Analisis Dampak AI terhadap Keterlibatan dan Prestasi Akademik Mahasiswa: Pendekatan Statistik untuk Perguruan Tinggi
Exploring the Impact of Artificial Intelligence on Student Engagement and Performance: A Statistical Model for Higher Education Institutions
DOI:
https://doi.org/10.31004/riggs.v4i2.1090Keywords:
Artificial Intelligence, Kinerja Institusi Pendidikan, Mahasiswa, Kecerdasan Buatan, ChatGPT, Academic PerformanceAbstract
Penelitian ini bertujuan untuk menyelidiki dampak implementasi kecerdasan buatan (AI) terhadap keterlibatan dan kinerja akademik mahasiswa di institusi pendidikan tinggi. Dengan menggunakan pemodelan statistik, studi ini menganalisis data keterlibatan mahasiswa sebelum dan sesudah intervensi AI, serta menghubungkannya dengan data kinerja akademik. Temuan utama menunjukkan peningkatan yang signifikan dalam tingkat keterlibatan mahasiswa setelah implementasi AI, dengan mean yang meningkat dari 4.9 menjadi 8.3. Implikasi dari penelitian ini menyoroti potensi AI dalam menciptakan pengalaman belajar yang lebih interaktif dan personal, serta memberikan rekomendasi praktis bagi institusi pendidikan tinggi untuk memanfaatkan AI dalam meningkatkan hasil belajar mahasiswa dan merumuskan kebijakan yang mendukung adopsi AI secara efektif
Downloads
References
Al-Ajlan, H. A. K. M. Abdul-Rahman, B. C. M. Chan, N. N. S. H. M. Nizar, and N. N. A. H. M. Nizar, “Assessment and Evaluation of Different Machine Learning Approaches for Predicting Student Performance,” Computational and Mathematical Methods in Medicine, vol. 2022, no. 9110122, pp. 1–13, Jan. 2022. doi: 10.1155/2022/9110122
M. D. Adewale, A. Azeta, A. Abayomi-Alli, and A. Sambo-Magaji, “Impact of Artificial Intelligence Adoption on Students' Academic Performance in Open and Distance Learning: A Systematic Literature Review,” Heliyon, vol. 10, no. 22, pp. e40025, Jan. 2024. doi: 10.1016/j.heliyon.2024.e40025
Thomas, G., Kumar, R., & George, S. “Development of Automatic Models Based on Deep Learning to Predict Presentation Style from Lecture Videos and Learner Engagement from Their Emotional Behaviour,” Education and Information Technologies, vol. 27, no. 4, pp. 5123–5143, 2022. doi: 10.1007/s10639-021-10716-1
Lamb, J., Ma, Y., & Zhang, X. “Enhance Predictive Models of Student Achievements Using Brain Data from fNIRS in Adaptive Learning,” Computers & Education: Artificial Intelligence, vol. 3, 2022, 100062. doi: 10.1016/j.caeai.2022.100062
Denes, D. “Use of a Range of AI Models to Investigate Whether AI Can Be Used as an Alternative to Exam-Based Grades,” Education and Information Technologies, vol. 28, no. 1, pp. 1–20, 2023. doi: 10.1007/s10639-022-11135-2
Hurix Digital, “AI and Student Engagement: Fostering Interactive Learning Experiences,” Hurix Digital Blog, Jan. 2024. [Online]. Available: https://www.hurix.com/blogs/ai-and-student-engagement-fostering-interactive-learning-experiences/
AIPRM, “AI in Education Statistics: Student Outcomes and Engagement,” AIPRM Blog, Jan. 2024. [Online]. Available: https://www.aiprm.com/ai-in-education-statistics/
Campbell University Academic Technology, “AI in Higher Education: A Meta Summary of Recent Surveys of Students and Faculty,” Campbell University Academic Technology Site, Mar. 2025. [Online]. Available: https://sites.campbell.edu/academictechnology/2025/03/06/ai-in-higher-education-a-summary-of-recent-surveys-of-students-and-faculty/
S. Lee, “5 Key Statistics: AI's Impact on Global Education Policy Trends,” Number Analytics Blog, Jan. 2025. [Online]. Available: https://www.numberanalytics.com/blog/5-key-statistics-ais-impact-global-education-policy-trends
Cruz-Jesus, F., Oliveira, T., & Bacao, F. “Impact of Artificial Intelligence on Assessment Methods in Primary and Secondary Education,” Revista de Psicodidáctica (English Edition), vol. 26, no. 1, pp. 1–11, 2021. doi: 10.1016/j.psicoe.2020.10.002
Wang, X., & Huang, Y. “Artificial Intelligence and Student Engagement in Higher Education: A Systematic Review,” Education and Information Technologies, vol. 27, no. 2, pp. 2363–2384, 2022. doi: 10.1007/s10639-021-10701-8
Zafari, M., Dastjerdi, H. V., & Gharayagh Zandi, H. “Predicting Academic Performance of Public High School Students Using Artificial Intelligence Techniques,” Education and Information Technologies, vol. 26, pp. 4299–4321, 2021. doi: 10.1007/s10639-021-10543-4
Bhutoria, B. “Enhancing Student Engagement in Higher Education Through AI-Based Adaptive Learning Systems,” Education and Information Technologies, vol. 27, pp. 1617–1635, 2022. doi: 10.1007/s10639-021-10689-1
Bearman, M., Boud, D., & Ajjawi, R. “AI-Driven Intelligent Tutoring Systems in Higher Education: Opportunities and Challenges,” British Journal of Educational Technology, vol. 54, no. 4, pp. 1004–1020, 2023. doi: 10.1111/bjet.13232
Kumar, V., & Singh, D. “Machine Learning Algorithms for Predicting Student Performance: A Comparative Study,” Education and Information Technologies, vol. 26, pp. 6799–6820, 2021. doi: 10.1007/s10639-021-10590-x
Almalki, A., & Williams, N. “The Role of Artificial Intelligence in Enhancing Academic Performance in Higher Education,” International Journal of Educational Technology in Higher Education, vol. 20, no. 1, 2023. doi: 10.1186/s41239-023-00410-7
Li, J., & Chen, X. “A Review of Predictive Models for Student Academic Performance Based on Artificial Intelligence,” Education and Information Technologies, vol. 27, pp. 11509–11530, 2022. doi: 10.1007/s10639-022-11100-z
Wang, Y., & Li, H. “Statistical Analysis of AI Impact on Student Outcomes in Higher Education,” Education and Information Technologies, vol. 28, pp. 2345–2367, 2023. doi: 10.1007/s10639-022-11087-7
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 sabo hermawan, Surya Anugrah, Windy Permata Suyono

This work is licensed under a Creative Commons Attribution 4.0 International License.


















