HCI and the AI Revolution: Cognitive Engineering and Generative Design
Date:
This lecture explored the core foundations of Human-Computer Interaction (HCI) and examined how Artificial Intelligence is transforming the field through Cognitive Engineering and Generative Design. It bridged traditional usability principles with modern AI-driven interface trends.
Topics covered:
- HCI Fundamentals & Evolution: The historical shift from product-centric development (Waterfall methodologies) to human-centric, agile approaches. Emphasized the primary objectives of HCI: interface optimization, error reduction, and user satisfaction.
- Cognitive Engineering: Application of Donald Norman’s principles, including Mental Models, the Gulfs of Execution and Evaluation, Affordances, and Constraints, to ensure systems mirror internal human cognitive processes.
- Human Information Processing: An in-depth look at the multistore memory model (Sensory, Working, and Long-Term Memory). Explored cognitive phenomena such as Miller’s Law, Chunking, the Stroop Effect, and the Dual Coding Theory for better interface design.
- User Research & Task Analysis: Techniques for user segmentation (Mass, Professional, Occasional) and building Personas based on Alan Cooper’s methodology. Discussed Hierarchical Task Analysis (HTA) and ConcurTaskTrees (CTT) for mapping user goals.
- Usability Evaluation: The three pillars of usability (Effectiveness, Efficiency, Satisfaction) alongside practical applications of Nielsen’s 10 Usability Heuristics.
- AI Trends & Generative Malleability: How Large Language Models (LLMs) are enabling dynamic, generative interfaces that transform natural language prompts directly into structured, adaptive UI components (e.g., dynamically generating personalized dashboards).
- State-of-the-Art Research: Discussion of the “Typoist” model (CHI 2025 Honorable Mention), demonstrating how advanced models can simulate human touchscreen typing errors (slips, lapses, and mistakes) by tracking finger and gaze movements.