Peningkatan Literasi Kecerdasan Buatan bagi Mahasiswa Kedokteran melalui Talkshow Edukatif Interaktif di Fakultas Kedokteran Universitas Islam Sultan Agung Semarang, Jawa Tengah
DOI:
https://doi.org/10.54082/jamsi.2333Kata Kunci:
etika AI, kecerdasan buatan, literasi AI, mahasiswa kedokteran, talkshow edukatifAbstrak
Mahasiswa kedokteran Fakultas Kedokteran Universitas Islam Sultan Agung (FK UNISSULA) angkatan 2025 menghadapi tantangan rendahnya literasi kecerdasan buatan, terutama karena belum pernah mendapatkan pendidikan formal mengenai AI selama pendidikan menengah. Kondisi ini menimbulkan risiko automation bias dan kurangnya kesadaran etis dalam penerapan AI yang semakin banyak digunakan dalam diagnosis dan layanan kesehatan. Kegiatan pengabdian kepada masyarakat ini bertujuan meningkatkan literasi dan kesadaran etis mahasiswa terhadap kecerdasan buatan dalam konteks kedokteran. Metode pelaksanaan meliputi tiga tahap: (1) persiapan materi dan instrumen evaluasi, (2) pelaksanaan talkshow edukatif interaktif dengan narasumber dosen FK UNISSULA yang mengajarkan applied AI, membahas dasar-dasar AI, potensi dan bahaya, risiko ketergantungan teknologi, serta etika AI dalam praktik kedokteran, dan (3) evaluasi menggunakan pre-test dan post-test dengan lima pertanyaan pilihan ganda. Kegiatan diikuti 101 mahasiswa. Hasil menunjukkan peningkatan rata-rata skor dari 3,74 menjadi 4,24 (peningkatan 13,4%), disertai peningkatan partisipasi aktif dan sikap kritis mahasiswa dalam sesi diskusi. Kegiatan ini berhasil meningkatkan kompetensi literasi AI dan kesadaran etis mahasiswa kedokteran dalam memahami peran serta keterbatasan kecerdasan buatan.
Referensi
Abd-alrazaq, A., AlSaad, R., Alhuwail, D., Ahmed, A., Healy, P. M., Latifi, S., Aziz, S., Damseh, R., Alabed Alrazak, S., & Sheikh, J. (2023). Large Language Models in Medical Education: Opportunities, Challenges, and Future Directions. JMIR Medical Education, 9, e48291. https://doi.org/10.2196/48291
Al Saad, M. M., Shehadeh, A., Alanazi, S., Alenezi, M., Abu Alez, A., Eid, H., Alfaouri, M. S., Aldawsari, S., & Alenezi, R. (2022). Medical Students’ Knowledge and Attitude Towards Artificial Intelligence: An Online Survey. The Open Public Health Journal, 15(1), e187494452203290. https://doi.org/10.2174/18749445-v15-e2203290
Aljamaan, F., Temsah, M.-H., Altamimi, I., Al-Eyadhy, A., Jamal, A., Alhasan, K., Mesallam, T. A., Farahat, M., & Malki, K. H. (2024). Reference Hallucination Score for Medical Artificial Intelligence Chatbots: Development and Usability Study. JMIR Medical Informatics, 12, e54345. https://doi.org/10.2196/54345
Dergaa, I., Chamari, K., Zmijewski, P., & Ben Saad, H. (2023). From human writing to artificial intelligence generated text: Examining the prospects and potential threats of ChatGPT in academic writing. Biology of Sport, 40(2), 615–622. https://doi.org/10.5114/biolsport.2023.125623
Gao, C. A., Howard, F. M., Markov, N. S., Dyer, E. C., Ramesh, S., Luo, Y., & Pearson, A. T. (2023). Comparing scientific abstracts generated by ChatGPT to real abstracts with detectors and blinded human reviewers. Npj Digital Medicine, 6(1), 75. https://doi.org/10.1038/s41746-023-00819-6
Goodstats. (2025). 95% Mahasiswa RI Gunakan AI dalam Proses Pembelajaran—GoodStats Data. https://data.goodstats.id/statistic/95-mahasiswa-ri-gunakan-ai-dalam-proses-pembelajaran-FIm7A
Gordon, M., Daniel, M., Ajiboye, A., Uraiby, H., Xu, N. Y., Bartlett, R., Hanson, J., Haas, M., Spadafore, M., Grafton-Clarke, C., Gasiea, R. Y., Michie, C., Corral, J., Kwan, B., Dolmans, D., & Thammasitboon, S. (2024). A scoping review of artificial intelligence in medical education: BEME Guide No. 84. Medical Teacher, 46(4), 446–470. https://doi.org/10.1080/0142159X.2024.2314198
Grassini, S. (2023). Shaping the Future of Education: Exploring the Potential and Consequences of AI and ChatGPT in Educational Settings. Education Sciences, 13(7), 692. https://doi.org/10.3390/educsci13070692
Kerasidou, A. (2020). Artificial intelligence and the ongoing need for empathy, compassion and trust in healthcare. Bulletin of the World Health Organization, 98(4), 245–250. https://doi.org/10.2471/BLT.19.237198
Laupichler, M. C., Aster, A., Meyerheim, M., Raupach, T., & Mergen, M. (2024). Medical students’ AI literacy and attitudes towards AI: A cross-sectional two-center study using pre-validated assessment instruments. BMC Medical Education, 24(1), 401. https://doi.org/10.1186/s12909-024-05400-7
Lee, J., Wu, A. S., Li, D., & Kulasegaram, K. (Mahan). (2021). Artificial Intelligence in Undergraduate Medical Education: A Scoping Review. Academic Medicine, 96(11S), S62–S70. https://doi.org/10.1097/ACM.0000000000004291
Masters, K. (2019). Artificial intelligence in medical education. Medical Teacher, 41(9), 976–980. https://doi.org/10.1080/0142159X.2019.1595557
Pena, G. P., & De Souza Andrade-Filho, J. (2010). Analogies in medicine: Valuable for learning, reasoning, remembering and naming. Advances in Health Sciences Education, 15(4), 609–619. https://doi.org/10.1007/s10459-008-9126-2
Shishehgar, S., Murray‐Parahi, P., Alsharaydeh, E., Mills, S., & Liu, X. (2025). Artificial Intelligence in Health Education and Practice: A Systematic Review of Health Students’ and Academics’ Knowledge, Perceptions and Experiences. International Nursing Review, 72(2), e70045. https://doi.org/10.1111/inr.70045
Wartman, S. A., & Combs, C. D. (2018). Medical Education Must Move From the Information Age to the Age of Artificial Intelligence. Academic Medicine, 93(8), 1107–1109. https://doi.org/10.1097/ACM.0000000000002044
Yanti, N., Mulyati, Y., Sunendar, D., & Damaianti, V. (2021). Tingkat Literasi Digital Mahasiswa Indonesia. Diksa : Pendidikan Bahasa Dan Sastra Indonesia, 7(1), 59–71. https://doi.org/10.33369/diksa.v7i1.22391
Unduhan
Diterbitkan
Cara Mengutip
Terbitan
Bagian
Lisensi
Hak Cipta (c) 2026 Qorry Amanda, Najwa Fatin Siddiq, Annisa Fadhilah Permatasari, Miftah Nur Zaidan, Anggia Ersa Pratiwi, Salsabila Mutiara Yunus, Dannu Purwanto
Artikel ini berlisensi Creative Commons Attribution 4.0 International License.
