Pengaruh Kesalahan Informasi Generative AI terhadap Berpikir Kritis dan Ketekunan Belajar Mahasiswa: Studi Eksperimental
Keywords:
Generative AI, Kesalahan Informasi, Berpikir Kritis, Ketekunan Belajar, MahasiswaAbstract
Generative AI semakin banyak digunakan mahasiswa sebagai sumber informasi akademik, tetapi keluarannya dapat memuat kesalahan informasi (hallucination) yang disajikan secara meyakinkan. Penelitian ini bertujuan menganalisis pengaruh paparan kesalahan informasi generative AI terhadap berpikir kritis dan ketekunan belajar mahasiswa. Desain yang digunakan adalah eksperimen dengan rancangan pretest–posttest control group dan alokasi acak, dilaksanakan pada 5 Maret–5 April 2026.di Universitas Nurul Hasanah Kutacane. Sampel berjumlah 50 mahasiswa yang dibagi sama banyak menjadi kelompok intervensi (n = 25), yang mengerjakan tugas berbasis keluaran AI berisi kesalahan informasi terkontrol, dan kelompok kontrol (n = 25), yang menerima keluaran AI yang telah diverifikasi. Berpikir kritis diukur dengan tes berpikir kritis dan ketekunan belajar dengan skala ketekunan belajar. Data dianalisis menggunakan uji t independen, chi-square, dan regresi linear berganda. Hasil uji eksperimental menunjukkan skor berpikir kritis kelompok intervensi menurun 5,1 poin, sedangkan kelompok kontrol meningkat 6,6 poin (p < 0,001); ketekunan belajar kelompok intervensi menurun 3,8 poin dibandingkan peningkatan 5,2 poin pada kelompok kontrol (p < 0,001). Paparan kesalahan informasi meningkatkan peluang berpikir kritis rendah (OR = 6,00; 95% CI 1,69–21,30). Disimpulkan bahwa kesalahan informasi generative AI berpengaruh negatif terhadap berpikir kritis dan ketekunan belajar mahasiswa. Literasi AI dan kebiasaan verifikasi informasi perlu diintegrasikan dalam pembelajaran
References
Abbas, M., Jam, F. A., & Khan, T. I. (2024). Is it harmful or helpful? Examining the causes and consequences of generative AI (ChatGPT) usage among university students. International Journal of Educational Technology in Higher Education, 21, Article 10.
Alkaissi, H., & McFarlane, S. I. (2023). Artificial hallucinations in ChatGPT: Implications in scientific writing. Cureus, 15(2), e35179.
APJII. (2024). Survei penetrasi internet Indonesia 2024. Asosiasi Penyelenggara Jasa Internet Indonesia.
Baidoo-Anu, D., & Owusu Ansah, L. (2023). Education in the era of generative artificial intelligence (AI): Understanding the potential benefits of ChatGPT in promoting teaching and learning. Journal of AI, 7(1), 52–62.
Bastani, H., Bastani, O., Sungu, A., Ge, H., Kabakcı, Ö., & Mariman, R. (2025). Generative AI without guardrails can harm learning: Evidence from high school mathematics. Proceedings of the National Academy of Sciences, 122(26), e2422633122.
Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021). On the dangers of stochastic parrots: Can language models be too big? Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (FAccT '21), 610–623.
BPS Kabupaten Aceh Tenggara. (2024). Kabupaten Aceh Tenggara dalam Angka 2024. Badan Pusat Statistik Kabupaten Aceh Tenggara.
BPS Provinsi Aceh. (2024). Provinsi Aceh dalam Angka 2024. Badan Pusat Statistik Provinsi Aceh.
Chan, C. K. Y. (2023). A comprehensive AI policy education framework for university teaching and learning. International Journal of Educational Technology in Higher Education, 20, Article 38.
Chan, C. K. Y., & Hu, W. (2023). Students' voices on generative AI: Perceptions, benefits, and challenges in higher education. International Journal of Educational Technology in Higher Education, 20, Article 43.
Cotton, D. R. E., Cotton, P. A., & Shipway, J. R. (2024). Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Innovations in Education and Teaching International, 61(2), 228–239.
Dwivedi, Y. K., Kshetri, N., Hughes, L., et al. (2023). "So what if ChatGPT wrote it?" Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI. International Journal of Information Management, 71, 102642.
Fan, Y., Tang, L., Le, H., et al. (2025). Beware of metacognitive laziness: Effects of generative artificial intelligence on learning motivation, processes, and performance. British Journal of Educational Technology, 56(2), 489–530.
Farrokhnia, M., Banihashem, S. K., Noroozi, O., & Wals, A. (2024). A SWOT analysis of ChatGPT: Implications for educational practice and research. Innovations in Education and Teaching International, 61(3), 460–474.
Gerlich, M. (2025). AI tools in society: Impacts on cognitive offloading and the future of critical thinking. Societies, 15(1), 6.
Hadi Mogavi, R., Deng, C., Kim, J. J., et al. (2024). ChatGPT in education: A blessing or a curse? A qualitative study exploring early adopters' utilization and perceptions. Computers in Human Behavior: Artificial Humans, 2(1), 100027.
Ji, Z., Lee, N., Frieske, R., et al. (2023). Survey of hallucination in natural language generation. ACM Computing Surveys, 55(12), 1–38.
Kasneci, E., Seßler, K., Küchemann, S., et al. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274.
Kemendikbudristek. (2024). Panduan penggunaan generative artificial intelligence (AI) pada pembelajaran di perguruan tinggi. Kementerian Pendidikan, Kebudayaan, Riset, dan Teknologi.
Lee, H.-P., Sarkar, A., Tankelevitch, L., et al. (2025). The impact of generative AI on critical thinking: Self-reported reductions in cognitive effort and confidence effects from a survey of knowledge workers. Proceedings of the CHI Conference on Human Factors in Computing Systems (CHI '25).
Lo, C. K. (2023). What is the impact of ChatGPT on education? A rapid review of the literature. Education Sciences, 13(4), 410.
Messeri, L., & Crockett, M. J. (2024). Artificial intelligence and illusions of understanding in scientific research. Nature, 627, 49–58.
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.
Ouyang, F., Zheng, L., & Jiao, P. (2022). Artificial intelligence in online higher education: A systematic review of empirical research from 2011 to 2020. Education and Information Technologies, 27, 7893–7893.
Rudolph, J., Tan, S., & Tan, S. (2023). ChatGPT: Bullshit spewer or the end of traditional assessments in higher education? Journal of Applied Learning & Teaching, 6(1), 342–363.
Sallam, M. (2023). ChatGPT utility in healthcare education, research, and practice: Systematic review on the promising perspectives and valid concerns. Healthcare, 11(6), 887.
Stadler, M., Bannert, M., & Sailer, M. (2024). Cognitive ease at a cost: LLMs reduce mental effort but compromise depth in student scientific inquiry. Computers in Human Behavior, 160, 108386.
Tlili, A., Shehata, B., Adarkwah, M. A., et al. (2023). What if the devil is my guardian angel: ChatGPT as a case study of using chatbots in education. Smart Learning Environments, 10, Article 15.
UNESCO. (2023). Guidance for generative AI in education and research. United Nations Educational, Scientific and Cultural Organization.
Walter, Y. (2024). Embracing the future of artificial intelligence in the classroom: The relevance of AI literacy, prompt engineering, and critical thinking in modern education. International Journal of Educational Technology in Higher Education, 21, Article 15.
WHO. (2024). Ethics and governance of artificial intelligence for health: Guidance on large multi-modal models. World Health Organization.
Zhai, C., Wibowo, S., & Li, L. D. (2024). The effects of over-reliance on AI dialogue systems on students' cognitive abilities: A systematic review. Smart Learning Environments, 11, Article 28.
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