PENGARUH INTENSITAS PENGGUNAAN GENERATIVE ARTIFICIAL INTELLIGENCE TERHADAP BERPIKIR KRITIS DAN HASIL BELAJAR MAHASISWA

Penulis

  • Prasetya Yoga Santoso Universitas Sahid
  • Ressa Uli Patrissia Muhammadiyah Palangkaraya University

DOI:

https://doi.org/10.54124/jlmp.v23i1.192

Kata Kunci:

Generative AI, berpikir kritis, hasil belajar, literasi AI, pendidikan tinggi

Abstrak

Penelitian ini mengkaji pengaruh penggunaan Generative Artificial Intelligence (Gen AI) terhadap kemampuan berpikir kritis dan hasil belajar mahasiswa di perguruan tinggi Indonesia. Kebaruan penelitian ini terletak pada integrasi variabel literasi AI (AI literacy) sebagai variabel moderator, yang belum pernah diteliti secara simultan dalam konteks pendidikan tinggi Indonesia. Penelitian menggunakan metode pre-eksperimen one-shot case study dengan 50 mahasiswa sebagai sampel yang dibagi ke dalam tiga kelompok berdasarkan intensitas penggunaan Gen AI: rendah (n=16), sedang (n=17), dan tinggi (n=17). Data dianalisis menggunakan Analysis of Variance (ANOVA) satu arah. Hasil penelitian menunjukkan terdapat perbedaan yang signifikan dalam kemampuan berpikir kritis (F(2,47) = 18.43, p < .001) dan hasil belajar (F(2,47) = 22.17, p < .001) antar ketiga kelompok. Kelompok dengan intensitas penggunaan Gen AI tinggi memperoleh rerata skor berpikir kritis tertinggi (M = 84.71, SD = 5.34) dan hasil belajar terbaik (M = 87.12, SD = 4.91). Penelitian ini merekomendasikan integrasi terstruktur Gen AI ke dalam kurikulum pendidikan tinggi disertai peningkatan literasi AI bagi mahasiswa.

Unduhan

Data unduhan belum tersedia.

Referensi

Acar, O. A. (2023). AI Prompt Engineering Isn’t the Future. Harvard Business Review. https://hbr.org/2023/06/ai-prompt-engineering-isnt-the-future

Anderson, L. W., & Krathwohl, D. R. (2001). A Taxonomy for Learning, Teaching, and Assessing: A Revision of Bloom’s Taxonomy of Educational Objectives. Longman.

Asosiasi Penyelenggara Jasa Internet Indonesia. (2023). Laporan Survei Penetrasi Internet Indonesia 2023. APJII Press.

Badan Pusat Statistik. (2023). Statistik Pendidikan Tinggi Indonesia 2023. BPS RI.

Brown, T. B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., Agarwal, S., Herbert-Voss, A., Krueger, G., Henighan, T., Child, R., Ramesh, A., Ziegler, D. M., Wu, J., Winter, C., & Amodei, D. (2020). Language Models are Few-Shot Learners. Advances in Neural Information Processing Systems, 33, 1877–1901. https://doi.org/10.5555/3495724.3495883

Campbell, D. T., & Stanley, J. C. (1963). Experimental and Quasi-Experimental Designs for Research. Rand McNally.

Chen, L., Chen, P., & Lin, Z. (2023). Artificial Intelligence in Education: A Review. IEEE Access, 8, 75264–75278. https://doi.org/10.1109/ACCESS.2020.2988510

Ennis, R. H. (1987). A taxonomy of critical thinking dispositions and abilities. In J. B. Baron & R. J. Sternberg (Eds.), Teaching Thinking Skills: Theory and Practice (pp. 9–26). W. H. Freeman.

Frieder, Simon Pinchetti, Luca Griffiths, Ryan R. Salvatori, Tommaso Lukasiewicz, Thomas Petersen, Philipp C. Chevalier, Alexis Berner, & Julius. (2023). Mathematical capabilities of ChatGPT. https://doi.org/10.48550/arXiv.2301.13379

Gilson, A., Safranek, C. W., Huang, T., Socrates, V., Chi, L., Taylor, R. A., & Chartash, D. (2023). How does ChatGPT perform on the United States Medical Licensing Examination? The implications of large language models for medical education and knowledge assessment. JMIR Medical Education, 9(1), e45312. https://doi.org/10.2196/45312

Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. MIT Press.

Holstein, K., McLaren, B. M., & Aleven, V. (2018). Student Learning Benefits of a Mixed-Reality Teacher Awareness Tool in AI-Enhanced Classrooms. In C. Penstein Rose (Ed.), Artificial Intelligence in Education (pp. 154–168). Springer. https://doi.org/10.1007/978-3-319-93843-1_12

Indonesian Digital Literacy Survey. (2023). AI Literacy Among Indonesian Higher Education Students 2023. IDLS Institute.

Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., Krusche, S., Kutyniok, G., Michaeli, T., Nerdel, C., Pfeffer, J., Poquet, O., Sailer, M., Schmidt, A., Seidel, T., & 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

Kemdikbudristek, R. I. (2023). Laporan Survei Penggunaan Kecerdasan Buatan dalam Pembelajaran Mahasiswa Indonesia. Kemendikbudristek Press.

Kirschner, P. A., Sweller, J., & Clark, R. E. (2006). Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discovery, problem-based, experiential, and inquiry-based teaching. Educational Psychologist, 41(2), 75–86. https://doi.org/10.1207/s15326985ep4102_1

Kung, T. H., Cheatham, M., Medenilla, A., Sillos, C., De Leon, L., Elepaño, C., Madriaga, M., Aggabao, R., Diaz-Candido, G., Maningo, J., & Tseng, V. (2023). Performance of ChatGPT on USMLE: Potential for AI-assisted medical education using large language models. PLOS Digital Health, 2(2), e0000198. https://doi.org/10.1371/journal.pdig.0000198

Lembaga Layanan Pendidikan Tinggi. (2023). Survei Kesiapan Dosen dalam Menghadapi Era AI di Perguruan Tinggi. LL-Dikti Press.

Long, D., & Magerko, B. (2020a). 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

Long, D., & Magerko, B. (2020b). 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. (2017). Towards artificial intelligence-based assessment systems. Nature Human Behaviour, 1(3), 0028. https://doi.org/10.1038/s41562-016-0028

Miller, G. A. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review, 63(2), 81–97. https://doi.org/10.1037/h0043158

Mollick, E. R., & Mollick, L. (2023). Assigning AI: Seven Approaches for Students, with Prompts. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4475995

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

Nugroho, A., Syarif, M., & Prasetyo, D. (2024). Pola penggunaan kecerdasan buatan generatif di kalangan mahasiswa Indonesia: Sebuah studi nasional. Jurnal Teknologi Pendidikan Indonesia, 14(1), 45–62. https://doi.org/10.26737/jtpi.v14i1.4401

Paas, F., Renkl, A., & Sweller, J. (2003). Cognitive load theory and instructional design: Recent developments. Educational Psychologist, 38(1), 1–4. https://doi.org/10.1207/S15326985EP3801_1

Rahmawati, D., & Kurniawan, B. (2023). Dampak penggunaan ChatGPT terhadap academic dishonesty dan kemampuan menulis kritis mahasiswa di universitas Indonesia. Jurnal Pendidikan Dan Kebudayaan, 8(2), 112–128. https://doi.org/10.24832/jpnk.v8i2.3712

Santoso, P. Y., Hidayat, R., & Wulandari, T. (2023). Persepsi mahasiswa terhadap penggunaan ChatGPT sebagai alat bantu pembelajaran: Studi multi-kampus di Jakarta. Jurnal Penelitian Pendidikan, 23(3), 287–303. https://doi.org/10.17509/jpp.v23i3.59124

Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257–285. https://doi.org/10.1207/s15516709cog1202_4

Sweller, J., van Merrienboer, J. J. G., & Paas, F. (2019). Cognitive architecture and instructional design: 20 years later. Educational Psychology Review, 31(2), 261–292. https://doi.org/10.1007/s10648-019-09465-5

Tamkin, A., Brundage, M., Clark, J., & Ganguli, D. (2021). Understanding the capabilities, limitations, and societal impact of large language models.

Tlili, A., Shehata, B., Adarkwah, M. A., Bozkurt, A., Hickey, D. T., Huang, R., & Agyemang, B. (2023). What if the devil is my guardian angel: ChatGPT as a case study of using chatbots in education. Smart Learning Environments, 10(15), 1–24. https://doi.org/10.1186/s40561-023-00237-x

UNESCO. (2023). Guidance for Generative AI in Education and Research. UNESCO Publishing. https://doi.org/10.54675/HMBB1350

Vygotsky, L. S. (1978). Mind in Society: The Development of Higher Psychological Processes. Harvard University Press.

Wardat, Y., Tashtoush, M. A., AlAli, R., & Jarrah, A. M. (2023). ChatGPT: A revolutionary tool for teaching and learning mathematics. EURASIA Journal of Mathematics, Science and Technology Education, 19(7), em2286. https://doi.org/10.29333/ejmste/13272

Watson, G., & Glaser, E. M. (1980). Watson-Glaser Critical Thinking Appraisal Manual. The Psychological Corporation.

Zawacki-Richter, O., Marin, 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

Unduhan

Diterbitkan

30-06-2026

Cara Mengutip

Santoso, Prasetya Yoga, dan Ressa Uli Patrissia. “PENGARUH INTENSITAS PENGGUNAAN GENERATIVE ARTIFICIAL INTELLIGENCE TERHADAP BERPIKIR KRITIS DAN HASIL BELAJAR MAHASISWA”. Jurnal Lingkar Mutu Pendidikan 23, no. 1 (Juni 30, 2026): 34–41. Diakses September 12, 2026. https://jlmp.kemdikbud.go.id/index.php/jlmp/article/view/192.

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