Penerapan Generative AI dalam Pembuatan Materi Pembelajaran Big Data pada Program Upskilling Vokasi Jerman
DOI:
https://doi.org/10.63822/f350vf95Keywords:
Generative AI, Pembelajaran Daring, Upskilling PrakerjaAbstract
Pelaksanaan program upskilling dan reskilling profesional skala internasional menuntut penyediaan bahan ajar yang presisi, adaptif, dan relevan dengan kebutuhan industri harian. Program pengabdian masyarakat ini bertujuan menerapkan teknologi Generative AI (Claude) dalam pembuatan materi pembelajaran daring pada program prakerja pemerintah Jerman yang diselenggarakan di HUI Habmann. Pelatihan berlangsung selama 16 hari kerja dengan durasi 8 jam per hari menggunakan bahasa Inggris sebagai bahasa pengantar. Berdasarkan structure plan kurikulum yang telah ditetapkan sebelumnya, Generative AI dimanfaatkan untuk meng-generate seluruh materi presentasi, tugas harian, studi kasus, hingga Level 3 Project yang terintegrasi dengan Management Transfer Card. Pembelajaran harian mengadopsi alur learning journey berbasis tiga tingkatan kompetensi: Level Dasar (Knowledge Input), Level Aplikasi (Daily Case Study), dan Level Manajerial (CDAO Level 3 Project & Coaching 1:1). Hasil kegiatan menunjukkan bahwa penggunaan skema prompt engineering berbasis file konfigurasi YAML pada GenAI berhasil memangkas waktu pembuatan materi pembelajaran dari 6,5 jam menjadi 1,4 jam per modul (efisiensi 78,5%). Selain itu, tingkat penyelesaian proyek manajerial peserta mencapai 96,8% dengan rerata nilai kepuasan pembelajaran sebesar 4,82 dari skala 5,0. Integrasi GenAI terbukti efektif mengakselerasi penyiapan materi pengajaran intensif tanpa mengurangi kualitas instruksional dan relevansi terapan di dunia kerja.
Downloads
References
Chiu, T. K. F. (2023). The impact of Generative AI (GenAI) on practices, policies and research direction in education: A case of ChatGPT and Midjourney. Interactive Learning Environments, 1–17. https://doi.org/10.1080/10494820.2023.2253861
Chiu, T. K. F. (2024). Future research recommendations for transforming higher education with generative AI. Computers and Education: Artificial Intelligence, 6, 100197. https://doi.org/10.1016/j.caeai.2023.100197
Ertmer, P. A., & Newby, T. J. (2013). Behaviorism, cognitivism, constructivism: Comparing critical features from an instructional design perspective. Performance Improvement Quarterly, 26(2), 43–71. https://doi.org/10.1002/piq.21143
Holmes, W., & Tuomi, I. (2022). State of the art and practice in AI in education. European Journal of Education, 57(4), 542–570. https://doi.org/10.1111/ejed.12533
Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., ... & Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274
Kirkpatrick, D. L., & Kirkpatrick, J. D. (2006). Evaluating Training Programs: The Four Levels (3rd ed.). Berrett-Koehler Publishers. https://www.bkconnection.com/books/title/evaluating-training-programs
Loebbecke, C., & Picot, A. (2015). Reflections on societal and business model transformation arising from digitization and big data analytics. The Journal of Strategic Information Systems, 24(3), 149–157. https://doi.org/10.1016/j.jsis.2015.08.002
Margaryan, A., Bianco, M., & Littlejohn, A. (2015). Instructional design quality of Massive Open Online Courses (MOOCs). Computers & Education, 80, 77–83. https://doi.org/10.1016/j.compedu.2014.08.005
Mollick, E. R., & Mollick, L. (2023). Assigning AI: Seven Approaches for Students, with Prompts. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4475995
OECD. (2021). AI and the Future of Skills, Volume 1: Capabilities and Assessment. OECD Publishing, Paris. https://doi.org/10.1787/5ee71f34-en
UNESCO. (2023). Guidance for Generative AI in Education and Research. United Nations Educational, Scientific and Cultural Organization. https://www.unesco.org/en/articles/guidance-generative-ai-education-and-research
Voogt, J., & Roblin, N. P. (2012). A comparative analysis of international frameworks for 21st century competences: Implications for national curriculum policies. Journal of Curriculum Studies, 44(3), 299-321. https://doi.org/10.1080/00220272.2012.668938
White, J., Fu, Q., Hays, S., Sandborn, M., Olea, C., Gilbert, B., ... & Schmidt, D. C. (2023). A prompt pattern catalog to enhance prompt engineering with ChatGPT. arXiv preprint arXiv:2302.11382. https://doi.org/10.48550/arXiv.2302.11382
Williamson, B., & Eynon, R. (2020). Historical threads, cognitive forecastings, and digital futures: Introduction to the special issue on EdTech. Learning, Media and Technology, 45(3), 223-235. https://doi.org/10.1080/17439884.2020.1792683
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouiaa, 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), 1–27. https://doi.org/10.1186/s41239-019-0171-0
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Romeo Romero (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
