Thứ Tư, 30 tháng 7, 2025
InnoAIQA-VN Project Participates in DAAD ToT Workshop in Germany
Thứ Bảy, 4 tháng 1, 2025
AI Pedagogy: Rooted in Pedagogy, Centered on Humans
In modern education, as technology advances rapidly, AI
(Artificial Intelligence) has become an essential tool in teaching and learning
activities. However, for successful AI integration, we must always remember the
principle: “rooted in pedagogy, centered on humans.” This means that AI is a
means to serve educational goals, while the core remains the pedagogical
methods and the interaction between educators and learners. This article will
analyze the concept of "AI pedagogy" and provide user-friendly
examples that resonate with learners.
1. What is AI Pedagogy?
“AI Pedagogy” refers to the application of AI in teaching and
learning from a pedagogical perspective. AI acts as a supporting tool to
implement learning and training activities but does not replace the central
role of humans and pedagogical principles. In other words, AI is “integrated”
into the teaching process to optimize and personalize learning while adhering
to the fundamental values of education: humanity, interaction, and a focus on
holistic learner development.
2. Rooted in Pedagogy
2.1 Teaching methods based on Kolb’s Learning
Styles
Challenges in the past: Designing lessons based on Kolb’s learning
styles (with four stages: Concrete Experience, Reflective Observation, Abstract
Conceptualization, and Active Experimentation) often required educators to
spend significant time creating scenarios, activities, and various materials
tailored to different learner groups (e.g., those who prefer direct experience
versus those who prefer analysis).
AI Integration: AI can suggest learning activities tailored to each
learner’s style, create real-life simulations, or provide diverse materials
(videos, readings, interactive games). This allows lesson planning to become
faster and more flexible while preserving the core value of Kolb’s method:
connecting learners with experiences and reflection.
2.2 Blended Learning
Challenges in the past: Designing a blended learning course (combining
in-person and online learning) required educators to carefully balance teaching
time, select online platforms, organize group activities, and assess learners.
Ensuring that online content was cohesive and engaging was a major challenge.
AI Integration: AI can track learners' progress and recommend schedules,
content, or interactive activities tailored to individual abilities and
preferences. This enables learners to engage in online learning comfortably,
while in-person sessions focus on interaction and discussion. Thus, the essence
of blended learning—a harmonious combination of in-person and online
learning—is enhanced, not overshadowed by technology.3. Centered on Humans
3.1 Virtual tutors and friendly learning
assistants
Virtual tutors: These are learning assistants available
anytime, anywhere. For instance, when learners need to review knowledge or ask
questions outside classroom hours, virtual tutors can provide answers, suggest
materials, or assign practice exercises.
Human-centric value: While AI can respond quickly, educators remain
crucial in guiding, sparking critical thinking, and offering emotional and
psychological support. Virtual tutors cannot replace the motivation and
personal care educators provide.
3.2 Chatbots trained on educators’ curricula
Learning chatbots: Chatbots built on official course materials
help learners quickly search for information, address common questions, and
review knowledge. Learners can interact with chatbots, asking questions ranging
from simple to complex.
Human-machine interaction: Since chatbots are trained from materials
developed by educators, their answers align closely with classroom teaching and
the pedagogical intentions of educators. Additionally, educators can track
frequently asked questions to adjust lessons, enrich examples, or design
appropriate learning activities.
Core value: Humans (educators) remain the ones who “ignite inspiration,”
crafting lively curricula, encouraging learning enthusiasm, and ensuring the
quality and standards of content. Chatbots act as bridges, helping learners
grasp and reinforce knowledge more effectively.
4. Benefits and Challenges
The integration of AI
into education offers numerous benefits and presents certain challenges. On the
positive side, AI optimizes time and resources for educators by streamlining
lesson planning and assessment, while also personalizing and enhancing
interactions with learners. It creates engaging learning experiences through
simulations, games, and visual aids, empowering learners to take charge of
their own learning and revision.
However, challenges
include ensuring that AI serves as a means to support education, rather than
becoming the ultimate goal. Safeguarding learners’ personal data, such as
information and learning outcomes, is a critical concern. Additionally,
educators must be flexible and equipped with technological skills to
effectively use AI. Continuous updates and maintenance of AI tools are
essential to prevent inaccuracies or irrelevant chatbot responses, ensuring that
the technology remains a valuable and reliable educational tool.
5. Conclusion
“AI Pedagogy” is not just about using AI for
technical purposes but, more importantly, about maintaining the core values of
education “rooted in pedagogy, centered on humans.” No matter how powerful and
versatile AI becomes, the central role lies with educators and learners. AI is
a companion, helping us design creative and personalized lessons and learning
environments, without overshadowing the essential elements of interaction,
empathy, and mutual understanding—the foundations of education.
The application of AI from a pedagogical perspective empowers
learners to take charge of their education, becoming more active and engaged in
acquiring knowledge. At the same time, it allows educators to devote more time
to fostering the holistic development of learners. This approach paves the way
for a modern, high-quality, and humane vocational education system.
Lê Phương Trường
Thứ Năm, 2 tháng 1, 2025
AI in Quality Assurance
In the past, when designing learning outcomes for a course or educational program, educators often had to spend significant time researching and memorizing the verbs in Bloom’s taxonomy. Memorizing or manually referencing Bloom’s verb table across various materials was not only time-consuming but also prone to errors. For example, if a teacher wanted to express the competency of "analyzing," they would have to look up suitable verbs in Bloom’s taxonomy and then cross-check their alignment with learning objectives.
Today, with the support of AI models specifically trained in quality assurance, educators no longer need to “commit to memory” every detail of Bloom’s taxonomy. Instead, they can interact directly with AI to quickly identify appropriate verbs and pinpoint areas for improvement. This significantly reduces the effort required to consult resources or verify the coherence of training programs. For instance, if an educator aims to adjust a learning outcome from the level of "understand" to "apply," AI can suggest verbs like "perform," "apply," or "execute," accompanied by a clear explanation of their relevance.
Additionally, AI can provide detailed advice and guidance to help educators better understand accreditation standards such as AUN-QA or the Ministry of Education and Training’s requirements. Rather than navigating through numerous legal documents or accreditation manuals, teachers simply need to ask questions and receive immediate, accurate answers. This makes the process of skill enhancement more flexible and engaging, allowing educators to explore quality assurance knowledge in their own proactive and creative way.
In summary, AI does not replace the role of educators but acts as an intelligent “assistant” that collaborates with them to design and refine educational programs. It helps save time, accelerates workflows, and, most importantly, sustainably enhances the quality of education.
To learn more about the application of AI in quality assurance, visit:
Link: ChatGPT - Trợ lý đảm bảo chất lượng
Le Phuong Truong
Workshop Materials
You can download all materials here.
Workshop 2: AI Use in Higher Education Quality Assurance: Opportunities, Challenges and Ethical Dimensions
Redesigning Assessments in the AI Era
Introduction
In the technological era, particularly with the explosion of Artificial Intelligence (AI), numerous fields have been profoundly impacted, such as content creation, data analysis, and marketing. Education is no exception. One significant advantage of AI is its ability to reduce administrative tasks and personalize the learning process for each individual. However, a major challenge educators face is assessment. As AI becomes more prevalent in learning, students can rely on AI tools to complete assignments and exams more quickly and effortlessly. This raises an urgent question: How can fairness and integrity in assessments be ensured?
This article will discuss redesigning assessment systems in the AI era and propose solutions to address the challenges posed by students using AI in exams.
The Impact of AI on Assessment
Generative AI provides numerous helpful tools for learners, ranging from solving complex problems, generating text content automatically, to offering detailed answers to academic questions. While these advancements bring significant benefits to learning, they also present serious challenges in assessing the actual competencies of students. Specifically:
Cheating: Students can use generative AI tools such as ChatGPT, Claude, and Copilot to generate essays or answer complex questions effortlessly without conducting their own research or critical thinking.
Difficulty in Determining Actual Competence: Without appropriate control measures, assessments may fail to reflect students' actual competencies, as AI can help them complete tasks without in-depth understanding. Over time, this reliance on AI may erode their critical thinking and deep comprehension of the topics under study.
Solutions for Redesigning Assessment in the AI Era
1. Design Assessments Based on Critical Thinking
Instead of focusing on knowledge-based or straightforward questions, assessments should evaluate learners’ critical thinking, problem-solving, and creativity. Open-ended questions requiring reasoning, analysis, and personal opinions are more challenging for AI tools to address effectively.
2. Integrate Direct and Practical Assessments
An effective solution is to combine theoretical tests with practical or in-person assessments. For instance, after completing a written essay or exam, students could be required to present orally or perform related tasks on the spot to verify their understanding and ability to apply knowledge. This ensures that students genuinely grasp the content rather than relying on AI.
3. Leverage Technology to Detect AI-Generated Content
AI-detection software is being developed and can be integrated into assessment systems. These tools help identify whether an essay or answer has been generated by AI, reducing the risk of cheating.
4. Focus on Learning Processes Instead of Final Results
Rather than concentrating solely on final exams, educators can evaluate students through their learning processes. Long-term projects, stage-by-stage reports, or continuous group activities can assess progress and capabilities comprehensively. This makes it harder for students to rely on AI throughout all phases without demonstrating genuine understanding.
5. Encourage Using AI as a Learning Tool, Not for Cheating
Educators should design teaching and assessment activities where AI is a support tool rather than a means of cheating. For example, students may be asked to use AI for information retrieval but then analyze and provide personal insights based on the results. This promotes responsible and creative use of AI while still accurately assessing learners’ abilities.
6. Use Presentation Methods
Presentations are one of the most effective tools to discourage students from over-relying on AI. Presentations require students to understand the subject matter and demonstrate their communication and logical content delivery skills. Through this method, educators can easily evaluate students' actual understanding and their ability to address arising questions during the presentation. Benefits of this method include:
- Enhancing Critical Thinking and Analysis: Students must synthesize information, think critically, and explain concepts clearly.
- Fostering Creativity: Presentations provide an opportunity for students to showcase creativity through interpretation and content illustration.
- Developing Communication Skills: Communication skills are essential not only in learning but also in future careers.
Conclusion
In the AI era, assessments face numerous challenges but also present opportunities to redesign and improve systems to enhance learners’ critical thinking and adaptability. By applying innovative assessment methods, leveraging technology, and promoting critical thinking, educators can build fair assessment systems that accurately reflect students’ real abilities while encouraging responsible use of AI. Teachers and educational administrators must proactively adjust their approaches, not only to address the challenges AI brings but also to turn it into an effective learning support tool.
Le Phuong Truong
AI Competence Framework for teacher
The AI Competency Framework for Teachers by UNESCO is designed to equip educators with the necessary skills and knowledge to effectively integrate artificial intelligence (AI) into their teaching practices. This framework emphasizes a human-centered approach, prioritizing inclusivity, human agency, and respect for diversity.
The framework is structured around five key areas:
Human-Centered Mindset: Encouraging teachers to understand and assert their agency in relation to AI.
Ethics of AI: Promoting responsible use, ethical principles, and safe practices in AI applications.
AI Foundations and Applications: Providing foundational AI knowledge and skills necessary for educators.
AI Pedagogy: Supporting teachers in leveraging AI for innovative teaching methods and enhancing learning experiences.
AI for Professional Development: Outlining how educators can utilize AI to drive their own lifelong professional growth.
These competencies are categorized into three progression levels: Acquire, Deepen, and Create, allowing for a structured development pathway for teachers at different stages of AI integration.
For a comprehensive understanding and to access the full document, you can download the framework from UNESCO's official repository.
Link: Download here
Thứ Tư, 1 tháng 1, 2025
Quality Assessment for Distance Higher Education Programmes in Vietnam: Introduction, Benchmark and Lessons Learned
Quality Assessment
for Distance Higher Education Programmes
in
Vietnam: Introduction, Benchmark and Lessons Learned
Ho
Dac Hai Mien
Vice-Director of Center for Education
Accreditation, Vietnam National University - Ho Chi Minh City
PhD
student, VNUHCM-University of Social Sciences and Humanities
Abstract
In the context of
Industry 4.0 and the pandemic of Covid – 19, the quality of distance eduction
in higher education institutions has been much concerned by stakeholders. This
paper introduces distance education development and quality assessment standards for distance higher
education programmes in Vietnam. The paper also provides benchmark between Code
of Practice for Programme Accreditation: Open and Distance learning issued by
Malaysian Qualifications Agency and Vietnam’s quality assessment standards for
distance higher education programmes issued by the Ministry of Education and
Training, from that the lessons are withdrawn for improvement. Some suggestions
for the Ministry of Education and Training are also mentioned with hope to shorten the gap with international standards and to promote
distance education quality improvement in Vietnam.
Keywords:
accreditation, distance education, quality assessment
1. General introduction on distance education in
Vietnam
1.1.
Definition of distance education
In Vietnam, distance
education is defined as “an education process in which the student and the teacher
are mostly separated in time and place. By this mode of education, the students
study through textbooks, video tapes, audio tapes,
CD-ROMs, computer software, using personal audio-visual media, broadcasting
radio, television, multimedia communication complexes and the internet under the management and
support of the school” (MOET, 2003). This definition contains basic contents that UNESCO as well as other
international institutions define about distance education. Distance
education includes online education (with ≥ 80% of the content delivered
online) and blended education (with 30 – 79% of the content delivered online),
as well as modes of education using printed material delivered by post and/or
other tools for bridging the distance. Distance education programmes have the same volume, content and structure
as traditional programmes of the same major and level. The
degrees are guaranted in legality and value as other forms of education by the
government.
There are 4 methods of distance education: a) Mail: The programme is conducted mainly by mail through the main
printed learning materials (textbooks, reference books, study guides,
researches, workbooks, exam and test guides); b) Radio and television: The programme is
mainly conducted through radio and television systems, in which the main
learning materials are radio and television programme that are broadcast live
or replayed on radio and television channels; c) Computer network: The programme
is implemented mainly through computer networks, internet and
telecommunications networks in which the main learning materials are electronic
learning materials transferred over the network, the teaching is carried out
online or offline; d) Combination: combine the above methods (MOET, 2017).
1.2. The history of distance education development in Vietnam
The history of distance education development in Vietnam can be divided into 2 periods of time: before and after 2009. Before 2009, there were not many research on distance education in Vietnam. Around 2003-2004, distance education in Vietnam attracted more attentions from many higher education institutions through many seminars and conferences on distance education held at school and national level. Vietnam has joined the Asia E-learning Network (AEN) with the participation of the Ministry of Education and Training, the Ministry of Science and Technology, the Ministry of Posts and Telecommunications and Ha Noi University of Science and Technology. Besides, some software companies in Vietnam launched a number of products to support training. Although these products were not perfect, they have initially contributed to promote the development of e-learning in Vietnam (Pham Hong Hanh & Ha Thanh Hoa, 2019).
After 2009, being invested by businesses and higher education institutions, distance education gradually has attracted the attention of many learners/students. In 2013, Hanoi Open University built an online training technology system, becoming the first university in Vietnam to provide a full e-learning programme which has put the foundation in distance education in higher education institutions until today.
At present, Vietnam has over 100 bachelor degree programmes under distance education mangaged by around 21 higher education institutions. The programmes include a variety of majors such as: business administration, accounting, finance - banking, information technology, law, English, Vietnamese studies, tourism…
2. Introduction on quality assessment standards for distance higher education programmes in Vietnam 2.1. The legal foundation of the establishment quality assessment standards for distance higher education programmes in Vietnam.
In Vietnam, the policy of distance education development and information technology application has been early concerned, first shown on
the Project "Development of distance education in the period
2005-2010" approved by the Prime Minister (2005). The Project mentioned the policy of developing and improving the
quality of distance education; creating
conditions for people, especially who live in remote areas
with difficult socio-economic conditions for regular study and lifelong learning; that contributes to enhance the education level, professional and vocational skills; raises people's intellectual level and
trains human resources for country industrialization and modernization. In 2015, the Prime Minister (2015) continued to promulgate the Project
"Development of distance education for the period 2015-2020" which
set a specific goal for all distance higher education programmes to be accredited by 2020. Higher education institutions conducting distance programmes are also encouraged to be
accredited by reputable international accreditation
agencies. To implement this Project, two legal
documents have been issued including Circular No. 10/2017/TT-BGDDT dated on April 28, 2017 of the Minister of Education
and Training on Regulation on distance learning at university level (MOET, 2017) and Circular No. 39/2020/TT-BGDDT dated on October 9, 2020 of the Minister of
Education and Training stipulating standards/criteria for assessing the quality of distance education programmes at university level (MOET, 2020). These two main documents created a solid
legal foundation for the development of distance education, as well as
emphasized the important attention to quality assurance of this form of
education.
In particular, Law No.
34/2018/QH14 promulgated on November 19, 2018 by the National Assembly (2018) has a remarkable point in which there are no
differences in degree value between different forms of education. All
requirements of
outcome
standards, programme content, teaching methods... of training programmes, no
matter what forms of
training are implemented, must ensure the same quality. This adjustment
reflects the spirit of integration with global education, creating equality for
learners, and emphasizes the important role of quality assurance for all types
of training.
From the above bases,
standards/criteria for assessing the quality
of distance education programmes at university level were born, making the
foundation for the quality assurance and accreditation of this type of
education.
2.2. The structure of quality assessment standards for distance higher education programmes in Vietnam.
Highly influenced by
AUN-QA's assessment at programme
level (AUN-QA, 2015), the quality assessment standards for distance higher
education programmes in Vietnam (below called Vietnam’s standards) has about 80% of the same
content as the AUN-QA’s assessment (see Figure 1). The remaining 20% is
designed to be adapted with Vietnam education context and with the features of distance
education programmes (especilly facilities, infrastructure and materials, as
well as Programme Management).
Figure 1. Comparison
between AUN-QA and Vietnam’s model
The Vietnam’s model (see Figure 1: the model on the
right) includes
the following eleven standards: (1) Expected Learning Outcomes; (2) Programme Specification, Structure
and Content;
(3) Teaching
and Learning Approach; (4) Student
Assessment; (5)
Academic Staff; (6) Support Staff Quality; (7) Student Quality and Support; (8) Facilities, Infrastructure and
Materials; (9) Programme Management; (10) Programme Quality Enhancement; (11) Output.
The model starts with
stakeholders needs which are transfered into the expected learning outcomes
which drive the programme. In the
centre, there are four rows in which the first row addresses the question of
how the expected learning outcomes are translated into the programme; and how
they can be achieved through teaching and learning approach and student
assessment.
The second row considers the
"input" into the process including academic and support staff;
student quality and support; facilities and infrastructure and materials; and
Programmes Management.
The third row addresses the programme
quality enhancement which requires to identify the methods to get feedback from
stakeholders, to measure and to use feedback for improvement. The concept of PDCA (Plan, Do, Check, Act)
is manipulated into the process of improvement.
The fourth row focuses on
the output of the programme including pass rates and dropout rates, the average
time to graduate, employability of the graduates, research activities and
stakeholders’ satisfaction.
The final column addresses
the achievements of the expected learning outcomes and the programme.
The model finishes with the
fulfilment of stakeholders’ needs and the continuous improvement of the quality
assurance system and benchmarking to seek best practices.
3. Benchmark with Code of Practice for Programme
Accreditation: Open and Distance learning (COPPA: ODL - MQA)
According to my research, in countries of ASEAN, Malaysia, specifically
Malaysian Qualifications Agency (MQA) has developed and applied Code of
Practice for Programme Accreditation: Open and Distance Learning (COPPA: ODL)
for accreditation and program audit purposes. The COPPA:ODL contains
specific indicators and benchmark standards that will guide the institutions in
the development, delivery, assessment as well as the monitoring and review of
the ODL programme (Malaysian
Qualifications Agency, 2019).
Compared with COPPA: ODL, the Vietnam’s standards are mostly the same in term
of assessment domains (see Table 1) . Although the
distribution/arrangement of criteria and sub-criteria is different, both focus
on assessing these following main areas: Programme Development and Delivery,
Student Assessment, Academic Staff, Student Support, Facilities and Materials, Programme
Managment, Continual Quality Enhancement.
|
Vietnam’s standards |
COPPA: ODL (MQA) |
|
1. Expected
Learning Outcomes |
1. Programme Development and Delivery |
|
2. Programme
Specification, Structure
and Content |
1. Programme Development and Delivery |
|
3. Teaching
and Learning Approach |
1. Programme Development and Delivery |
|
4. Student Assessment |
2. Assessment of Student Learning |
|
5. Academic Staff |
4. Academic Staff; |
|
6. Support Staff Quality |
4. Academic Staff; |
|
7. Student
Quality and Support |
3. Student Selection and Support
Services; |
|
8. Facilities, Infrastructure and Materials |
5. Educational Resources; |
|
9. Programme
Management |
6. Programme Management |
|
10. Programme
Quality Enhancement |
7. Programme Monitoring, Review and Continual Quality Improvement. |
|
11. Output
|
7. Programme Monitoring, Review and Continual Quality Improvement. |
|
11 criteria, 55 sub-criteria |
7 criteria/areas,
21 sub-criteria |
Table 1. Comparison
between Vietnam’s standards and COPPA: ODL (MQA)
Through benchmark with COOPA: ODL, there are some important and special points that Vietnam could learn as follows:Firstly, COOPA: ODL emphasizes the sufficience in academic autonomy of the ODL programme department and staff in programme development and management. These points are clearly mentioned at sub-criteria: 1.2.1, 2.3.1, 4.2.2, 6.1.4 (see Table 2). However, this requirements have not been mentioned in Vietnam’s standards while academic autonomy is one of the basic and important requirement in higher education. |
A HEP is expected
to have sufficient autonomy, especially over academic matters. Such autonomy
must be reflected at the departmental level where the programme is being
designed and offered. 1.2.1 The department must have
sufficient autonomy to design the curriculum and to utilise the
allocated resources necessary for its implementation. 2.3.1 The department and its
academic staff must have an adequate level of autonomy in the
management of student assessments. 4.2.2 The academic staff must
be given sufficient autonomy to focus on areas of their expertise. 6.1.4 The academic board of
the department must be an effective decision-making body with an adequate
degree of autonomy”. |
Table 2: Sub-criteria:
1.2.1, 2.3.1, 4.2.2, 6.1.4 (Malaysian Qualifications Agency, 2019)
Secondly, COOPA: ODL requires clearly the allignment
between the programme with Malaysian Qualifications Framework (MQF) in some
aspects, such as: learning outcomes; assessement principles, methods and
practices (see Table 3). However, in Vietnam’s standards, there
is only one standard (sub-criteria 1.2) that refers the allignment between programme
learning outcomes and Vietnamese Qualifications Framework (VQF), but the
related requirements do not show in detail how and what clusters of VQF learning
outcomes should be assessed. This could make the institution and external
assessors pay less attention on this allignment and then not assess exactly and
specifically the allignment level.
|
1.1.4 The programme learning
outcomes must correspond to an MQF level descriptors and the five clusters of
MQF learning outcomes: i. Knowledge and understanding; ii. Cognitive skills; iii. Functional work skills; iv. Personal and
entrepreneurial skills v. Ethics and professionalism; v. Ethics and professionalism. 2.1.1 Assessment principles,
methods and practices must be aligned to the learning outcomes, consistent
with the levels defined in the MQF. |
Table 3: Sub-criteria:
1.1.4, 2.1.1 (Malaysian Qualifications Agency, 2019)
Thirdly, COOPA: ODL guildline shows clearly the
relationship between criteria/areas and sub-criteria (for example sub-criteria 1.1.2
must be read together with sub-criteria 1.2.2 in Area 1 and 6.1.6 in Area 6…). This helps the
institutions and external assessors have an overview picture of the matrix of criteria/areas
and sub-criteria relationship, from which the quality of
assessment/self-assessment become more comprehensive. I can not find this
information in the Vietnam’s standards.
Finally, through the information I got from
the conference “Education & Research in the COVID-19 Era” organized by DESE Australian High
Commission KL from 23 -25 August 2021, 336 ODL programmes (the statistics updated to 30 April 2021),
including provisional accreditation and full accreditation, were assessed and
accredited using COOPA: ODL (MQA, 2021). While, in
Vietnam, although standards have taken effect from November 2020, however,
there has not been any programmes assessed and accredited. The lack of clear
processes and guildances for implementing the standards should be the main
reason for this situation.
As it can be
found that there are many similar points in context between Malaysia and
Vietnam, Vietnam should do more research on distance education quality
assessment in Malaysia, including how to build and apply the COPPA: ODL, from
that good practices could be learnt for improvement.
4. Conclusion and suggestion for VietnamThis paper introduced the situation of distance higher education, as well as the quality assessment standards for distance higher education programmes in Vietnam. The paper also showed some important points withdrawn through benchmark/comparison between COPPA: ODA (MQA) and Vietnam’s standards. Some more suggestions for the Ministry of Education and Training in Vietnam are shown as follows:
- Conduct more regional and international research on distance higher education assessment, from that they have scientific and practical basis for building up the quality assurance system for distance higher education programmes.
- Build sufficiently guildlines on process, methods and instrument for distance higher education assessment.
- Encourage institutions who are offerring distance programmes to build up and carry out quality assurance process to distance programmes. When the internal quality assurance process is implemented well enough, they can be ready for external assessment and be accredited.
I believe that the above suggestions if being concerned by the Ministry of Education and Training will help Vietnam’s standards shorten the gap with international standards and improve the quality of distance programmes in higher education institutions.
References
AUN-QA.
(2015). Guide to AUN-QA Assessment at Programme Level Version 3.0. ASEAN
University Network.
Malaysian Qualifications Agency.
(2019). Code of Practice for Programme Accreditation: Open and Distance
Learning (COPPA; ODL).
MOET. (2003). Decision 40/2003/QD-BGDĐT
dated 08/8/2003 promulgating regulations on organization of training,
examination, assessment, granting certificates and graduation degrees in the
form of distance education.
MOET. (2017). Circular No.
10/2017/TT-BGDDT dated April 28, 2017 promulgating the Regulation on distance
learning at university level.
MOET. (2020). Circular 39/2020/TT-BGDDT
dated October 9, 2020 of the Minister of Education and Training stipulating
standards for assessing the quality of distance education programs at
university level.
MQA. (2021, August 23). MQA update on
quality assurance in the higher education sector in Malaysia with respect to
online education. Quality Assurance in Online Higher Education in Australia and
Malaysia. Education & Research in the COVID-19 Era.
National Assembly. (2018). Law No.
34/2018/QH14 promulgated on November 19, 2018 by the National Assembly on
amending and supplementing a number of articles of the Higher Education Law.
Pham Hong Hanh, & Ha Thanh Hoa.
(2019). E-learning Training in China and Experiences for Vietnam. 120–121.
Prime Minister. (2005). Decision No.
164/2005/QD-TTg dated July 4, 2005 approving the Project “Development of
distance education in the period 2005–2010.”
Prime Minister. (2015). Decision No.
1559/QĐ-TTg dated September 10, 2015 approving the Project “Development of
distance education in the period 2010–2020.”
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