OpenAlex · Aktualisierung stündlich · Letzte Aktualisierung: 30.04.2026, 23:42

Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.

AI Readiness for Personalized Learning: A Comparative Study Between Millennials and Gen Z Contents

2026·0 Zitationen·Physical Education Health and Social SciencesOpen Access
Volltext beim Verlag öffnen

0

Zitationen

3

Autoren

2026

Jahr

Abstract

This research examines the impact of Artificial Intelligence (AI) on personalized learning across two generational cohorts, Generation Z (Gen Z) and Millennials, with a focus on three key variables: engagement with AI in education, perceptions of AI in education, and technological fluency and interaction with AI. Using a 30-item AI Readiness Scale (Cronbach's α = .96), data were collected from 123 participants, including 78 Gen Z and 45 Millennial learners (84 females and 39 males). Independent samples t-tests revealed that Gen Z learners scored significantly higher than Millennials in overall AI readiness t (54.48) = 4.75, p < .001), with large effect sizes for engagement (d = 1.23) and technological fluency (d = 1.00), and a moderate effect for perceptions (d = 0.61). A significant association was found between generational group and AI readiness level, χ² (2, N = 123) = 20.02, p < .001. Gender-based chi-square analyses showed similar trends. Among females, Gen Z participants were significantly more likely to be in the high readiness category (33.9%) than Millennial females (10.7%), χ² (2, N = 84) = 12.52, p = .002. Among males, Gen Z learners also outperformed their Millennial peers, with significant differences observed, χ² (2, N = 39) = 7.43, p = .024. These findings support that Gen Z exhibits higher AI readiness and highlight the need for differentiated AI integration strategies in educational settings. Institutions should leverage Gen Z’s advanced digital fluency while providing targeted support to bridge readiness gaps among millennial learners. The results offer critical insights into generational dynamics in the adoption of AI for personalized learning.

Ähnliche Arbeiten

Autoren

Institutionen

Themen

AI in Service InteractionsGenerational Differences and TrendsArtificial Intelligence in Healthcare and Education
Volltext beim Verlag öffnen