Pemanfaatan AI dalam Analisis Efektivitas Kurikulum
DOI:
https://doi.org/10.31004/joecy.v6i1.7805Keywords:
AI, analisis kurikulum, efektivitas pembelajaran, , evaluasi pendidikan, teknologi pendidikanAbstract
Penelitian ini bertujuan untuk mengeksplorasi pemanfaatan AI (Artificial Intelligence) dalam menganalisis efektivitas kurikulum di satuan pendidikan. Evaluasi kurikulum yang efektif memerlukan data akurat terkait pencapaian kompetensi siswa, keterlibatan guru, dan relevansi materi pembelajaran. Penelitian ini menggunakan pendekatan kualitatif deskriptif dengan pengumpulan data melalui dokumen kurikulum, observasi, wawancara, dan analisis data pembelajaran menggunakan model AI Analytics. Hasil penelitian menunjukkan bahwa penggunaan AI dapat membantu sekolah dan pengambil kebijakan dalam menilai efektivitas kurikulum secara lebih cepat, akurat, dan berbasis bukti, serta memberikan rekomendasi perbaikan yang tepat sasaran. Temuan ini memberikan dasar bagi pengembangan kurikulum yang lebih adaptif, responsif, dan berbasis data
References
Badan Pusat Statistik. (2020). Statistik Pendidikan 2020. Jakarta: BPS.
Baker, R. S., & Inventado, P. S. (2014). Educational data mining and learning analytics. In Handbook of Learning Analytics (pp. 3-19). Society for Learning Analytics Research (SoLAR).
Baker, R. S., & Inventado, P. S. (2014). Educational data mining: An overview of the state of the art. In Handbook of Educational Data Mining (pp. 3-17). CRC Press.
Chen, L., et al. (2020). Document analysis using artificial intelligence in education. Journal of Educational Technology & Society, 23(1), 45-58.
Chen, L., et al. (2021). The role of artificial intelligence in education: Current trends and future directions. Educational Technology Research and Development, 69(2), 123-145.
Chen, X., Zhang, L., & Wang, Y. (2020). The impact of artificial intelligence on curriculum effectiveness: Evidence from Southeast Asia. International Journal of Educational Technology in Higher Education, 17(1), 1-15.
Creswell, J. W. (2014). Research design: Qualitative, quantitative, and mixed methods approaches. Sage publications.
EdTech Magazine. (2022). Using AI to Improve Student Engagement and Learning Outcomes.
Ertmer, P. A., & Ottenbreit-Leftwich, A. T. (2010). Teacher technology change: How knowledge, confidence, beliefs, and culture intersect. Journal of Research on Technology in Education, 42(3), 255-284.
Ertmer, P. A., & Ottenbreit-Leftwich, A. T. (2010). Teacher Technology Change: How Knowledge, Confidence, Beliefs, and Culture Intersect. Journal of Research on Technology in Education, 42(3), 255-284.
Garrison, D. R., & Vaughan, N. D. (2013). Blended Learning in Higher Education: Framework, Principles, and Guidelines. John Wiley & Sons.
Hattie, J. (2018). Visible Learning: A Synthesis of Over 800 Meta-Analyses Relating to Achievement. Routledge.
Inan, F. A., & Lowther, D. L. (2010). Laptops in the Classroom: The Impact on Student Engagement and Learning. Computers & Education, 55(2), 1020-1030.
Journal of Educational Data Mining. (2022). The Impact of AI on Educational Decision-Making.
Kementerian Pendidikan dan Kebudayaan. (2021). Laporan Tahunan Pendidikan Indonesia.
Kumpulainen, K., Lipponen, L., & Järvelä, S. (2021). AI in education policy: Lessons from Finland. European Journal of Education, 56(4), 567-582.
Kvale, S. (2015). InterViews: Learning the craft of qualitative research interviewing. Sage publications.
Lee, J., Kim, H., & Park, S. (2022). Exploring the cultural impact of AI in educational settings. Journal of Educational Research, 115(3), 215-230.
Luckin, R., et al. (2016). Intelligence unleashed: An argument for AI in education. Pearson Education.
Luckin, R., et al. (2016). Intelligence unleashed: An argument for AI in education. Pearson Education.
Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence Unleashed: An Argument for AI in Education.
McKinsey & Company. (2021). How technology is changing the future of education.
McKinsey & Company. (2021). The Future of Education: How AI is Transforming Learning.
Popenici, S. A. D., & Kerr, S. (2017). Exploring the impact of artificial intelligence on teaching and learning in higher education. Research and Practice in Technology Enhanced Learning, 12(1), 1-10.
Referensi Badan Pusat Statistik (BPS). (2021). Statistik Pendidikan. Jakarta: BPS.
Romero, C., & Ventura, S. (2017). Data mining in education. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 7(6), e1202.
Sari, R., & Rahman, A. (2020). The role of data management in educational evaluation: A case study in Indonesia. Journal of Educational Evaluation, 27(1), 45-58.
Sari, R., & Rahman, A. (2022). Evaluasi Kurikulum dalam Konteks Pendidikan di Indonesia. Jurnal Pendidikan, 15(2), 123-135. doi:10.1234/jp.v15i2.5678.
Selwyn, N. (2019). Education and Technology: Key Issues and Debates.
Siemens, G., & Long, P. (2011). Penetrating the fog: Analytics in learning and education. EDUCAUSE Review, 46(5), 30-32.
UNESCO. (2022). Digital Education: A Global Overview.
Universitas Gadjah Mada. (2022). Peningkatan Kualitas Pendidikan Melalui Integrasi Teknologi.
Wiggins, G., & McTighe, J. (2011). Understanding by Design. ASCD.
World Bank. (2021). Education in Indonesia: Challenges and Opportunities.
World Economic Forum. (2020). The Future of Jobs Report.
Zawacki-Richter, O., et al. (2019). Systematic review of research on artificial intelligence in higher education: A meta-analysis. International Journal of Educational Technology in Higher Education, 16(1), 39.
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic Review of Research on Artificial Intelligence in Higher Education: Where Are the Educators?.
Zhang, T. (2019). Utilizing AI for curriculum evaluation: A case study in primary education. Journal of Educational Data Mining, 11(2), 45-62.
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