This pilot study evaluates an optional extra-credit project introduced in a math-intensive graduate control theory course. Students used GenAI as a coding and design partner to develop web-based, interactive visualizations of abstract theorems and concepts.
*Note: One student in the sample group completed the curriculum fully online.
Dimension Title
• Small sample baseline (N=10) in a specialized graduate course prevents broad macro-generalization.
• Self-reported open surveys introduce inherent perception & potential social biases.
• Voluntary framework induces self-selection bias from naturally driven students.
• Lack of longitudinal tracking metrics to analyze mastery preservation over time.
• GenAI shifts structural work focus directly up to higher-order cognitive verification tracks.
• Strong fundamental understanding remains a pre-requisite to use GenAI for tasks beyond rote homework.
• The symbiotic interaction built essential validation & project engineering meta-skills.
• Healthy skepticism gained from resolving AI mistakes is a high-value pedagogical asset.