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RESPONSIBILITIES OF LECTURERS IN USING AI TOOLS IN TEACHING
AND SCIENTIFIC RESEARCH
Pham Thi Hang, M.A.
Lecturer
Ho Chi Minh City Branch of the National Academy of Public Administration
Email: hang2407dhnv@gmail.com
Phone: 0385.515.919
Abstract: In the current digital transformation context, artificial intelligence (AI)
technology plays an important role not only in optimizing automated processes but also in
bringing significant opportunities and challenges to lecturers in teaching and scientific
research. Lecturers must not only master AI tools but also have the responsibility to protect
ethical principles, transparency, and fairness in using this technology. This article analyzes
some of the responsibilities of lecturers when applying AI to teaching and research, and
based on several proposed solutions, the article also boldly proposes a roadmap for AI
application in Vietnamese higher education for the period 2025-2030.
Keywords: Lecturers, AI tools, teaching, scientific research, AI ethics, digital
transformation.
I. PROBLEM STATEMENT
In the context of rapidly developing society and education, artificial intelligence (AI)
technology has become an indispensable tool in teaching and scientific research activities.
The application of AI not only creates opportunities to improve educational quality but also
sets new requirements for lecturers. The responsibility of lecturers, therefore, is not limited
to effectively adopting and using technology but also ensuring compliance with ethical
principles, protecting the rights of students and learners, while maintaining transparency in
all academic processes. This is a decisive factor in ensuring the fairness and effectiveness of
AI in the educational environment.
II. RESEARCH METHODOLOGY
1. Document Selection Criteria
Selected documents include studies published from 2019-2024, official reports on AI in
education, and relevant Vietnamese legal documents.
Priority is given to empirical research, systematic reviews, and AI application policies.
2. Analysis Process
Step 1: Search and collect documents from Scopus, Web of Science databases, and official
websites.
Step 2: Screen according to title, abstract, and keywords criteria, eliminating duplicate and
irrelevant documents.
Step 3: Categorize by topic: teaching, scientific research, legal framework, and application
roadmap.
Step 4: Analyze content using systematic review methods, establishing commonalities,
differences, and policy recommendations.
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3. Research Scope
Focus on analyzing from the perspective of lecturers' responsibilities at universities and
academies in teaching and scientific research with AI tools.
III. RESEARCH CONTENT
1. Responsibilities of lecturers in teaching with AI tools
1.1. Innovating teaching methods
The application of AI tools in teaching is not merely about adopting technology but also
about transforming teaching methods, helping to create a more flexible and interactive
learning environment. Lecturers have the responsibility to integrate AI into traditional
teaching methods to optimize students' learning processes, while ensuring personalization in
accessing knowledge, thereby improving learning and teaching effectiveness.
According to a study by Azizi and colleagues (2021), AI has demonstrated the ability to
support lecturers in adjusting content and teaching methods to suit each student's
capabilities and learning needs. For instance, adaptive learning systems help adjust learning
content according to each student's progress, bringing higher learning efficiency compared
to traditional methods.
In Vietnam, four universities participate in the project "Expanding educational access
through AI application in teaching in Vietnam," namely Ho Chi Minh City University of
Education, Hanoi National University of Education, Vinh University, and University of
Education - Vietnam National University, Hanoi (VNU). This is an interdisciplinary project
aimed at promoting digital transformation in Vietnam, as well as focusing on developing
activities for teachers and students from different regions on using AI tools for teaching and
learning. The project applies three specialized tools: conversational AI, large language
models, and multimodal emotion recognition systems to experiment with teachers and
students at six public schools in Vietnam. (Le Van, 2024)
In addition, there are several other universities in Ho Chi Minh City and Hanoi that have
collaborated with corporations and technology companies to develop initiatives in the AI
field. Among them, Fulbright University Vietnam, Ho Chi Minh City University of Industry
and Trade (HUIT), and RMIT University are currently leading in implementing AI into
teaching curricula, research, and international cooperation. (Hai Yen, 2024)
Specifically, RMIT Vietnam and VNU have launched a new research cooperation program,
focusing on AI and semiconductor technology. More than 20 researchers and leadership
representatives from both schools have discussed pilot projects, focusing on these two
strategic areas. (Hai Yen, 2024). Adaptive learning systems use AI to adjust learning content
according to each student's needs and abilities, allowing each student to maximize their
potential. Personalizing the learning experience not only helps students learn more
effectively but also creates a learning space that suits the pace and style of each individual.
Moreover, this is an important factor in enhancing interaction between lecturers and
students, as well as between students and learning tools.
1.2. Protecting privacy and ensuring information security
One of the important responsibilities that lecturers must fulfill when using AI technology in
teaching is ensuring security and privacy for students. AI tools often require collecting and
processing a large amount of personal data from learners, hence lecturers need to be
responsible for protecting this information.
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According to research by Johnson and colleagues (2020), information security and student
privacy are issues that need special attention when using AI technology in education. The
collection and analysis of student learning data must comply with legal regulations on
personal data protection, such as the General Data Protection Regulation (GDPR) of the
European Union.
Some advanced online learning systems have applied strict security measures, such as data
encryption and protection of students' personal information, to prevent risks from
unauthorized use of data. For example, online learning platforms like Coursera and edX
have implemented advanced security measures to protect learner information, while
committing to comply with the European Union's data protection regulations (GDPR).
Protecting students' personal information is not only a legal responsibility but also a factor
that helps maintain students' trust in technological tools in education. At the same time,
information security is also a way to minimize the risks of abuse and violation of learners'
privacy.
2. Responsibilities of lecturers in scientific research with AI tools
2.1. Improving research quality
Lecturers have responsibilities not only in applying AI to teaching but also in exploiting AI
tools to optimize scientific research processes. AI can assist lecturers in processing and
analyzing big data, thereby helping to draw accurate conclusions with practical value.
According to a study by Krittanawong and colleagues (2021), AI can assist lecturers in
detecting hidden data patterns in medical research, analyzing data from previous studies, or
even making predictions about research results based on machine learning algorithms. This
not only saves time but also improves accuracy in research results.
Research using AI in medical image analysis has helped improve effectiveness in disease
diagnosis. For example, AI is used to analyze X-ray and MRI images, helping to detect early
signs of cancer that doctors might miss.
In healthcare research, AI has been used to analyze patient data to detect signs of disease,
helping to make predictions about health risks. Research using AI not only saves time but
also enhances accuracy in medical analyses, such as applying AI in analyzing medical
images for cancer diagnosis.
AI not only helps reduce research time and costs but also helps researchers access complex
analytical methods that previously could only be performed by experts. This creates
opportunities to promote innovation and creativity in scientific research.
2.2. Ensuring ethics and transparency in research
One of the important requirements when using AI in scientific research is ensuring
transparency and adherence to ethical principles in collecting, processing, and publishing
research data. Lecturers need to commit that the AI tools used must be clear about the
source and method of data processing, while avoiding issues related to bias or manipulation
of research results.
Scientific journals now require authors to clearly disclose data analysis methods, including
AI tools used, to ensure transparency in the research process. For example, studies
published in journals like Nature and Science require authors to detail how data is collected
and processed, including the AI algorithms applied.
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Transparency in using AI in research not only helps ensure the reliability of research results
but also helps build trust with learners and the scientific community.
3. Some solutions to enhance lecturers' responsibility when using AI tools in teaching
and scientific research
3.1. Building a clear legal and ethical framework for AI use
One of the first and most important solutions to enhance lecturers' responsibility when using
AI tools in teaching and research is for the State to develop and issue a clear legal and
ethical framework. Although AI technology is no longer a new concept, to date our State has
not issued specific legal regulations as well as sanctions for violations related to AI
applications. Therefore, in the coming time, it is necessary to develop and issue a separate
law on AI to ensure that AI use takes place responsibly and protects the interests of related
parties. In addition, universities need to develop and issue regulations on the use of AI in
teaching, research, and academic management. These regulations include ethical principles
such as protecting student privacy, ensuring transparency in data use, and preventing the
abuse of AI technology. Ethical regulations in AI use will help lecturers have specific
guidelines to maintain fairness and transparency in the teaching process. Having a clear
legal framework will help lecturers ensure that they not only comply with current
regulations but also maintain the trust of students and the scientific community.
3.2. Training and enhancing lecturers' capacity in AI use
Lecturers need to have solid knowledge about AI technology to be able to apply it
effectively in teaching and scientific research. To accomplish this, universities need to
organize training courses, workshops, and in-depth training programs on AI for lecturers.
These courses not only help lecturers become familiar with AI tools but also equip them
with the necessary skills to understand and solve ethical and legal issues when using AI.
Studies have indicated that lecturers in Vietnam still face many difficulties in using AI due
to lack of knowledge and proper training. Therefore, providing AI training programs will be
a decisive factor in helping lecturers enhance their capabilities and ensure the correct and
effective use of this tool in education.
3.3. Enhancing transparency and openness in the process of using AI
Another important solution is to enhance transparency and openness in the process of using
AI tools in teaching and research. Lecturers need to clearly disclose how AI is used, what
data is collected, and how AI tools will assist in improving teaching and research quality.
This helps students and other researchers better understand the process of using AI and can
accurately evaluate the results.
According to Binns & Sood (2021), transparency in AI use not only helps ensure accuracy
in research results but also builds trust with learners and the scientific community.
Disclosing methods and data related to research helps lecturers maintain objectivity and
ensure that no external factors affect research results.
3.4. Enhancing responsibility in protecting privacy and personal data
Lecturers need to be aware of their responsibility in protecting student privacy and personal
data when using AI tools. AI tools in teaching and research often require collecting and
processing a large amount of data. Therefore, securing personal data of students and
research participants is very important. Lecturers must ensure that collected data is used
reasonably and only for teaching or scientific research purposes.
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A study by Johnson et al. (2020) points out that protecting personal data is one of the most
important factors in applying AI in education. Failure to ensure information security can
lead to serious consequences such as violating student privacy and affecting the reputation
of educational institutions.
3.5. Encouraging research and development of AI tools suitable for specific educational
needs
Universities should encourage lecturers to participate in research and development of AI
tools suitable for the specifics of education. This not only helps improve teaching and
research quality but also ensures that the AI tools developed and used will meet the right
needs and requirements of the educational environment. Encouraging lecturers to participate
in the AI development process will also help them gain deeper insight into the challenges
and opportunities when using this technology. Developing domestic AI tools can help
lecturers solve specific problems in the education system, thereby enhancing the
effectiveness of technology use and maximizing the potential of AI in education.
3.6. Enhancing support roles from schools, students, and the Government
To avoid the situation where lecturers have to bear all responsibility when applying AI, there
needs to be close and synchronous support from three stakeholders. On the School side,
they need to proactively invest in building the necessary technical infrastructure and
software systems, while issuing professional training policies and clear regulations on
standards and processes for using AI in teaching and research. On the Student side, they
should be encouraged to provide constructive feedback through survey tools and discussion
groups, while strictly adhering to ethical rules and regulations on data security when using
AI platforms. On the Government side, it plays a key role in establishing a transparent
legal framework, allocating financial resources for AI application research projects, and
promoting public-private cooperation through support programs, thereby creating a solid
legal and financial environment. The harmonious coordination between schools, students,
and the government not only ensures that the AI application process takes place safely and
transparently but also contributes to improving the quality and effectiveness of sustainable
higher education.
IV. SUGGESTED ROADMAP FOR AI APPLICATION IN HIGHER EDUCATION
AT VIETNAMESE UNIVERSITIES
1. Phase 1 (2025-2026):
o Completing internal legal frameworks and school policies;
o Building basic IT infrastructure; piloting adaptive learning systems.
2. Phase 2 (2027-2028):
o Expanding the model to faculties and specializations;
o Training lecturers and students on AI and data management;
o Establishing AI laboratories applied in research.
3. Phase 3 (2029-2030):
o Evaluating and improving processes based on feedback;
o International cooperation, publishing research results;