Use generative AI as a preparation accelerator for bounded execution-level tasks, not as a design partner¶

Strategy · All strategies
Evidence · no claims cited

Description¶

The authors found generative AI tools "useful at specific, bounded points in the preparation process": rewriting emails to match a character's voice, generating plausible inject variants, and identifying gaps in milestone coverage. They did not replace judgment about exercise goals, milestone logic soundness, or difficulty calibration for the target audience.

Design Implications¶

Context¶

Requirements¶

• Human judgment must remain responsible for what the exercise should achieve and whether difficulty is calibrated correctly

Constraints¶

• AI is framed as a preparation accelerator for execution-level tasks, not a design partner for decisions requiring understanding of trainees and learning objectives

Target Learners¶

• exercise designers and instructors in computing education

Target Learning Goals¶

• efficient preparation of technology-enhanced tabletop exercises

Related Strategies¶

• Support instructors during execution with predefined email templates and instructor notes
• Reuse and adapt existing scenarios to make repeated TTX delivery sustainable

Examples¶

-

Key Sources¶

• J. Vykopal, P. Čeleda, M. Horák, V. Švábenský. (2026). Technology-Enhanced Tabletop Exercises for Cybersecurity Education: Lessons Learned. In Proceedings of the 56th IEEE Frontiers in Education Conference (FIE '26). https://arxiv.org/abs/2607.28179