How Nanyang Polytechnic’s AI Tutor Assistant is reshaping asynchronous learning

As students advance through higher education, institutions increasingly adopt asynchronous learning methods to promote independent and self-directed study. The shift toward blended and asynchronous learning has created both opportunities and challenges for post-secondary education. As students gain greater flexibility in how and when they learn, institutions must rethink how support can be delivered beyond the classroom.

Established in 1992, Nanyang Polytechnic (NYP) is a post-secondary education institution in Singapore that offers quality education and training through full-time diploma courses and common entry programs for post-secondary education, and a wide range of continuing education and training options for adult learners.

This post examines how NYP and NCS—an Amazon Web Services (AWS) Generative AI Competency partner and part of AWS Generative AI Innovation Center (GenAIIC) Partner Innovation Alliance (PIA)—reshaped asynchronous learning through an AI Tutor Assistant. The solution enhances student learning while reducing lecturers’ preparation time by 80%, demonstrating the transformative potential of generative AI in education.

Background

Students in hybrid or online settings often struggle with motivation and conceptual understanding when they lack the interactive support that they typically receive in a traditional classroom learning environment. While AI-powered tools have emerged as a novel and useful way to address these challenges, many students find these tools effective at answering factual queries but not able to provide support and guidance on deeper thinking or knowledge exploration—creating the perception of an isolated and impersonal learning experience.

At the same time, the nature of asynchronous learning can present educators with challenges. With students learning independently across different schedules and paces, lecturers often lack feedback from direct engagement to identify knowledge gaps as they emerge. This makes it difficult to track individual learning progress and intervene effectively for the students who require further support and guidance.

These intersecting challenges highlight a critical need in the higher education classrooms: a smarter, more responsive solution that empowers students in their learning journey and equips lecturers with the tools to monitor and guide students more effectively.

Solution

In collaboration with NCS, NYP piloted the AI Tutor Assistant using Amazon Bedrock for the IT Governance Risk and Compliance module. The AI Tutor Assistant taps into the learning resources provided by NYP to respond to student queries in real-time. The AI Tutor Assistant utilizes the Retrieval-Augmented Generation (RAG) technique through Amazon Bedrock Knowledge Bases so that its responses are based on the learning material provided. This prevents potential AI hallucinations, ensuring students engage exclusively with content aligned to their syllabus.

For students

The AI Tutor Assistant equips students with the right toolkit to study effectively, with natural-language responses grounded in the learning resources from their courses—providing them with relevant content for study. Beyond simply answering queries, the AI Tutor Assistant also suggests the top three frequently asked questions for students who might find it difficult to formulate questions themselves. The AI Tutor Assistant is used by 59% of students in the pilot to clarify concepts when studying or for assistance in completing assignments.

Using prompting techniques to incorporate pedagogical concepts such as Bloom’s Taxonomy, the AI Tutor Assistant aims to deepen students’ understanding of the lecture content by generating higher-order questions to guide students.

Many students begin their learning journey in a subject by asking basic factual questions, such as “What is IT governance?”—as this practice allows them to establish foundational understanding in the subject. While these recall-level questions are valuable, deeper conceptual mastery and long-term retention often require active engagement with higher-order thinking. After explaining the concept of IT governance, the AI Tutor Assistant will suggest the student to ask, “Why is it important for IT governance to be implemented?”

By scaffolding questions from simple recall to critical analysis, the AI Tutor Assistant actively guides students to delve deeper into subjects—fostering critical thinking, conceptual understanding, and improved knowledge retention. The AI Tutor Assistant was found to be helpful by 52% of students in guiding them to move beyond memorization and develop the analytical skills vital for academic and professional success.

Another challenge students face with asynchronous learning is assessing their progress and development. The AI Tutor Assistant lets students create customized self-assessment tests that help them measure, track, and improve on their mastery of the subject. This is one of the most popular features of the AI Tutor Assistant, used by 67% of students.

From the moment students engage with their course content to the point where they assess their own understanding, the AI Tutor Assistant is able to support students in the various learning phases in an asynchronous learning context, with 82% of students recommending the usage of the AI Tutor Assistant.

For lecturers

When students engage with the AI Tutor Assistant, the system actively captures all their queries in the background. These questions are then categorized using generative AI to identify patterns in student understanding. By analyzing this data, the solution surfaces valuable insights on topics that are frequently misunderstood or commonly asked about, helping lecturers pinpoint areas where students may need more guidance.

These insights are presented in an intuitive, easy-to-navigate dashboard that enables lecturers to adjust their lesson plans, identify specific concepts they need to reinforce, and provide targeted support to students who need it most. Within the dashboard, lecturers also have the option to export the collected data to perform further analysis, enabling deeper exploration of learning gaps and student engagement trends.

As a result, lecturers reported that they achieved 80% in time savings in lesson preparation and administration by using the AI Tutor Assistant.

Conclusion

The pilot experience of the AI Tutor Assistant at NYP offered significant lessons in using AI to address the challenges of asynchronous learning in higher education. By combining AI-powered assistance with pedagogically sound principles, the solution has successfully created a more engaging and effective learning environment for students while empowering lecturers with valuable insights into the learning process.

The impressive adoption rates and positive feedback—with 82% of students recommending the solutions and lecturers reporting 80% time savings—demonstrate that AI can meaningfully enhance educational outcomes when thoughtfully integrated with existing teaching frameworks. The solution’s ability to promote higher-order thinking, provide personalized support, and enable data-driven teaching decisions has effectively bridged the gap between the flexibility of asynchronous learning and the need for interactive, guided education.

Looking ahead, this pilot experience points to a future where AI-assisted learning will become an integral part of higher education—not as a replacement for human educators, but as a powerful tool that enhances the teaching and learning experience. As educational institutions continue to evolve their approach to asynchronous learning, solutions like the AI Tutor Assistant will be crucial in ensuring that technological advancement serves the fundamental goals of education: fostering deep understanding, critical thinking, and student success.

Learn more about how AWS Generative AI Innovation Center and AWS partners like NCS help institutions build, deploy, and scale automated AI solutions that address higher education needs. Contact AWS today.