Model Pembelajaran Berbasis Deep Learning Untuk Kelas Digital

Authors

  • Nur Indah Margi Utami Madrasah Aliyah Negeri Sukoharjo Author
  • Ririn Sri Sumasni Madrasah Aliyah Negeri Sukoharjo Author
  • Irwan Rilandi Madrasah Aliyah Negeri Sukoharjo Author

DOI:

https://doi.org/10.64845/jimi.v2i1.160

Keywords:

Deep Learning, Kelas Digital, Pembelajaran Bermakna, Model Pembelajaran

Abstract

Perkembangan teknologi digital telah mendorong transformasi pembelajaran menuju kelas digital yang menuntut model pembelajaran inovatif, adaptif, dan berpusat pada peserta didik. Penelitian ini bertujuan mengembangkan Model Pembelajaran Berbasis Deep Learning yang dirancang untuk meningkatkan kualitas pembelajaran di kelas digital melalui penguatan pemahaman konseptual, keterampilan berpikir tingkat tinggi, serta literasi digital peserta didik. Model ini mengintegrasikan prinsip deep learning Pendidikan meliputi pembelajaran bermakna, keterlibatan aktif, refleksi kritis, dan kolaborasi dengan pemanfaatan teknologi digital sebagai media dan sumber belajar. Pendekatan pengembangan model dilakukan melalui kajian teoretis dan analisis kebutuhan pembelajaran digital, yang kemudian dirumuskan dalam sintaks pembelajaran mencakup tahap orientasi masalah, eksplorasi mendalam, analisis dan konstruksi pengetahuan, refleksi, serta evaluasi autentik. Hasil kajian menunjukkan bahwa Model Pembelajaran Berbasis Deep Learning mampu mendorong keterlibatan belajar yang lebih aktif, meningkatkan kemampuan berpikir kritis dan kreatif, serta memperkuat kemandirian belajar peserta didik di kelas digital. Model ini diharapkan menjadi alternatif strategis bagi pendidik dalam mengoptimalkan pembelajaran digital yang bermakna, efektif, dan berorientasi pada keterampilan abad ke-21.

References

Alim, M., & Suryani, N. (2022). Kecerdasan Buatan dalam Pendidikan Digital: Peluang dan Tantangan. Jakarta: Prenadamedia Group

Biggs, J., & Tang, C. (2011). Teaching for quality learning at university. Higher Education Research & Development, 30(6), 741–756. https://doi.org/10.1080/07294360.2011.64283

Bond, M., Buntins, K., Bedenlier, S., Zawacki-Richter, O., & Kerres, M. (2020). Mapping research in student engagement and educational technology. International Journal of Educational Technology in Higher Education, 17(1), 1–30. https://doi.org/10.1186/s41239-019-0176-8

Chi, M. T. H., & Wylie, R. (2014). The ICAP framework: Linking cognitive engagement to active learning outcomes. Educational Psychologist, 49(4), 219–243. https://doi.org/10.1080/00461520.2014.965823

Dede, C. (2014). The role of digital technologies in deeper learning. Educational Technology, 54(5), 21–25.

Fredricks, J. A., Blumenfeld, P. C., & Paris, A. H. (2004). School engagement: Potential of the concept, state of the evidence. Review of Educational Research, 74(1), 59–109. https://doi.org/10.3102/00346543074001059

Garrison, D. R., & Vaughan, N. D. (2008). Blended learning in higher education: Framework, principles, and guidelines. Internet and Higher Education, 10(2), 87–95. https://doi.org/10.1016/j.iheduc.2007.10.001

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

Hattie, J. (2009). Visible learning: A synthesis of over 800 meta-analyses relating to achievement. Educational Research Review, 3(2), 81–112. https://doi.org/10.1016/j.edurev.2008.07.001

Johnson, D. W., Johnson, R. T., & Smith, K. A. (2014). Cooperative learning: Improving university instruction by basing practice on validated theory. Journal on Excellence in College Teaching, 25(3–4), 85–118.

Kahu, E. R. (2013). Framing student engagement in higher education. Studies in Higher Education, 38(5), 758–773. https://doi.org/10.1080/03075079.2011.598505

Kemendikbudristek. (2023). Panduan Transformasi Digital dalam Pembelajaran Abad 21. Jakarta: Direktorat Jenderal Pendidikan Tinggi.

Kurniawan, R. (2021). Penerapan Artificial Intelligence dalam Dunia Pendidikan di Indonesia. Jurnal Teknologi Pendidikan, 9(2), 85–97.

Martin, F., & Bolliger, D. U. (2018). Engagement matters: Student perceptions on the importance of engagement strategies in online learning. Online Learning Journal, 22(1), 205–222. https://doi.org/10.24059/olj.v22i1.1092

Mayer, R. E. (2019). Thirty years of research on online learning. Applied Cognitive Psychology, 33(2), 152–159. https://doi.org/10.1002/acp.3482

Ng, A. (2020). Machine Learning Yearning: Technical Strategy for AI Engineers. Deeplearning.ai.

UNESCO. (2021). Artificial Intelligence in Education: Challenges and Opportunities for Sustainable Development. Paris: UNESCO Publishing.

Prince, M. (2004). Does active learning work? A review of the research. Journal of Engineering Education, 93(3), 223–231. https://doi.org/10.1002/j.2168-9830.2004.tb00809.x

Schindler, L. A., Holgado, D., & Williams, M. A. (2017). Computers in education: A meta-analysis of digital learning engagement. Computers & Education, 111, 1–17. https://doi.org/10.1016/j.compedu.2017.02.006

Sun, C., Shrivastava, A., Singh, S., & Gupta, A. (2017). Revisiting Unreasonable Effectiveness of Data in Deep Learning Era. IEEE International Conference on Computer Vision.

Zepke, N., & Leach, L. (2010). Improving student engagement: Ten proposals for action. Active Learning in Higher Education, 11(3), 167–177. https://doi.org/10.1177/1469787410379680

Zhou, Z. H. (2021). A Brief Introduction to Weakly Supervised Learning. National Science Review, 5(1), 44–53.

Downloads

Published

2026-01-06

Issue

Vol. 2 No. 1 (2026): Jurnal Ilmiah Multidisiplin Indonesia

Section

Articles

License

Copyright (c) 2025 Nur Indah Margi Utami, Ririn Sri Sumasni, Irwan Rilandi

Creative Commons License

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

How to Cite

Model Pembelajaran Berbasis Deep Learning Untuk Kelas Digital. (2026). Jurnal Ilmiah Multidisiplin Indonesia, 2(1), 21-32. https://doi.org/10.64845/jimi.v2i1.160