Empowering the Higher Education Community through AI Fluency Masterclasses to Bridge the Industrial Skill Gap
DOI:
https://doi.org/10.55927/ijsd.v5i3.28Keywords:
Community Service Integration, Industry Readiness Index (IRI), Industry-Academia Collaboration, AI educationAbstract
The rapid evolution of artificial intelligence (AI) has created a significant skills gap between academic output and industrial requirements. This paper evaluates the effectiveness of AI fluency masterclasses conducted at Nahdlatul Ulama University of Surabaya (UNUSA) as a community service intervention. By utilizing the IOE digital learning platform in collaboration with the Indonesian Employers Association (APINDO), the program provided standardized AI competency training to students, faculty, and staff. The study employs a mixed-methods approach to assess the impact of this intervention on technological literacy and job readiness. Findings indicate that the integration of industry-standardized digital platforms into the higher education ecosystem is a highly efficient strategy to cultivate "job-ready" talent without necessitating the immediate, wholesale restructuring of formal curricula. This study underscores the critical role of university-industry partnerships in mitigating the digital divide and enhancing the employability of graduates in an AI-driven global economy
References
Benavides, L., Tamayo Arias, J., Arango Serna, M., Branch Bedoya, J., & Burgos, D. (2020). Digital Transformation in Higher Education Institutions: A Systematic Literature Review. Sensors, 20(11), 3291. https://doi.org/10.3390/s20113291
Etzkowitz, H., & Leydesdorff, L. (2000). The dynamics of innovation: From National Systems and “Mode 2” to a Triple Helix of university–industry–government relations. Research Policy, 29(2), 109–123. https://doi.org/10.1016/S0048-7333(99)00055-4
Gou, D. (2025). The Potential, Challenges, and Pathways of Generative Artificial Intelligence in Empowering the Professional Development of International Chinese Language Teachers. Journal of Current Social Issues Studies, 2(2), 104–115. https://doi.org/10.71113/JCSIS.2025v2i2.104-115
Hari, Y. (2024). Assessing Novice Voter Resilience on Disinformation During Indonesia Elections 2024 with Naïve Bayes Classifier. Journal of Applied Data Sciences, 6(1), 299–310. https://doi.org/10.47738/jads.v6i1.489
Koh, E., & Doroudi, S. (2023). Learning, teaching, and assessment with generative artificial intelligence: Towards a plateau of productivity. Learning: Research and Practice, 9(2), 109–116. https://doi.org/10.1080/23735082.2023.2264086
Leydesdorff, L., & Meyer, M. (2003). The Triple Helix of university-industry-government relations. Scientometrics, 58(2), 191–203. https://doi.org/10.1023/A:1026276308287
Long, D., & Magerko, B. (2020). What is AI Literacy? Competencies and Design Considerations. Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, 1–16. https://doi.org/10.1145/3313831.3376727
Luckin, R. (2018). Machine learning and human intelligence: The future of education for the 21st century. Institute of Education Press.
Munenakoppa, M., Rane, N. L., Rane, J., & Heggond, S. (2026). Generative artificial intelligence-driven adaptive learning for sustainable, personalized, and resilient education systems. International Journal of Applied Resilience and Sustainability, 2(2), 279–311. https://doi.org/10.70593/deepsci.0202011
Ng, D. T. K., Leung, J. K. L., Chu, S. K. W., & Qiao, M. S. (2021). Conceptualizing AI literacy: An exploratory review. Computers and Education: Artificial Intelligence, 2, 100041. https://doi.org/10.1016/j.caeai.2021.100041
Perkmann, M., Tartari, V., McKelvey, M., Autio, E., Broström, A., D’Este, P., Fini, R., Geuna, A., Grimaldi, R., Hughes, A., Krabel, S., Kitson, M., Llerena, P., Lissoni, F., Salter, A., & Sobrero, M. (2013). Academic engagement and commercialisation: A review of the literature on university–industry relations. Research Policy, 42(2), 423–442. https://doi.org/10.1016/j.respol.2012.09.007
Selwyn, N. (2019). Should robots replace teachers? AI and the future of education. Medford, MA, USA : Polity Press.
Tzirides, A. O. (2026). Multiliteracies, translanguaging and digital literacy in higher education: Exploring the role of generative artificial intelligence. Pedagogies: An International Journal, 21(2), 353–374. https://doi.org/10.1080/1554480X.2026.2638241
Wenjing, X., Marešová, H., & Khan, S. (2026). Micro-credentials in higher education: Transforming credentialing for lifelong learning and workforce alignment. Frontiers in Computer Science, 8, 1853493. https://doi.org/10.3389/fcomp.2026.1853493
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education – where are the educators? International Journal of Educational Technology in Higher Education, 16(1), 39. https://doi.org/10.1186/s41239-019-0171-0
Zhou, G., Yang, Q., & Chen, X. (2026). Longitudinal associations between generative artificial intelligence adoption and university PE teachers’ professional competence. Frontiers in Psychology, 17, 1775028. https://doi.org/10.3389/fpsyg.2026.1775028
