Pelatihan Online Tools AI untuk Meningkatkan Kemampuan Literasi AI Mahasiswa dalam Memvalidasi Referensi Karya Tulis Ilmiah di Jurusan PGSD FKIP Universitas Halu Oleo

Authors

  • Dewa Made Andikayana Universitas Halu Oleo Author
  • Lisnawati Rusmin Universitas Halu Oleo Author
  • Julsari Karopak Universitas Halu Oleo Author

DOI:

https://doi.org/10.63822/nvggbx68

Keywords:

AI literacy; citation hallucination; reference validation; Scite AI; Elicit AI; Consensus AI; online training; Hake N-Gain

Abstract

The massive use of generative artificial intelligence (AI) among university students is not matched by adequate AI literacy skills in validating scientific references. This condition gives rise to a serious threat in the form of academic citation hallucination, a phenomenon in which AI produces fictitious references that appear convincing but cannot be found in any scientific database. An initial survey of 30 students at the Elementary School Teacher Education Department (PGSD), Faculty of Teacher Training and Education (FKIP), Universitas Halu Oleo (UHO) in January–February 2026 revealed that 80% had used ChatGPT to compile references, 70% had never verified their validity, and 90% were unaware of verified academic AI tools. A review of 20 academic papers found that 35% contained references untraceable in any scientific database. This community service activity aimed to improve students' AI literacy in validating scientific references through online training using three academic AI tools: Scite AI, Elicit AI, and Consensus AI. The method employed was participatory training based on live demonstration and guided practice, using a one-group pre-test post-test design (n=30), analyzed using the Hake N-Gain formula. Results showed an average score increase from 51.40 (pre-test) to 87.33 (post-test) with a mean N-Gain of 0.73 (High category). N-Gain distribution: 15 participants (50%) High and 15 participants (50%) Medium, with no participants in the Low category. Participant satisfaction reached 83.33% (Very Satisfied). Online academic AI tools training is proven effective in improving AI literacy among prospective elementary school teacher students in validating scientific references.

Downloads

Download data is not yet available.

References

Alkaissi, H., and S. I. McFarlane. 2023. “Artificial Hallucinations in ChatGPT: Implications in Scientific Writing.” Cureus 15(2):e35179. doi:https://doi.org/10.7759/cureus.35179.

Arikunto, S. 2021. Prosedur Penelitian: Suatu Pendekatan Praktik. Jakarta: Rineka Cipta.

Athaluri, S. A., S. V Manthena, V. S. R. K. M. Kesapragada, V. Yarlagadda, T. Dave, and R. T. S. Duddumpudi. 2023. “Exploring the Boundaries of Reality: Investigating the Phenomenon of Artificial Intelligence Hallucination in Scientific Writing through ChatGPT References.” Cureus 15(4):e37432. doi:https://doi.org/10.7759/cureus.37432.

Bhattacharyya, M., V. M. Miller, D. Bhattacharyya, and L. E. Miller. 2023. “High Rates of Fabricated and Inaccurate References in ChatGPT-Generated Medical Content.” Cureus 15(5):e39238. doi:https://doi.org/10.7759/cureus.39238.

Dergaa, I., K. Chamari, P. Zmijewski, and H. Ben Saad. 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):615–22. doi:https://doi.org/10.5114/biolsport.2023.125623.

Gravel, J., M. D’Amours-Gravel, and E. Osmanlliu. 2023. “Learning to Fake It: Limited Responses and Fabricated References Provided by ChatGPT for Medical Questions.” Mayo Clinic Proceedings: Digital Health 1(3):226–34. doi:https://doi.org/10.1016/j.mcpdig.2023.05.004.

Hake, R. R. 1998. “Interactive-Engagement versus Traditional Methods: A Six-Thousand-Student Survey of Mechanics Test Data for Introductory Physics Courses.” American Journal of Physics 66(1):64–74. doi:https://doi.org/10.1119/1.18809.

Kasneci, E., K. Sessler, S. Küchemann, M. Bannert, D. Dementieva, F. Fischer, U. Gasser, G. Groh, S. Günnemann, E. Hüllermeier, S. Krusche, G. Kutyniok, T. Michaeli, C. Nerdel, J. Pfeffer, O. Poquet, M. Sailer, A. Schmidt, T. Seidel, M. Stadler, J. Weller, J. Kuhn, and G. Kasneci. 2023. “ChatGPT for Good? On Opportunities and Challenges of Large Language Models for Education.” Learning and Individual Differences 103:102274. doi:https://doi.org/10.1016/j.lindif.2023.102274.

Lund, B. D., T. Wang, N. R. Mannuru, B. Nie, S. Shimray, and Z. Wang. 2023. “ChatGPT and a New Academic Reality: Artificial Intelligence-Written Research Papers and the Ethics of the Large Language Models in Scholarly Publishing.” Journal of the Association for Information Science and Technology 74(5):570–81. doi:https://doi.org/10.1002/asi.24750.

Sundayana, R. 2015. Statistika Penelitian Pendidikan. Edisi ke-2. Bandung: Alfabeta.

Walters, W. H., and E. I. Wilder. 2023. “Fabrication and Errors in the Bibliographic Citations Generated by ChatGPT.” Scientific Reports 13:14045. doi:https://doi.org/10.1038/s41598-023-41032-5.

Published

2026-07-11

How to Cite

Andikayana, D. M., Rusmin, L., & Karopak, J. (2026). Pelatihan Online Tools AI untuk Meningkatkan Kemampuan Literasi AI Mahasiswa dalam Memvalidasi Referensi Karya Tulis Ilmiah di Jurusan PGSD FKIP Universitas Halu Oleo. Indonesia Berdampak: Jurnal Pengabdian Kepada Masyarakat, 2(2), 507-518. https://doi.org/10.63822/nvggbx68