Published: Nov 18, 2025
Reimagine asynchronous learning experience with Nanyang Polytechnic through AI
Key takeaways
- Reimagined asynchronous learning through AI tutor assistant
- Drove student engagement and critical thinking integrating pedagogy into AI
- Equipped lecturers with data-driven insights to identify and support students early
- Improved teaching efficiency and lesson planning
The background
The shift towards 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.
Students in hybrid or online settings often struggle with motivation and conceptual understanding when they lack real-time support. While AI-powered tools have emerged as a sustainable and novel way to close this gap, many students still find them impersonal, as they are better at answering factual queries than guiding deeper thinking or exploration.
Educators face parallel challenges. With students learning independently across different schedules and paces, lecturers often lack the tools to monitor real-time engagement or identify knowledge gaps as they emerge. This makes it particularly difficult to track individual learning progress or intervene effectively when misconceptions arise.
These intersecting challenges highlight a critical need in post-secondary classrooms: a smarter, more responsive way to empower students in their learning journey while equipping lecturers with the tools to guide them more effectively.
The solution
In collaboration with NCS and AWS GenAI Innovation Center (GenAIIC) Partner Innovation Alliance (PIA) team, Nanyang Polytechnic (NYP) launched a pilot for an AI Tutor Assistant developed on Amazon Bedrock. The AI Tutor Assistant taps into the learning resources provided by NYP to respond to student queries in real time. It also helps students with their assignments and deepens their understanding by suggesting higher-order questions. This has reimagined the teaching and learning experience for both lecturers and students.
The AI Tutor Assistant utilises the Retrieval-Augmented Generation (RAG) technique to ensure that its responses are grounded in the learning material provided. This prevents potential AI hallucinations and ensures that students engage exclusively with content aligned with 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 course, 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.
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. This encourages students to move beyond memorisation and proceed to analyse, evaluate, and apply the content they are learning – fostering critical thinking. Finally, the AI Tutor Assistant can also generate MCQ tests that allow students to assess their own progress.
From the moment students engage with their course content to the point where they assess their own understanding, the AI Tutor Assistant transforms how NYP students adapt to asynchronous learning. By offering timely guidance, personalised prompts, and self-assessment tools, it redefines how students interact with their learning materials.
For lecturers
While students engage with the AI Tutor Assistant, the system actively captures all their queries in the background. These questions are then categorised using GenAI to identify patterns in student understanding. By analysing this data, the platform surfaces valuable insights on topics that are frequently misunderstood or commonly asked about, helping lecturers pinpoint areas where students may be struggling.
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.
The impact
Through the pilot, the outcomes are significant:
- Improved test preparation process for students
A significant majority of students find the AI Tutor Assistant to be very useful for preparing for their tests, highlighting its positive impact on their study and revision experience. - Increased efficiency in lesson preparation for lecturers
Lecturers experienced a reduction in time spent on lesson preparation and administrative tasks, allowing them to focus more on engaging students and refining their teaching methods. - Insights on commonly asked topics to improve lesson planning
The AI Tutor Assistant empowered lecturers to enhance their lesson planning by offering valuable insights into the topics students were most frequently curious about, enabling more targeted and responsive teaching.