Control point inflation and promote the integration of artificial intelligence in higher education.
The Ministry of Education and Training has just issued guidelines for implementing tasks in the 2026-2027 academic year for higher education and teacher training colleges, which set out requirements for innovation in governance, admissions, and training programs; strengthening the application of AI, controlling grade inflation, and linking training with the human resource needs of the labor market.
For the 2026-2027 academic year, training institutions will be required to evaluate results based on specific products, the level of achievement of objectives, and the efficiency of resource utilization.
Regarding admissions, the Ministry of Education and Training requires schools to complete the 2026 admissions process in accordance with regulations, while also reviewing the 2027 admissions plan to ensure stability, transparency, simplified admission methods, and fairness and substance.
The number of students to be admitted must be determined based on faculty, facilities, output quality, and human resource needs. Schools need to compare the academic results of each group of admitted students to use as a basis for adjusting their admission plans.
The Ministry of Education and Training also requested a review and update of training programs, prioritizing strategic technology fields. Learning outcomes should integrate digital knowledge and skills, innovation capabilities, and AI applications into undergraduate, master's, and doctoral programs; eliminating, integrating, or replacing outdated content, while equipping learners with independent, critical, creative thinking, professional ethics, and responsibility when using AI.
Interdisciplinary and cross-disciplinary programs, especially in STEM fields, are encouraged, focusing on areas such as information and communication technology, AI, semiconductors, automation, biotechnology, and green energy. Businesses and professional associations are encouraged to participate more actively in identifying workforce needs, establishing learning outcomes, designing programs, and organizing training.
Universities are also required to diversify their training methods, pilot digital higher education models, increase learning through research, projects, and practical experience; and continue to develop open online courses for the general public, prioritizing content on digital skills, AI, and areas of strength for sharing and common use throughout the system.
Furthermore, a notable requirement for the new academic year is to strengthen substantive quality control. Training institutions must analyze the distribution of course grades, learning outcomes, and graduation classifications for each major, course, and training format; compare them with output standards and feedback from businesses to detect, investigate, and address grade inflation.
The Ministry of Education and Training clearly states that it will not impose quotas on grades or graduation rates for excellent or outstanding achievements; nor will it lower standards to increase performance. Schools must review exam papers, projects, theses, and evaluation evidence; and complete reports on grade inflation control and improvement results before the end of the school year.
At the same time, schools must conduct post-audits of admissions, evaluate learning outcomes, issue diplomas, assess faculty qualifications, training locations, and the use of AI; they must clearly define the scope of permitted AI use, reporting obligations, methods for verifying students' actual contributions, and handling academic fraud.
In scientific research, the Ministry requires a focus on quality, applicability, and social impact, rather than chasing the quantity of publications; increased control over scientific integrity and intellectual property; and prioritizing scholarships and research support for master's and doctoral students in STEM fields.
To meet the human resource needs of emerging fields, training institutions are required to accelerate high-quality human resource training programs in information and communication technology, cybersecurity, AI, semiconductors, automation, nuclear power, high-speed rail, advanced materials, biotechnology, and green energy; develop STEM talent programs, AI-intensive programs, and interdisciplinary AI+X and X+AI programs that are appropriate to their capabilities and quality assurance conditions.
Another key task is to innovate university governance. Educational institutions must complete the review and submission for approval or adjustment of their development strategies before December 31, 2026; build a modern governance system based on digital technology and AI; streamline internal governance structures, reducing the number of departments and intermediate management levels. The Ministry also requires a review and elimination of as many unnecessary administrative procedures and internal processes as possible, reducing intermediate approval steps and digitizing all eligible procedures.
Data continues to be identified as the foundation of university governance. Universities must complete the connection with the Higher Education Database System (HEMIS), managing data according to the principles of "accuracy, completeness, cleanliness, viability, consistency, and shared use"; cross-checking data on enrollment, students, faculty, programs, finance, research, degrees, and employment. The head of the institution is responsible for the accuracy and consistency of the data.
The Ministry of Education and Training requires schools to issue implementation plans in 2026 based on the principles of clear tasks, clear responsibilities, clear timelines, clear outcomes, and clear authority. The head of the institution will directly supervise and conduct periodic inspections, prioritizing products related to data management, grade inflation control, integrated AI programs, business collaboration, and procedural streamlining.
According to VNA