AI as a Personal Tutor to aid Pupil Learning

I want to launch straight into this post today, because it is one that interests me to a high level (enough to want to do a PhD on it). AI as a personal tutor!

As every educator should now know, AI is an emerging field as far as its applications to various industries go. Every day there is news that shows AI launching blistering cyber attacks on unsuspecting companies, or about how it’s going to replace all our jobs (thanks Elon). But today, is a good news day! I want to look at how we can use AI as a personal tutor and help our students to use AI in a way that is positive and has a good impact on learning!

A recent study published in Scientific Reports found that students who learned with AI as a personal tutor achieved significantly better results than students participating in traditional in-class active learning activities. The research is notable because it was conducted in a real university setting using a randomised controlled trial (RCT), one of the strongest methods for evaluating educational interventions.

Researchers compared two groups of students:

• One group used AI as a personal tutor designed around established learning science principles.
• The other group took part in conventional active learning classroom activities.

The results showed that students using the AI tutor demonstrated greater learning gains than those in the active learning group. This suggests that a well-designed platform to use AI as a personal tutor can provide highly effective personalised instruction at scale.

The study highlights that the success of the AI tutor was not simply due to the use of AI. The system was carefully designed using evidence-based educational practices, including:

• Personalised feedback
• Interactive questioning
• Guided problem solving
• Continuous adaptation to individual learner needs

These features mirror many of the benefits traditionally associated with one-to-one human tutoring.

Many other studies on AI in education have taken place in a controlled laboratory environment. This research is noteworthy because it tested the technology in an educational environment with real students and real course requirements. This makes the findings more relevant for schools, colleges, and universities considering adopting AI-supported learning tools and much easier to replicate due to its real world settings.

These findings make the research a valuable contribution to the growing evidence on educational chatbots in education. They also complement a recent meta-analysis of pedagogical approaches to AI chatbots, which suggests that learning benefits depend heavily on how chatbot activities are designed.

We should also spend some time focusing on how PS2 Pal was designed. Students did not simply receive access to a general-purpose chatbot (like Gemini Notebook or ChatGPT). The researchers created a fixed instructional sequence, supplied pre-recorded explanations, wrote question-specific prompts, and embedded expert-authored solutions so the model could provide more accurate guidance.

The AI tutor was instructed to promote active engagement, manage cognitive load, and encourage a growth mindset. To put it another way, the programme was structured to combine conversational AI with a substantial level of human pedagogical judgment. This might not be the norm among AI platforms, but it will certainly contribute to future implementations of AI in this context.

We should have an element of caution with this research. The study only covered two short lessons within one course at one institution. The tests measured learning immediately after instruction rather than exploring the impact AI can have on delayed retention and retrieval. The tasks emphasised understanding, application, and analysis more than complex synthesis or sustained critical thinking. While there is much in this research to be excited about, there is also much work that is still required before there is a mainstream application of AI that can implement this type of instruction automatically.

The findings suggest that using AI as a personal tutor could move towards addressing some of education’s biggest challenges:

• Providing personalised support to large numbers of learners
• Supplementing limited teaching resources
• Improving student engagement and achievement
• Offering additional support outside classroom hours

Of course, at no point is the study suggesting that AI can replace teachers. Instead, it points toward a potential future opportunity where AI can act as a powerful teaching assistant, enabling educators to focus more on mentoring, facilitation, and higher-level learning activities. It can also work in the spaces that teachers cannot naturally inhabit – outside of school-evenings, weekends and holiday periods, home study (prior to exam periods), homework assistance (not giving the answers of course), and additional assistance/learning programmes.

Moving AI from a passive answer generator to a true 1:1 personal tutor for pupils requires shifting from prompting to systematic pedagogical design. Both Google Gems and Microsoft Copilot(via Copilot Agents) provide the infrastructure needed to create dedicated, persistent AI tutors.

To turn this concept into a practical reality, deployment must focus on structured framework design, grounding with trusted materials, and embedding within existing classroom workflows:

1. Designing the persona: Using a Socratic core over direct answers
2. Grounding the AI in a trusted curriculum (preventing hallucinations and keeping the AI focused on curriculum-relevant content)
3. Integrating with platform ecosystems
4. Building key guardrails and embedding best practices from the research

This study – within a specific context- provides strong evidence that a thoughtfully designed platform using AI as a personal tutor can outperform traditional active learning approaches. As AI tools become increasingly more sophisticated, they may play an increasingly important role in creating personalised, effective learning experiences while complementing, rather than replacing, human teachers.

The potential scope of application in using AI as a personal tutor, particularly in the context of delivering an equity of experience, can be significant. Not all parents can afford to pay for tutors for their children. With the right setup, boundaries and pedagogical structure, an AI tutor could offer a very strong service and a set of results (that is now visible through the research) that can improve exam outcomes for students.