Effects of AI guided experiential learning on market intelligence skills among university students in Colombia
TL;DR
It is suggested that AI integration can strengthen market intelligence education in resource-constrained environments by expanding access to advanced analytical capabilities while preserving human-centered pedagogical principles.
Abstract
This quasi-experimental study examined whether AI-guided experiential learning improves market intelligence capabilities among Colombian undergraduate students compared to traditional instruction. A total of 120 students from two universities participated in an eight-week intervention structured around Kolb’s experiential learning cycle. The experimental group used ChatGPT to support data interpretation, reflection, conceptual modeling, and analytical scenario testing, while the control group followed conventional teaching methods. ANCOVA results indicated significantly higher posttest scores for the AI-supported group, with a medium-to-large effect size (Cohen’s d = 0.64). Learning progression analyses showed the greatest gains during the reflective observation and abstract conceptualization phases, demonstrating that AI tools enhance analytical development when embedded within structured experiential processes. These findings suggest that AI integration can strengthen market intelligence education in resource-constrained environments by expanding access to advanced analytical capabilities while preserving human-centered pedagogical principles. Rather than advancing a new theory, the study offers context-specific empirical evidence—consistent with experiential learning and structured AI-scaffolding accounts—that AI-supported experiential activities can be implemented feasibly and are associated with meaningful short-term gains in market-intelligence performance under the conditions examined.