Digital Competence as a Proxy for AI Readiness and Equity Conditions for Undergraduate Research: A Cross-Sectional Student–Faculty Study in Panama

Undergraduate research (UR) increasingly requires students and mentors to work in digitally mediated environments, yet digital readiness and access to support may be unevenly distributed. This cross-sectional, observational secondary analysis examined student and faculty perception data from Panama to characterize competencies relevant to technology-enhanced UR. Digital competence was treated explicitly as a proxy for, rather than a direct measure of, AI readiness. Analyses used a student domain-profile subsample (N = 96) and a student–faculty comparison subsample (N = 42), with regional distributions, high-affirmation percentages, mean scores, and dispersion examined descriptively. Students reported a comparatively strong information-management and digital-competence profile (mean regional high affirmation = 69.27%), although regional and domain-level asymmetries remained; mathematics showed the widest regional range (40.8 points). Student and faculty mean perceptions were similar (2.82 and 2.84), but student responses were more dispersed (SD = 0.664 vs. 0.418), and student high-affirmation percentages exceeded faculty estimates in every region. Faculty technology-use readiness was generally positive but varied regionally (53.3%–85.7%). The findings support a variance-sensitive diagnostic framework that distinguishes digital-readiness foundations, student–faculty perceptual alignment, and mentor-side capacity. They do not demonstrate AI literacy or AI-specific performance; instead, they identify conditions that may support equitable development of AI-ready UR ecosystems when combined with explicit integrity, verification, and mentoring practices.