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Thematics and Program

Track 1

AI-Enhanced Learning Environments

  • Applications of AI in Higher Education Systems
  • Intelligent data analytics for learning insights
  • AI-enabled personalized academic support (e.g., virtual advisors, chatbots)
  • Automated feedback and formative assessment mechanisms
  • Use of AI in maintaining academic honesty and exam proctoring
  • Algorithmic systems for academic planning and course recommendations
  • AI tools for designing, mapping, and updating curricula
  • Emotion-aware computing to support student engagement and mental health
  • Deeply customized and responsive learning journeys
  • Augmented and virtual realit,y powered by AI, to simulate immersive educational experiences
  • Designing inclusive educational tools through AI-driven personalization

Track 2

Instructional Design and Teaching Innovation

  • AI-supported pedagogical models
  • Adaptive instructional pathways using machine learning
  • Cognitive and motivational processes in AI-mediated learning
  • Use of intelligent tutoring systems for skill development
  • AI applications in mastery-based and outcomes-based education
  • Designing and evaluating AI-powered educational games and simulations

Track 3

Designing and Assessing AI Tools in Education

  • Development and validation of AI systems for education
  • Methods for benchmarking and comparing educational AI tools
  • Participatory and user-centered design approaches for educational technologies
  • Longitudinal impact studies on the use of AI in academic performance and engagement

Track 4

Ethical, Cultural, and Societal Considerations

  • Mitigating algorithmic discrimination and ensuring fairness in educational AI
  • Promoting access, inclusivity, and social justice in AI-enhanced learning systems
  • Addressing cultural variability and responsiveness in AI design
  • Protecting student data and upholding digital rights
  • Psychological and behavioral effects of pervasive AI in learning environments

Track 5

Educators, Leaders, and Institutional Innovation

  • Evolving faculty roles in AI-enabled classrooms
  • Faculty training and professional development for AI fluency
  • Strategic uses of AI for university management and academic planning
  • Reimagining institutional models through digital transformation
  • Leadership and governance practices for AI adoption in education

Track 6

Infrastructure, Strategy, and Policy Frameworks

  • Assessing the digital preparedness of institutions for AI implementation
  • Planning and leading organizational change for AI integration
  • Legal and ethical frameworks governing educational AI use
  • National, regional, and international policy developments
  • Financial models, sustainability planning, and funding strategies for AI deployment

Track 7

Academic Research and Publishing Innovations

  • Machine-assisted research synthesis, summarization, and drafting
  • Algorithmic tools in scholarly peer review processes
  • Generative AI and authorship in academic knowledge creation
  • Emerging standards and metrics in AI-mediated academic impact
  • Transparency, traceability, and integrity in AI-supported publication

Track 8

Interdisciplinary and Cross-Cultural Insights

  • Cross-country comparisons of AI integration in higher education
  • Addressing the needs and constraints of the Global South and low-resource contexts
  • Collaborative AI use across STEM, arts, humanities, and social sciences
  • Philosophical inquiries into the nature of intelligence, learning, and the role of AI
  • Designing human-AI systems that respect academic values and autonomy

Track 9

Future Outlooks and Disruptive Developments

  • Emerging AI capabilities and their educational implications
  • Predictive modeling for academic risk detection and early support
  • AI in continuous and adult learning environments
  • Entrepreneurship, edtech ecosystems, and startup innovations in higher ed
  • Open-source AI tools and democratizing access to educational technology

Special Track: AI for Sustainable Development in Education

Exploring how AI applications in education can accelerate progress toward the UN Sustainable Development Goals (SDGs), this category welcomes conceptual, empirical, and case-based research. Topics may include but are not limited to:

SDG 4 – Quality Education

  • AI-driven strategies for inclusive and equitable access to education
  • Bridging digital divides through AI-powered learning tools in low-resource contexts
  • AI-enabled literacy and numeracy programs for underserved populations
  • Multilingual and culturally adaptive AI learning systems

SDG 5 – Gender Equality

  • Addressing gender bias in AI educational technologies
  • Promoting gender inclusion in STEM through AI interventions
  • AI-based support systems for women and girls in education

SDG 8 – Decent Work and Economic Growth

  • AI-driven upskilling and reskilling programs for employability
  • AI and the future of work: preparing students for AI-influenced careers
  • Integration of labor market forecasting in curriculum development using AI

SDG 9 – Industry, Innovation and Infrastructure

  • Building resilient digital infrastructures for AI in education
  • AI-enhanced public–private partnerships in educational technology
  • Case studies on innovation ecosystems that support AI in education

SDG 10 – Reduced Inequalities

  • Equity-focused AI models in higher education
  • Supporting marginalized learners through personalized AI learning systems
  • AI-enabled interventions to address socioeconomic disparities in access to education

SDG 11 – Sustainable Cities and Communities

  • Community-based educational initiatives using AI
  • Localized AI systems for education in rural and urban areas
  • AI tools for civic education and community engagement

SDG 12 – Responsible Consumption and Production

  • Educating students on sustainability through AI-enhanced simulations and AR/VR
  • Reducing educational waste through AI-optimized resource management

SDG 13 – Climate Action

  • AI-enhanced education on climate change and environmental literacy
  • Predictive modeling and simulation tools for environmental science education
  • Promoting behavioral change through AI-informed learning experiences

SDG 16 – Peace, Justice and Strong Institutions

  • Ethics and accountability in AI deployment in educational institutions
  • AI for civic education, ethics training, and democratic engagement

SDG 17 – Partnerships for the Goals

  • Cross-sector collaborations leveraging AI for educational equity
  • Multi-stakeholder partnerships to scale AI-based education projects
  • Regional and global AI initiatives advancing educational sustainability.

Program

Day 1: 5th of October 2026

Registration at the

8:00 am - 9:00 am

Keynote talks and training

9:00 am - 12:00 pm

Lunch and networking

12:00 pm -1:30 pm

Parallel presentations

1:30 pm - 4:30 pm

Day 2: 6th of October 2026

Keynote talks and training

9:00 am - 12:00 pm

Lunch and networking

12:00 pm -1:30 pm

Parallel presentations

1:30 pm - 4:30 pm

Closing dinner and award ceremony

8:00 pm -10:00 pm

Special Training
AI in Higher Education: From Vision to Practice

This interactive workshop introduces educators, researchers, and students to practical applications of Artificial Intelligence (AI) in teaching, learning, and academic research.

Presented by:

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Julius Nganji, PhD

Adjunct Faculty, Department of Occupational Science and Occupational Therapy, Temerty Faculty of Medicine, University of Toronto; PhD in Computer Science, University of Hull, UK; Research on AI in education, digital accessibility, e-learning personalization, usability, and human-computer interaction; Active researcher, reviewer, and guest editor in academic journals

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Neil Gordon, PhD

Professor of Computer Science, University of Hull, National Teaching Fellow, Principal Fellow of AdvanceHE, Leader of the University’s Computer Science Pedagogic and Education Group, Chair of the British Computer Society’s Ethics Group, Chair of IFIP Working Group 9.2 on Social Accountability and Computing, Author of 150+ publications, Contributor to AdvanceHE reports on flexible learning, assessment, and educational inclusion, Focused on ethical computing and responsible digital practice nationally and internationally, Recent work on the impact of AI on education and AI applications toward the United Nations’ Sustainable Development Goals, including education

At the end of this workshop, participants will be able to:
  • Understand key concepts and uses of AI in higher education.
  • Apply AI tools for research and student engagement.
  • Analyze and visualize data using AI-powered and no-code tools.
  • Evaluate ethical considerations and responsible use of AI in academia.
  • Identify practical ways to integrate AI into their own work or teaching context.
  • Use AI with institutional policies, accreditation requirements, or broader guidelines (UNESCO, national frameworks)

The workshop will focus on hands-on demonstrations of AI-powered tools applied in different educational contexts, such as:

  • Predictive Analytics for Student Success: Using Python with PyCaret to build a simple model that predicts student success or failure.
  • Sentiment Analysis of Student Feedback: Practical analysis of course evaluations to gain insights into student perceptions.
  • Responsible and Ethical AI in Education: An open, interactive discussion on the ethical implications of AI use.
  • Examples of AI adoption in Higher Education: Case studies highlighting real-world applications of AI in universities

Conference Sponsors

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Registration for SAMYRAD 2026 will open on July 15, 2026

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