THE PRACTICE OF DEEP LEARNING IN ENGLISH CLASSES: A CASE STUDY OF JUNIOR HIGH SCHOOLS IN SEMARANG CITY
DOI:
https://doi.org/10.26877/jp3.v12i1.530Keywords:
deep learning, pengajaran Bahasa Inggris, tantanganAbstract
Penelitian ini mengkaji implementasi Deep Learning dalam pembelajaran Bahasa Inggris di Sekolah Menengah Pertama di Kota Semarang. Data dikumpulkan melalui kuesioner, wawancara, dan observasi kelas. Kuesioner ditujukan kepada 66 guru Bahasa Inggris, sementara wawancara dan observasi dilakukan di dua sekolah dengan melibatkan guru dan siswa sebagai responden. Hasil penelitian menunjukkan adanya sikap yang secara umum positif terhadap Deep Learning, namun juga menekankan perlunya pelatihan dan dukungan institusional. Tercatat bahwa 37,9% responden melaporkan belum pernah mengikuti pelatihan apa pun yang berkaitan dengan Deep Learning. Para guru mengidentifikasi empat tantangan utama dalam mengimplementasikan Deep Learning di kelas mereka, yaitu kurangnya pelatihan atau pengetahuan tentang Deep Learning (69,7%), keterbatasan waktu dalam kurikulum (36,4%), jumlah siswa yang besar dalam satu kelas (48,5%), serta kurangnya sumber daya pembelajaran (28,8%).
References
Bhardwaj, P., Gupta, P. K., Panwar, H., Siddiqui, M. K., Morales-Menendez, R., & Bhaik, A. (2021). Application of deep learning on student engagement in e-learning environments. Computers & Electrical Engineering, 93, 107277. https://doi.org/10.1016/j.compeleceng.2021.107277
Gao, Y., Zhou, L., & He, J. (2025). Classroom expression recognition based on deep learning. Applied Sciences, 15(1), 166. https://doi.org/10.3390/app15010166
Hu, X. (2023). The role of deep learning in the innovation of smart classroom teaching mode under the background of internet of things and fuzzy control. Heliyon, 9(8), e18594. https://doi.org/10.1016/j.heliyon.2023.e18594
Indraganti, M. (2017). Enquiry-based learning workshop for deep learning in Middle Eastern classrooms – an action research approach. Educational Action Research, 26(4), 603–625. https://doi.org/10.1080/09650792.2017.1379423
Jaykumar, P., Gandhi, S., Katheriya, V., Pataliya, P., & Majumdar, A. (2025). Enhancing classroom attendance systems with face recognition through CCTV using deep learning. Procedia Computer Science, 258, 3031–3041. https://doi.org/10.1016/j.procs.2025.04.561
Kartal, M. (2020). Facilitating deep learning and professional skills attainment in the classroom: The value of a model United Nations course. Journal of Political Science Education, 17(sup1), 148–168. https://doi.org/10.1080/15512169.2020.1854771
Kovač, V. B., Nome, D. Ø., Jensen, A. R., & Skreland, L. L. (2023). The why, what and how of deep learning: critical analysis and additional concerns. Education Inquiry. https://doi.org/10.1080/20004508.2023.2194502
Ling, X., Yang, J., Liang, J., Zhu, H., & Sun, H. (2022). A deep-learning based method for analysis of students’ attention in offline class. Electronics, 11(17), 2663. https://doi.org/10.3390/electronics11172663
Price, J. (2004). A parent in the classroom – A valuable way of fostering deep learning for the children’s nursing student. Nurse Education in Practice, 4(1), 5–11. https://doi.org/10.1016/S1471-5953(03)00005-2
Qing, W. (2024). A study on the design of a deep learning model for classroom based on user participation and game chemistry processes. Entertainment Computing, 51, 100727. https://doi.org/10.1016/j.entcom.2024.100727
Smith, T. W., & Colby, S. A. (2007). Teaching for deep learning. The Clearing House: A Journal of Educational Strategies, Issues and Ideas, 80(5), 205–210. https://doi.org/10.3200/TCHS.80.5.205-210
Thind, B., Multani, K., & Cao, J. (2022). Deep learning with functional inputs. Journal of Computational and Graphical Statistics, 32(1), 171–180. https://doi.org/10.1080/10618600.2022.2097914
Trabelsi, Z., Alnajjar, F., Parambil, M. M. A., Gochoo, M., & Ali, L. (2023). Real-time attention monitoring system for classroom: A deep learning approach for student’s behavior recognition. Big Data and Cognitive Computing, 7(1), 48. https://doi.org/10.3390/bdcc7010048
Wang, J. S., Pascarella, E. T., Nelson Laird, T. F., & Ribera, A. K. (2014). How clear and organized classroom instruction and deep approaches to learning affect growth in critical thinking and need for cognition. Studies in Higher Education, 40(10), 1786–1807. https://doi.org/10.1080/03075079.2014.914911
Weng, C., Chen, C., & Ai, X. (2023). A pedagogical study on promoting students’ deep learning through design-based learning. International Journal of Technology and Design Education, 33, 1653–1674. https://doi.org/10.1007/s10798-022-09789-4
West, L., & Halvorson, D. (2019). Student engagement and deep learning in the first-year international relations classroom: Simulating a UN Security Council debate on the Syrian crisis. Journal of Political Science Education, 17(2), 173–190. https://doi.org/10.1080/15512169.2019.1616298
Zhang, J., Ji, X., Li, Y., Zhang, H., & Meng, L.-N. (2025). Deep learning approach in undergraduate nursing students and their relationship with learning outcomes: A latent profile analysis. Nurse Education in Practice, 85, 104379. https://doi.org/10.1016/j.nepr.2025.104379
Zheng, Y., & Wang, C. (2023). An activity architecture of deep learning for students in smart classroom. Frontiers in Educational Research, 6(19), 11–18. https://doi.org/10.25236/FER.2023.061903
Zhong, Y. (2025). Experience of intelligent speech robot in music online classroom based on deep learning and virtual reality. Entertainment Computing, 52, 100795. https://doi.org/10.1016/j.entcom.2024.100795
Zhu, Z., Xu, Z., & Liu, J. (2023). Flipped classroom supported by music combined with deep learning applied in physical education. Applied Soft Computing, 145, 110039. https://doi.org/10.1016/j.asoc.2023.110039
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