Indonesian university students demonstrate strong technical AI skills but lack critical soft skills in collaboration and cultural integration, revealing a need for holistic AI education that balances technological competence with local wisdom values.

Objective: This study aimed to assess Indonesian university students' readiness for AI-based project learning that integrates and strengthens local wisdom values, examining the relationship between technological literacy and cultural awareness.

Methods: A quantitative survey was conducted with 285 undergraduate students from four Indonesian universities across Engineering and Education faculties. The study used a validated 40-item online assessment covering 10 competency indicators, including AI conceptual knowledge, data processing, ethics, and cultural contextualization. Statistical analyses included descriptive statistics, ANOVA, Pearson correlations, and normality/homogeneity testing (Cronbach's alpha = 0.830).

Key Findings:

• Students excelled in technical areas: data management (80.8%), data processing (78.9%), and model evaluation (77.2%)
• Significant weaknesses appeared in soft skills: project presentation (40.5%) and collaboration (48.5%)
• Statistically significant differences existed among institutions in overall readiness
• Strong positive correlation between technological literacy and AI readiness
• Students struggle to contextualize AI within local cultural frameworks

Implications: The findings underscore the need for culturally responsive AI curricula that balance technical training with soft skills development, ethical reasoning, and cultural sensitivity. Educational institutions must redesign AI-PBL frameworks to preserve Indonesian cultural identity while advancing technological competence.

Limitations: Small sample size limited to four universities, reliance on self-reported data, cross-sectional design, and focus on specific educational contexts.

Future Directions: Research should expand to diverse institutions, employ mixed-methods approaches, conduct longitudinal studies, and develop empirically validated AI learning models that integrate local wisdom values.

Title and Authors: "Assessing students' readiness for artificial intelligence-based project learning to strengthen local wisdom values in Indonesia" by Sutrisno Sutrisno, Abdul Azis, Mohammad Bhanu Setyawan, Dinie Anggraeni Dewi, Yayuk Hidayah, Muhammad Hakiki, Mustofa Abi Hamid, and Radinal Fadli.

Published On: November 24, 2025

Published By: Cogent Education