and responsibility as they move through their work at their own pace.
A tool like UpStudy is a good example: it’s specially designed as a “homework helper” to break down complex problems. Students can even photograph their paper math problems for a helpful explainer.
One step up from providing different resources for different levels, adaptive tech guides students along different learning paths, assigning questions at the right difficulty and pace as they get things right or wrong. Khan Academy’s adaptive programs for math and other subjects also have an AI element in the form of interactive tutor Khanmigo. DreamBox Math uses AI to tailor questions to each student’s ability level.
If one thing’s certain, it’s that AI will continue to develop as a powerful force in education. We’re likely to see AI powering more advanced personalized learning tutors and giving more detailed and responsive feedback. There will also be more predictive analytics tools to identify students who need support from the very start, as well as tools specifically designed to help teachers generate suitable content, integrating the relevant educational standards.
We will also see new strands of pedagogy emerge to help educators and leaders navigate the new world of AI and integrate it successfully into the classroom—while maintaining the integral role of the teacher.
Personalized learning benefits students by boosting engagement and driving higher results, but it can be time-consuming to execute. AI tools can significantly cut the time and effort needed to personalize by making tasks like content generation, grading, and delivering adaptive teaching incredibly quick and easy. This leaves you more time for 1:1 support and detailed, data-driven planning.
As a next step, you might want to explore other ways to approach AI in the classroom, from checking student work for plagiarism to considering the impact on test results via cheating. You may also find our guide to AI ethics in education useful when planning a balanced approach to tech in the classroom.
An important part of personalizing learning is keeping track of student progress over time, so you can step in to plug the gaps.
Digital assessment via a dedicated platform like TAO can help you deliver frequent and engaging online testing that boosts student progress, giving you and your students immediate feedback on their performance. You can also make the tests adaptive to increase or decrease in difficulty to meet your students’ needs.
For more information on how TAO can help you deliver customizable, adaptive digital assessments that can highlight each student’s needs, schedule a demo.
Traditional personalized teaching varies learning materials for different levels, provides students with elements of choice, and analyzes data to understand each student’s needs, but all of these things can be time-consuming. AI personalized learning can be much quicker and easier to deliver, saving time for the teacher to give more 1:1 support.
AI can replace some jobs for the teacher in personalized learning: it can give rapid feedback, walk students through explanations, and grade tests. But it can’t replace the element of human interaction that can be vital for many students’ understanding, communication skills, and sense of motivation.