Discovery Learning Sebagai Teori Belajar Populer Lanjutan
DOI:
https://doi.org/10.56480/eductum.v1i2.742
Abstract View:
486
PDF downloads:
2210
Keywords:
Discovery Learning, Learning Theory, EducationAbstract
The learning model is a framework that provides a systematic description for carrying out learning in order to help students learn in a certain way to achieve. That is, the learning model is a plan or a pattern that is used as a guide in planning classroom learning or learning in tutorials. Discovery Learning is a learning method that applies Inquiry-Based Instruction. Discovery Learning is learning that encourages students to investigate on their own, discover and build on past experiences and knowledge, use intuition, imagination, and creativity, and seek new information to find new facts, correlations, and truths. Learning is not the same as absorbing what is said or read, but actively learning to find answers and solutions yourself. Discovery Learning is one of the learning methods known to improve the quality of education in learning in advanced theory.
References
Abadi, C. L. N., & Malang, K. L. K. (2022). Model Discovery Learning dalam Pembelajaran Pendidikan Agama Islam dan Budi Pekerti di Sekolah.
Abdul Majid. (2014). Strategi Pembelajaran. Bandung : Rosdakarya
Ana, N. Y. (2018). Penggunaan model pembelajaran discovery learning dalam peningkatan hasil belajaran siswa di sekolah dasar. Jurnal Imiah Pendidikan dan Pembelajaran, 2(1).
Anwar, A. H. (2021). Implementasi Tujuan Dan Model Pembelajaran Mata Pelajaran Pendidikan Agama Islam Pada Kurikulum 2013 (Penelitian di SMP S Riyadul Mubtadiin Cimanuk Kabupaten Pandeglang) (Doctoral dissertation, UIN SMH BANTEN).
Astari, F. A., Suroso, S., & Yustinus, Y. (2018). Efektifitas Penggunaan Model Discovery Learning Dan Model Problem Based Learning Terhadap Hasil Belajar Ipa Siswa Kelas 3 Sd. Jurnal Basicedu, 2(1), 1-10.
Class, V. I. I., & City, K. K. Meningkatkan Kemampuan Menulis Teks Cerita Fantasi dengan Model Pembelajaran Discovery Learning pada Siswa Kelas VII C SMP Negeri 4 Kendari Kota Kendari.
Elbadawi, M., Gaisford, S., & Basit, A. W. (2021). Advanced machine-learning techniques in drug discovery. Drug Discovery Today, 26(3), 769-777.
Fauzi, A., Zainuddin, Z., & Atok, R. (2018). Penguatan karakter rasa ingin tahu dan peduli sosial melalui discovery learning. Jurnal Teori Dan Praksis Pembelajaran IPS, 2(2), 83-93.
Febriana, R. (2021). Kompetensi guru. Bumi Aksara.
Feng Chun, Miao. 2006. Training Modules on Integrating ICT For Pedagogical Innovation. Makalah disampaikan dalam National Training on Integrating ICT and Taeaching and Learning yang diselenggarakan oleh UNESCO Bangkok bekerja sama dengan SEAMOLEC di jakarta,
Gaudelet, T., Day, B., Jamasb, A. R., Soman, J., Regep, C., Liu, G., ... & Taylor-King, J. P. (2021). Utilizing graph machine learning within drug discovery and development. Briefings in bioinformatics, 22(6), bbab159.
Gupta, R., Srivastava, D., Sahu, M., Tiwari, S., Ambasta, R. K., & Kumar, P. (2021). Artificial intelligence to deep learning: machine intelligence approach for drug discovery. Molecular Diversity, 25(3), 1315-1360.
Hosnan, M. (2014). Pendekatan saintifik dan kontekstual dalam pembelajaran abad 21. Jakarta: Ghalia Indonesia.
IMRON, G. (2021). EKSPERIMENTASI E-LEARNING BERBASIS MOODLE DENGAN PENDEKATAN GUIDED DISCOVERY LEARNING UNTUK MENINGKATKAN KEMAMPUAN BERPIKIR KRITIS DAN KOMUNIKASI MATEMATIS (Doctoral dissertation, UIN Raden Intan Lampung).
Kim, J., Park, S., Min, D., & Kim, W. (2021). Comprehensive survey of recent drug discovery using deep learning. International Journal of Molecular Sciences, 22(18), 9983.
Kristiowati, Y. (2022). ANALISIS PENGGUNAAN MODEL PEMBELAJARAN DISCOVERY LEARNING DALAM MENINGKATKAN HASIL BELAJAR SISWA SEKOLAH DASAR (Studi Kepustakaan) (Doctoral dissertation, FKIP UNPAS).
Kumar, R., & Saha, P. (2022). A review on artificial intelligence and machine learning to improve cancer management and drug discovery. International Journal for Research in Applied Sciences and Biotechnology, 9(3), 149-156.
Lu, Z. (2021). Computational discovery of energy materials in the era of big data and machine learning: a critical review. Materials Reports: Energy, 1(3), 100047.
Mai, H., Le, T. C., Chen, D., Winkler, D. A., & Caruso, R. A. (2022). Machine learning for electrocatalyst and photocatalyst design and discovery. Chemical Reviews, 122(16), 13478-13515.
Muhammad Irfan Al-Amin. "Mengenal Model Pembelajaran Aktif Discovery Learning". Katadata.co.id.
Mustofa, G. (2022). THE TEORI CONTIGUITY EDWIN RAY GUTHRIE:(TEORI BELAJAR ALIRAN BEHAVIORISTIK CONTIGUOUS CONDITIONING DAN PENERAPANNYA DALAM PEMBELAJARAN PAI DI SEKOLAH). EMPOWERMENT: Jurnal Pengabdian Pada Masyarakat, 2(2), 49-66.
Nandy, A., Duan, C., Taylor, M. G., Liu, F., Steeves, A. H., & Kulik, H. J. (2021). Computational discovery of transition-metal complexes: from high-throughput screening to machine learning. Chemical Reviews, 121(16), 9927-10000.
Sagita, V. Pengembangan Bahan Ajar Menggunakan Model Guided Discovery Learning (GDL) Pada Materi Aritmatika Sosial Tingkat SMP (Bachelor's thesis, Jakarta: FITK UIN Syarif Hidayatullah Jakarta).
Sariani, N., Prihantini, M. P., Winarti, P., Indrawati, S. P. I., Jumadi, S. P. I., Suradi, A., & Satria, R. (2021). Belajar dan Pembelajaran. EDU PUBLISHER.
Tao, Q., Xu, P., Li, M., & Lu, W. (2021). Machine learning for perovskite materials design and discovery. npj Computational Materials, 7(1), 1-18.
Vowels, M. J., Camgoz, N. C., & Bowden, R. (2021). D’ya like DAGs? A survey on structure learning and causal discovery. ACM Computing Surveys (CSUR).
Downloads
Published
Issue
Section
License
Copyright (c) 2022 Heri febri yadi, Neviyarni, Herman Nirwana
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-ShareAlike 4.0 International License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
