Special Session 2
AI-Resilient Computer Science Education:
Assessment Innovation, Curriculum Redesign, and Learning Analytics in the Era of Generative AI
The rapid evolution of generative AI has fundamentally reshaped the landscape of
Computer Science (CS) education. AI tools now assist in code generation, data analysis,
report writing, and problem-solving — raising urgent questions about assessment validity, academic
integrity, curriculum relevance, and student learning measurement. This Special Session provides a
focused forum to explore how CS education can evolve to remain rigorous, authentic, and
future-ready in an AI-saturated academic environment.
Scope & Topics of Interest
We welcome original research papers, case studies, empirical evaluations, conceptual frameworks, and system demonstrations addressing — but not limited to — the following themes:
1 — AI-Resilient Assessment Design
Authentic assessment in programming and data science courses
Redesigning examinations in AI-assisted environments
Competency-based and performance-based evaluation models
Academic integrity strategies in the era of generative AI
2 — Curriculum Innovation and Redesign
Integrating AI literacy into CS curricula
Teaching “with AI” versus teaching “about AI”
Industry-aligned curriculum transformation
Emerging competencies for AI-era graduates
3 — Learning Analytics and Educational Data Mining
Monitoring AI usage in coursework
Behavioural modelling of student engagement
Predictive analytics for learning outcomes
Intelligent dashboards and intervention systems
4 — Policy, Ethics, and Governance
Institutional AI policies in higher education
Responsible AI use frameworks
Equity and access considerations
Cross-national policy comparisons
5 — Comparative and Cross-Regional Studies
Perspectives from emerging economies
Asia–Africa–Global collaboration models
Multi-institutional case studies
Why Submit?
Present your work at a leading international conference in AI, Information Retrieval, and Knowledge Management
Contribute to shaping global discourse on AI in CS education
Network with researchers and academic leaders from multiple regions
Selected high-quality papers may be considered for an extended version in a post-conference special issue (subject to confirmation)
Submission & Publication
Submission Requirements
- Original, unpublished research in English
- 10–15 pages following Springer template
- Similarity score < 15%
- AI-generated content score < 20%
- No simultaneous submissions to other venues
- Must adhere to Springer Publishing Policies
Publication
- Published in Springer CCIS series
- Scopus indexed proceedings
- Full peer review per CCIS standards
- Presentation at conference required for inclusion
- Subject to publisher guidelines & indexing requirements
🔗 Submit your papers electronically via the EDAS portal, under the track entitled "SS2-AI-Resilient Computer Science Education"
EDAS
Deadline
Submission Deadline
30 April 2026
If you require visa letters, accessibility accommodations, or special session guidance, mention it in your email for faster routing.
Special Session Organizers
Session Organizer · 02
Prof. Ts. Dr. Nurfadhlina Mohd Sharef
Faculty of Computer Science and Information Technology
Universiti Putra Malaysia
nurfadhlina@upm.edu.my
Universiti Putra Malaysia
Positioning Statement
💡 As generative AI continues to redefine how programming, data science, and algorithmic
problem-solving are performed, the sustainability of traditional assessment models is under scrutiny.
This Special Session seeks forward-looking research that moves beyond reactive policies
toward robust, evidence-based educational redesign. We invite contributions that are
methodologically rigorous, theoretically grounded, and practically impactful.
Person to Contact
For inquiries regarding this special session, please contact:
Dr. Brian Halubanza
Mulungushi University, Zambia
bhalubanza@gmail.com
