Leveraging Artificial Intelligence for Curriculum Review and Updating at Ton Duc Thang University: A Reflection from TDTU

 Participating in the InnoAIQA-VN project was a meaningful professional journey for us as representatives of Ton Duc Thang University (TDTU). The project not only provided opportunities for learning and practicing artificial intelligence (AI) with experts and colleagues from country-wide institutions, but also inspired us to leverage AI as a robust tool to enhance TDTU’s internal quality assurance (IQA) system.

Figure 1. TDTU representatives presenting the project poster at the workshop.

One of the most important lessons we have learned from the project is that AI should not be used as a “quick solution” or a replacement for human responsibility. AI can only create value when it is connected with clear processes, reliable data, ethical principles, and the real needs of users. This message was especially relevant to IQA, where evidence, transparency, and continuous improvement are essential.

Figure 2. Presenting the 5-stage implementation framework of T-CORA.

For TDTU, the project had practical impact by coaching us to develop T-CORA (TDTU Curriculum & OBE Review Assistant), an AI-supported tool for reviewing and updating study programmes. Our team combined QA expertise with technical support, tested the tool during piloting, produced user guidelines, standardized QA templates, and provided support for faculties. Beyond the technical solution itself, T-CORA has transformed our approach - fostering a more systematic, data-informed, and collaborative environment for curriculum review.

Figure 3. Discussing QA practices with cross-institutional colleagues.

The project also changed our mindset about AI governance at the institutional level. Our journey taught us that putting AI into practice goes far beyond writing guidelines; it requires building infrastructure readiness, continuous training, pedagogical reform, and a system for continuous monitoring. At TDTU, this means continuing to foster AI literacy across lecturers, staff, and students; developing a clear guidance on ethical AI use; reinforcing data security and privacy; and empowering faculties to adapt institutional policies to their specific disciplinary contexts.

Figure 4. Sharing insights on institutional AI policies.

Finally, the TDTU team wishes to express our deepest gratitude to the project organizers for their exceptional management, well-structured timeline, and highly relevant themes that perfectly aligned with our expectations. We are immensely grateful to the project team, whose enthusiasm, unwavering support, and generous sharing of profound expertise and practical experience truly inspired us.

Figure 5. Organizers, mentors, and participants at the InnoAIQA-VN Workshop.

The innovative approach of the project - moving from awareness-raising keynote speeches to hands-on experiential practices, followed by mentor-guided real-world projects and cross-institutional experience sharing - created an invaluable learning environment. Ultimately, this comprehensive initiative not only significantly enhanced our professional capacity but also successfully forged a robust network among QA teams from universities nationwide.

                                                 Vo Ngan Tho, Nguyen Thi Trieu - Ton Duc Thang University

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A Journey of Accompanying the InnoAIQA-VN Project: Spreading AI Knowledge in Higher Education Quality Assurance

 Participating in the InnoAIQA-VN project as a mentor and a member of the training team, and accompanying groups from many universities across the country, was a very special experience for me. This was not only a professional activity on the application of artificial intelligence in higher education quality assurance, but also a journey of sharing knowledge, building connections, and working together to create practical values for Vietnamese education.

The training team presented certificates to the lecturers participating in the project

Most of the lecturers participating in the project came from quality assurance units of higher education institutions. Therefore, developing AI systems by themselves to directly support their professional work was a significant challenge. Many lecturers did not have a strong background in technology, programming, or AI system design. However, this made the project even more meaningful, because the goal was not only to create products, but also to help lecturers understand, master, and apply AI in a practical, effective, and responsible manner.

The training team took a commemorative photo with the lecturers participating in the project at Vietnam National University Ho Chi Minh City (Workshop 1)

The training team and the lecturers participating in the project took a commemorative photo at Tay Nguyen University (Workshop 2)

In Workshop 1, I provided guidance on foundational topics, ranging from basic concepts of AI and ways of thinking about AI applications in work, to methods for developing a personal AI assistant for specific tasks. Throughout the implementation process, I monitored the progress of the groups, supported them in solving technical difficulties, gave feedback on their ideas, and accompanied them step by step as they completed their products. What impressed me was that, although the groups had different starting points in terms of technology, their spirit of learning, perseverance, and desire to create practical value were very clear.

Guidance on developing a personal AI system at Workshop 1

I was particularly impressed by the team from Ton Duc Thang University with their product TCORA, a tool used to review programme learning outcomes based on the OBE philosophy. The product demonstrated careful preparation, high attention to detail, and strong alignment with practical needs in programme management. The team from Pham Van Dong University also left a strong impression on me through their systematic approach, with training courses focusing on ethics and effective and responsible use of AI, despite their limited infrastructure conditions. In addition, I could clearly feel the enthusiasm and aspiration of the University of Medical Technology and Pharmacy at Da Nang team to create technology-oriented products. For Lac Hong University, where I am currently working, the two chatbot products supporting students and lecturers in community service activities showed efficiency, applicability, and the ability to quickly implement AI solutions in a university environment.

Taking a commemorative photo with the poster of Pham Van Dong University

Taking a commemorative photo with the Lac Hong University team

In Workshop 2, I presented a paper on “Data Repositories in Quality Assurance”, focusing on the role of data in supporting QA managers to retrieve information more quickly, conduct better analysis, and make more accurate decisions. Through working with the groups, I became more aware that AI only becomes truly valuable when it is connected with structured data, specific workflows, and the practical needs of users. In the field of quality assurance, building a data repository not only helps reduce administrative workload, but also contributes to forming a culture of evidence-based decision-making.

Delivering a presentation at Workshop 2

Engaging in discussions with lecturers participating in the project

As a mentor, when I reviewed the reports and products of the groups, I experienced a feeling that was difficult to describe. In each product, I could see a part of my own contribution, not as someone who did the work for them, but as someone who accompanied them, opened up ideas, and shared methods so that the groups could create their own products. This gave me a great sense of pride, because personal knowledge, when shared in the right way, can spread, be transformed into community capacity, and create values that go beyond the scope of one individual or one institution.

Attending the reception hosted by Tay Nguyen University

Taking a photo with the project mentor from Germany, Benjamin Jung

Through the project, I also had the opportunity to connect with many colleagues from different regions of Vietnam. From online discussions and technical mentoring sessions to invitations to visit universities and share my experience, I could feel that an educational community was gradually being formed around the spirit of innovation, learning, and human-centered technology application. This was one of the greatest values that the project brought to me.

Sharing professional expertise at the University of Medical Technology and Pharmacy at Da Nang

Looking back on my journey with InnoAIQA-VN, I realize that the project brought me a great deal of joy, both spiritually and through practical experience. It helped me gain a deeper understanding of how to guide lecturers without strong technology backgrounds to create AI products that serve their own professional work. More importantly, the project created connections and formed a community that supports, shares, and promotes the application of AI in higher education quality assurance.

For me, InnoAIQA-VN is not only an AI project. It is a journey of spreading knowledge, awakening the creative capacity of lecturers, and opening up a new approach to improving the quality of higher education through technology, data, and collaboration.

By Le Truong

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A Journey of Learning, Sharing, and Growing with InnoAIQA-VN

 Joining the Innovative Artificial Intelligence in Quality Assurance Management for Higher Education in Vietnam (InnoAIQA-VN) project under the DIES National Multiplication Training Programme was one of the most meaningful professional experiences I have had in recent years.

As a member of the training team, I initially saw my role as contributing knowledge and supporting participants in exploring AI applications in higher education. However, this journey became much more than training delivery—it became a shared learning experience.

What made this project special was its practical focus. AI is rapidly entering higher education in Vietnam, yet many institutions are still navigating how to use it responsibly and effectively. Through this project, we moved beyond theory and worked with participants to explore real applications in quality assurance, curriculum review, research, and academic management. Of course, the journey came with challenges. Participants came from different institutions with very different levels of digital readiness. Some had exciting ideas but limited technical confidence. Organizing activities across regions also required significant coordination and flexibility. But these challenges made the outcomes even more meaningful. The most rewarding part for me was seeing participants become multipliers themselves—organizing workshops at their own universities, training colleagues and students, and initiating collaborations across institutions. That was the moment I realized this project was not simply about AI training; it was about building a community of change agents. Personally, this experience reminded me that successful transformation in higher education is not driven by technology alone. It requires people, collaboration, institutional support, and a willingness to learn together.

As this chapter closes, I believe the impact of InnoAIQA-VN is only beginning. The conversations, collaborations, and ideas created through this project will continue to grow—and I am grateful to have been part of that journey.

By Thuy Nguyen

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