Deep Learning-Enhanced Discovery Learning: Impact on High School Students' Environmental Change Outcomes

Dwi Andini Putri 1 Indonesia , Agung Setia Batubara 1 Indonesia
1 Department of Biology Education, Universitas Negeri Medan, Indonesia
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Published 2026-09-01
Vol. 6 No. 1 (2026) PAGES 15-26
DOI 10.51574/ijrer.v6i1.5306
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This study investigated the effect of the Discovery Learning model integrated with a Deep Learning approach on students’ learning outcomes in the topic of Environmental Change and Conservation. A quasi-experimental design with a Non-equivalent Control Group was employed, involving 70 Grade X students at High School 1 Batang Kuis, Indonesia, divided equally into experimental (n = 35) and control (n = 35) groups. Instruments included 20 higher-order thinking (C4–C6) multiple-choice items administered as pretest and posttest. Data were analysed using the Mann–Whitney U test and Normalised Gain (N-Gain) through IBM SPSS Statistics. Results showed that posttest mean scores were significantly higher in the experimental class (M = 89.57, SD = 7.51) than in the control class (M = 82.14, SD = 10.79). The Mann–Whitney test yielded a significant difference (U = 280.5, p = 0.03), with the experimental group’s mean rank (42.67) exceeding that of the control group (28.33). Furthermore, the experimental class achieved a high N-Gain category (0.78) compared to the moderate category of the control class (0.66). These findings demonstrate that the Discovery Learning–Deep Learning integration effectively promotes conceptual understanding and higher-order cognitive skills in biology education.

Putri , D. A., & Batubara, A. S. (2026). Deep Learning-Enhanced Discovery Learning: Impact on High School Students’ Environmental Change Outcomes . ETDC: Indonesian Journal of Research and Educational Review , 6(1), 15–26. https://doi.org/10.51574/ijrer.v6i1.5306
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  1. Agustin, M. (2026). Implementasi Pendekatan Deep Learning untuk Meningkatkan Kualitas Hasil Belajar Siswa SMA. Al-Irsyad Journal of Mathematics Education, 5(1), 375-386. https://doi.org/10.58917/ijme.v5i1.651
  2. Andayanie, L. M., Adhantoro, M. S., Purnomo, E., & Kurniaji, G. T. (2025). Implementation of deep learning in education: Towards mindful, meaningful, and joyful learning experiences. Journal of Deep Learning, 47-56. https://doi.org/10.23917/jdl.v1i1.11157
  3. Azzahra, W., Gusti, U. A., & Widodo, A. (2023). Inovasi Model Discovery Learning Berbasis Multi Teknologi Pada Materi Perubahan Lingkungan. Jurnal Bioedukasi, 6(2).
  4. Bhardwaj, V., Zhang, S., Tan, Y. Q., & Pandey, V. (2025). Redefining learning: student-centered strategies for academic and personal growth. Frontiers in Education (Vol. 10, p. 1518602). Frontiers Media SA. https://doi.org/10.3389/feduc.2025.1518602
  5. Ching, T., Himmelstein, D. S., Beaulieu-Jones, B. K., Kalinin, A. A., Do, B. T., Way, G. P., ... & Greene, C. S. (2018). Opportunities and obstacles for deep learning in biology and medicine. Journal of the royal society interface, 15(141), 20170387. https://doi.org/10.1098/rsif.2017.0387
  6. Faturrachim, H., & Muanifah, M. T. (2025). Application of the Discovery Learning Model to Improve Mathematical Activities and Conceptual Understanding. International Journal of Basic Educational Research, 2(1), 27-33. https://doi.org/10.14421/ijber.v2i1.11839
  7. Ferinda, P., Mustamiroh, M., Hidayat, T., & Iksam, I. (2026). The Effect of Problem-Based Learning (PBL) through a Deep Learning Approach on Cognitive Learning Outcomes in Science and Social Studies (IPAS) at Elementary School. Edunesia: Jurnal Ilmiah Pendidikan, 7(2), 982-996. https://doi.org/10.51276/edu.v7i2.1653
  8. Gawehn, E., Hiss, J. A., & Schneider, G. (2016). Deep learning in drug discovery. Molecular informatics, 35(1), 3-14. https://doi.org/10.1002/minf.201501008
  9. Goshisht, M. K. (2024). Machine learning and deep learning in synthetic biology: Key architectures, applications, and challenges. ACS omega, 9(9), 9921. https://doi.org/10.1021/acsomega.3c05913
  10. Honra, J. R. (2026). Understanding the influence of biomimetic projects on transdisciplinary thinking in biology education. Innovations in Education and Teaching International, 63(3), 766-780. https://doi.org/10.1080/14703297.2025.2512386
  11. Koyama, D., & Watanabe, T. (2023). Why a dispositional view of ecological literacy is needed. Teaching in Higher Education, 28(5), 1108-1117. https://doi.org/10.1080/13562517.2023.2198637
  12. Mansur, S., & Bare, Y. (2019). Meningkatkan hasil belajar siswa pada konsep perubahan dan pelestarian lingkungan hidup dengan model Discovery Learning di SMAS Katolik ST Gabriel Maumere. BIOEDUSCIENCE: Jurnal Pendidikan Biologi dan Sains, 3(2), 84-89.
  13. Mokoginta, A. P., Hulukati, E. P., & Kobandaha, P. E. (2025). Mathematical Reasoning Ability of Junior High School Students: Application of Discovery Learning Model. ETDC: Indonesian Journal of Research and Educational Review, 4(3), 517-531. https://doi.org/10.51574/ijrer.v4i3.2951
  14. Morris, D. L. (2025). Rethinking science education practices: Shifting from investigation-centric to comprehensive inquiry-based instruction. Education Sciences, 15(1), 73. https://doi.org/10.3390/educsci15010073
  15. Nur, Z., Mulyadi, M., & Nurdiansyah, E. (2025). Show and Tell Learning Method Based on the Discovery Learning Model: Creativity and Learning Outcomes at Primary School. ETDC: Indonesian Journal of Research and Educational Review, 5(1), 564-581. https://doi.org/10.51574/ijrer.v5i1.4350
  16. Nuraida, I., & Mulyanti, D. (2026). Analisis Implementasi Pembelajaran Deep Learning pada Siswa Sekolah Dasar. Jurnal Pendidikan Tambusai, 10(1), 952-958.
  17. Nurwidodo, N., Hindun, I., & Nuryady, M. M. (2026). Integration of deep learning approach and EMKONTAN model to improve environmental literacy, creativity, and collaboration of students. Formatif: Jurnal Ilmiah Pendidikan MIPA, 16(1), 147-158. https://doi.org/10.30998/eemndc10
  18. Ozdem-Yilmaz, Y., & Bilican, K. (2025). Discovery learning—jerome bruner. In Science education in theory and practice: An introductory guide to learning theory (pp. 173-187). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-81351-1_11
  19. Putrayasa, I. M., Syahruddin, S. P., & Margunayasa, I. G. (2014). Pengaruh model pembelajaran discovery learning dan minat belajar terhadap hasil belajar IPA siswa. Mimbar PGSD Undiksha, 2(1). https://doi.org/10.23887/jjpgsd.v2i1.3087
  20. Rahmawati, D. N., Surtikanti, H. K., & Riandi, R. (2024). An examination of the potential of STEM-based biology learning for improving higher order thinking skills. Assimilation: Indonesian Journal of Biology Education, 7(1), 1-10. https://ejournal.upi.edu/index.php/asimilasi/article/view/65479
  21. Sapoval, N., Aghazadeh, A., Nute, M. G., Antunes, D. A., Balaji, A., Baraniuk, R., ... & Treangen, T. J. (2022). Current progress and open challenges for applying deep learning across the biosciences. Nature Communications, 13(1), 1728. https://doi.org/10.1038/s41467-022-29268-7
  22. Schneider, S., Beege, M., Nebel, S., Schnaubert, L., & Rey, G. D. (2022). The cognitive-affective-social theory of learning in digital environments (CASTLE). Educational psychology review, 34(1), 1-38. https://doi.org/10.1007/s10648-021-09626-5
  23. Sharifani, K., & Amini, M. (2023). Machine learning and deep learning: A review of methods and applications. World information technology and engineering journal, 10(07), 3897-3904. https://ssrn.com/abstract=4458723
  24. Sinclair, M. (2026). Learning to be human: Forming and implementing national blends of transformative and holistic education to address 21st century challenges and complement AI. Education Sciences, 16(1), 107. https://doi.org/10.3390/educsci16010107
  25. Talaei Khoei, T., Ould Slimane, H., & Kaabouch, N. (2023). Deep learning: systematic review, models, challenges, and research directions. Neural Computing and Applications, 35(31), 23103-23124. https://doi.org/10.1007/s00521-023-08957-4
  26. Uri, F., Missa, H., & Seran, L. (2024). Pengaruh Model Discovery Learning Terhadap Hasil Belajar Peserta Didik Kelas X Materi Perubahan Lingkungan Di SMA St Arnoldus Janssen Kupang. JBIOEDRA: Jurnal Pendidikan Biologi, 2(2), 337-343. https://journal.unwira.ac.id/index.php/JBIOEDRA/article/view/3746
  27. Webb, S. (2018). Deep learning for biology. Nature, 554(7693), 555-557. https://doi.org/10.1038/d41586-018-02174-z
  28. Widiadnyani, K., Margunayasa, I. G., & Wibawa, I. M. C. (2025). The effect of Kahoot-assisted Discovery Learning model on science learning interest and outcomes. Jurnal Ilmiah Pendidikan dan Pembelajaran, 9(2), 287-295. https://doi.org/10.23887/jipp.v9i2.92924
  29. Xiong, Z., Song, Y., & Zhu, R. (2025). Pedagogical strategies for teaching environmental literacy in secondary school education: A systematic review. Sustainability, 17(20), 9104. https://doi.org/10.3390/su17209104
  30. Yan, J., Cai, J., Zhang, B., Wang, Y., Wong, D. F., & Siu, S. W. (2022). Recent progress in the discovery and design of antimicrobial peptides using traditional machine learning and deep learning. Antibiotics, 11(10), 1451. https://doi.org/10.3390/antibiotics11101451
  31. Zhang, L., Tan, J., Han, D., & Zhu, H. (2017). From machine learning to deep learning: progress in machine intelligence for rational drug discovery. Drug discovery today, 22(11), 1680-1685. https://doi.org/10.1016/j.drudis.2017.08.010

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Keywords
Biology Learning Environmental Conservation Deep Learning Discovery Learning Learning Outcomes