Application Of AI
In Academic Quality Assurance & Accreditation
This professional training program explores the integration of Artificial Intelligence (AI) in academic quality assurance and accreditation (AQAA) processes. Participants will gain insights into how AI can enhance institutional effectiveness, streamline accreditation compliance, improve decision-making, and optimize data-driven quality improvement initiatives. The program combines theoretical knowledge with practical applications using AI tools.
Methodology
This program incorporates an engaging mix of comprehensive lectures, thorough assessments, tangible practical applications in Excel, and MS BI, examples, and detailed case studies to equip participants with a robust mastery to harness the power of AI in academic QA and accreditation, data analysis, assessment, and reporting. The program will also include collaborative problem-solving and strategy development, and expert guidance led by experienced professionals in AQAA, AI, and accreditation.
Learning Outcomes
Upon successful completion of this program, attendees will have achieved a high level of proficiency that enables them to:
1. Demonstrate in-depth understanding of AQAA and Outcome Based Evaluation.
2. Understand the role of AI in enhancing academic QA and accreditation.
3. Identify AI-powered tools and applications in institutional effectiveness.
4. Apply AI for automating assessment, accreditation compliance, and reporting.
5. Utilize AI-driven analytics for decision-making and strategic planning.
6. Develop AI-based frameworks for continuous quality improvement.
7. Address ethical considerations and challenges of AI in education QA.
What You Will Learn
1. The principles of AQAA and Outcome Based Evaluation.
2. AI applications in higher education QA and accreditation.
3. Machine learning Deep Learning, GenAI, and Agentic AI.
4. AI tools for accreditation documentation and compliance tracking.
5. AI-driven institutional data analytics for assessment and improvement.
6. Predictive analytics for student learning outcomes and program effectiveness.
7. AI-enhanced benchmarking and KPI monitoring in academic institutions.
8. AI's role in risk assessment and policymaking in QA.
9. Implementation strategies for AI in institutional accreditation.
Duration and Mode of Delivery
The program extends over a period of 6 days, featuring 3 hours each day of intensive, interactive learning sessions. It is designed to be accessible and convenient for all by offering both online and in-person attendance options. Participants will be recognized with 18 PDUs (Professional Development Units) for their commitment to professional growth upon completion of the program.
Who Should Attend
The program is suitable for the following professionals, educators, and individuals interested in harnessing the power of AI-based technologies in AQAA:
QA & Accreditation Professionals: Enhance quality processes with AI.
- Institutional Effectiveness Officers: Improve data-driven decision-making.
- University Administrators & Leaders: Understand AI’s role in AQAA.
- AI and Data Science Professionals.
- Graduate Students in Education & AI: Build expertise in AI for quality assurance
- Students and Graduates.
- Anyone Interested in applying AI in AQAA.
Profile of the Trainer
More than 20 years of teaching and research experience in Higer Education, AI, Neural Networks, and Deep Learning.
Extensive experience in programing, statistics, data visualization, analysis, and interpretation.
Certified Lean Six Sigma Green Belt - Kansas University, USA.
- Certified AACSB Program Assessment.
- Certified AACSB Benchmarking.
- Certified ABET Fundamentals of Program Assessment.
- Reviewer of IEEE Online Learning Courses.