For: Students
AI Tutor
Supports learning along the competency map, suggesting practice and giving feedback.
Limits
Does not do students’ work for them.
Strategic project 2026–2031 · AI-native Competency-Based 5T University
An AI-native universitycentred on people
DAU is not simply “adding AI” to the university at surface level. DAU is redesigning its university model to be AI-native, with people, the 5T philosophy, OBE/VQF, evidenced competence and quality at the centre.
- integrated design layers
- 9
- integrated design layers
- core Copilots
- 4
- core Copilots
- maturity levels
- 5
- maturity levels
- AI-native target
- 2031
- AI-native target
Motto
Real Substance – Real Talent – Shaping the Future
01 — Overview
A university transformation programme, not a software project
This project is not about buying a chatbot or management software. It is about turning DAU into a university ecosystem that runs on data, learning outcomes, evidenced competence and AI — while people remain the final decision-makers.
01
Technology is restructuring education
AI, big data, automation, Digital Twins, the green transition and the digital economy are changing how universities teach, learn and govern.
02
The labour market needs real competence
Learners need to prove their competence through real work and authentic evidence, not through transcripts alone.
03
Autonomy and accountability
Higher education is moving towards autonomy, accreditation and quality transparency.
04
From scale to competence
The focus of development is shifting from scale to competence, data, quality and innovation.
2006
Foundation
Nearly 20 years of growth and development.
6 years
2026–2031
A key strategic project of DAU.
Level 5
AI-native
The maturity level DAU aims to reach by 2031.
2050
Vision
5T values – Evidenced competence – Asian and global stature.
02 — Identity
Three tiers of 5T
5T is DAU’s identity, structured in three distinct tiers: a guiding philosophy, an educational approach and institutional brand values. AI-native is simply the infrastructure for realising these values.
5T Philosophy
Intellectual foundation
- T1
Tranquility
Tĩnh tại
- T2
Theoria
Tuệ giác
- T3
Tangibility
Thực chứng
- T4
Transfluency
Thông biến
- T5
Transcendence
Trường tồn
5T Education
Educational approach
- T1
Think
Thực học
- T2
Train
Thực hành
- T3
Task
Thực nghề
- T4
Test
Thực chiến
- T5
Transform
Thực sáng tạo
5T Brand Values
Hallmarks of DAU learners
- T1
Trailblazing
Tiên phong
- T2
Tangible
Thực tiễn
- T3
Thriving
Toàn diện
- T4
Togetherness
Tương tác
- T5
Trustworthy
Trách nhiệm
Operational bridges mapping 5T into data and AI
Evidenced competenceDigital responsibilityConstructive thinking
03 — Model
One integrated design, nine layers
The AI-native Competency-Based DAU model is built from nine layers, running from human values to intelligence and quality infrastructure — one integrated design, not scattered tools.
5A
Human-centred 5T
People at the centre; AI does not replace lecturers.
5B
OBE/VQF
Outcome-based education aligned with the Vietnamese Qualifications Framework.
5C
AI-Native CBE Ecosystem
Turns learning outcomes into competencies that can be observed, measured, evidenced and improved.
5D
OBE/CBE Core
The academic data backbone of the whole university.
5E
Competency Map
Competencies described as observable behaviours, linked to evidence, rubrics and proficiency levels.
5F
Second Brain & Governance
Institutional memory, Knowledge Graph and data–AI governance.
5G
AI Infrastructure Efficiency
Model orchestration and cost control; models can be swapped without breaking the underlying data.
5H
Agentic Orchestration
Orchestration of AI agents with permissions, audit trails and humans in the loop.
5I
World Models, Evidence & Quality Intelligence
Digital Twin University, Learning Analytics, Living Portfolio, PDCA/CQI and living accreditation.
04 — Copilots
Four core Copilots, one shared foundation
Agentic AI is not a single chatbot but an ecosystem of agents with permissions, controls and accountability. Each Copilot has clear limits.
For: Lecturers
Faculty Copilot
Supports course design, rubrics, learning materials and feedback to learners.
Limits
Does not replace lecturers’ professional authority.
For: Researchers
Research Copilot
Supports literature reviews, data management and the publication process.
Limits
Does not ghost-write papers or fabricate data.
For: Administration
Admin Copilot
Supports processes, reporting, quality monitoring and accreditation.
Limits
Does not make academic, financial, staffing or accreditation decisions on its own.
All four share the Second Brain, Knowledge Graph, OBE/CBE Core and Data/AI Governance.
Second Brain helps DAU remember correctly
World Models help DAU forecast better
Humans decide
05 — Maturity
Five maturity levels
Each level is a prerequisite for the next. DAU moves step by step, measuring honestly before scaling up.
01
Digitized
Số hóa
Processes and data are digitised.
02
Data-informed
Dựa trên dữ liệu
Decisions are grounded in data.
03
AI-integrated
Tích hợp AI
AI is built into core activities.
04
AI-driven
Dẫn dắt bởi AI
AI orchestrates processes; people provide oversight.
05
AI-native
The university runs on data and AI by design.
Target: reach level 5 by 2031.
06 — Roadmap
Roadmap 2026–2031
Technology follows academic goals. Each phase expands only once data and evidence are reliable enough.
First 100 days
Launch
Set up the Steering Committee, select pilot programmes, launch Second Brain v1.
2026
AI-ready & CBE-ready
Pilot the OBE/CBE Core and Competency Map; issue data and AI policies.
2027
AI-integrated & CBE-integrated
Pilot AI Tutor, Faculty Copilot and Research Copilot; roll out the Living Portfolio.
2028–2029
AI-driven CBE DAU
Expand Agentic AI; Digital Twins at student, course and programme level; living accreditation.
2030–2031
AI-native core completion
Multi-agent ecosystem, university-wide Digital Twin, lifelong learning.
After 2031
AI-native scaling & maturity
University-wide scaling and operational optimisation.
“Start small, measure honestly, improve fast, scale under control.”
Milestones are a proposed framework; moving from one phase to the next depends on the Data Maturity Index and the Evidence Authenticity Index.
Targets to 2030
Proposed targets
- Programmes reviewed against learning outcomes, the VQF and accreditation
- 100%
- Programmes reviewed against learning outcomes, the VQF and accreditation
- Students in the 2027–2030 intakes with a Living Portfolio
- ≥50%
- Students in the 2027–2030 intakes with a Living Portfolio
- Lecturers trained in OBE/VQF, rubrics and assessment
- 100%
- Lecturers trained in OBE/VQF, rubrics and assessment
- Lecturers completing AI-readiness and digital learning materials training
- ≥80%
- Lecturers completing AI-readiness and digital learning materials training
- Full-time lecturers holding a doctorate
- ≥30%
- Full-time lecturers holding a doctorate
Based on the 2026–2030 Development Strategy. Results will be published only when backed by evidence.
07 — Pillars
Seven strategic pillars
All pillars rest on a common foundation: 5T values and outcome-based education under OBE/VQF.
01
Education
Competency-based programmes, studio-based learning, Living Portfolio.
02
Science, Technology & AI
Research Copilot and a transparent publication process.
03
Community
Service learning and engagement with the local region.
04
International Cooperation & Communications
Communicating the value of investing in education and expanding partnerships.
05
Faculty & Staff
Building lecturers’ OBE capability and AI-readiness.
06
Finance & Facilities
AI infrastructure, a second campus and more diverse resources.
07
Quality & IQA
Internal quality assurance at four levels: University, Faculty, Programme and Course.
Design × Domain interdisciplinary priorities
- Smart City, Urban Design & Digital Twin
- Green Architecture & Sustainable Construction
- BIM, Construction Management & Project Finance
- UX/UI, Digital Product & Visual Communication
08 — Pilot
Architectural design studio
Pilot version
A 9-standard rubric for architectural design projects is the first pilot product. AI use is controlled and must be declared; students must demonstrate their individual competence. AI resilience is built in throughout rather than treated as a separate standard.
- TC1Concept & creativity
- TC2Identity & local character
- TC3Space & function
- TC4Planning & landscape
- TC5Building technology
- TC6Materials & construction
- TC7Green architecture
- TC8Community impact
- TC9Presentation & defence
09 — Benchmarking
Scientific basis and benchmarking
Every component of DAU’s design already has precedents around the world. The advantage therefore comes not from the AI-native label, but from the quality of integration.
- Key reference cases in Vietnam
- 76
- Key reference cases in Vietnam
- Benchmark institutions: 80 international, 20 Vietnamese
- 100
- Benchmark institutions: 80 international, 20 Vietnamese
- Geographic clusters worldwide
- 14
- Geographic clusters worldwide
- Academic and institutional criteria
- 14
- Academic and institutional criteria
Six potential advantages
- 01Coherence between values and operating mechanisms
- 02Traceability down to each competency gap
- 03Separating learning from formal recognition
- 04Common standards, flexible pathways
- 05A living competency record — Living Portfolio
- 06Interdisciplinary studios rooted in Architecture – Construction – Design
This is an assessment of design quality and potential, not a claim that DAU has already achieved superior results.
10 — Principles
Operating principles
Humans decide
Human-in-command is the governance principle; human-in-the-loop is the execution mechanism.
Academics lead
Technology follows academic goals, not the other way round.
Stable core, flexible edge
The core holds the mission, 5T, OBE/VQF and governance; the edge tests micro-credentials and interdisciplinary studios quickly.
DAU owns its core knowledge
Under a Build–Buy–Partner model, DAU retains ownership of its standards, rubrics and evidence data.
Clean data first
No early scaling before data is clean and evidence is verified.
Evidence before claims
Only implementation levels and results backed by evidence are published.
People at the centre, 5T as our identity, evidenced competence as the measure, data and AI as intelligence infrastructure, and genuine quality as a long-term commitment.