Integration of Teacher Example in Building Character Education: Growing a Madrasah Generation with Noble Character and Global Insight



Authors (s)


(1) * Erwantana Erwantana   (Universitas Islam Negeri Sunan Ampel Surabaya)  
        Indonesia
(2)  Bayu Setia Giri   (Universitas Pancamarga Probolinggo)  
        Indonesia
(3)  Hudi Setiawan   (Universitas Pancamarga Probolinggo)  
        Indonesia
(*) Corresponding Author

Abstract


This study focuses on the role of teacher example in developing character education in madrasahs. The main objective of this study is to analyze how teacher reputation and influence as role models affect the effectiveness of character education in madrasahs, as well as the factors that support and hinder the process. The research method used is qualitative, with a case study conducted at Madrasah Aliyah Salman Al-Farisi. Data collection techniques include in-depth interviews with teachers, madrasah principals, and students as well as observation and documentation studies. Thematic and content analyses were applied to identify themes and patterns from the data collected. The survey results indicate that strategic interactions between teachers, students, and parents, innovation in educational methods, transformational leadership, and a supportive school culture play a significant role in character development. This study reveals that teacher example as role models contributes significantly to the effectiveness of character education. The implication of this study is the need for a holistic approach that involves the entire school community in supporting student character development. This study provides new insights into how these factors interact and contribute to character education in madrasahs.



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References


Al Shloul, T., Mazhar, T., Abbas, Q., Iqbal, M., Ghadi, Y. Y., Shahzad, T., Mallek, F., & Hamam, H. (2024). Role of activity-based learning and ChatGPT on students’ performance in education. Computers and Education: Artificial Intelligence, 6(April), 100219. https://doi.org/10.1016/j.caeai.2024.100219.

Adhimiy, Syafiqiyah. 2018. “Curriculum Development Through Creative Lesson Plan.” Cendekia: Jurnal Kependidikan Dan Kemasyarakatan 16 (1): 41. https://doi.org/10.21154/cendekia.v16i1.1164.

Adipratama, Zoga. 2018. “Manajemen Kurikulum Terpadu Di Sekolah Alam Berciri Khas Islam.” Jurnal Administrasi Dan Manajemen Pendidikan 1 (3): 372–80. https://doi.org/10.17977/um027v1i32018p372.

Alfiansyah, Muhammad, Yuni Afrilita, Sunan Kalijaga Yogyakarta, and U I N Sumatera Utara. 2021. “Desain Manajemen Kurikulum Sekolah Umum” 14: 116–33.

Alkatiri, Rahmawaty. 2022. “Manajemen Kurikulum Madrasah Aliyah Berorientasi Merdeka Belajar Di Sulawesi Utara.” Journal of Islamic Education Leadership 2 (1): 73–86. https://doi.org/10.30984/jmpi.v2i1.444.

Baharun, H., & Hasanah, R. (2023). Quality Improvement in Increasing Public Trust Using the Failure Mode and Effect Analysis (FMEA) Method. Tarbawi: Jurnal Keilmuan Manajemen Pendidikan, 9(01), 59–68. https://doi.org/10.32678/tarbawi.v9i01.7982

Conde, M., & Rodríguez-Sedano, F. J. (2024). Is learning analytics applicable and applied to education of students with intellectual/developmental disabilities? A systematic literature review. Computers in Human Behavior, 155(February), 108184. https://doi.org/10.1016/j.chb.2024.108184

Du Plooy, E., Casteleijn, D., & Franzsen, D. (2024). Data to support scoping review on: Personalized adaptive learning in higher education - key characteristics and impact on academic performance and engagement. Mendeley Data, 1(21), e39630. https://doi.org/10.1016/j.heliyon.2024.e39630

Ezzaim, A., Dahbi, A., Haidine, A., & Aqqal, A. (2024). Enabling sustainable learning: A Machine Learning Approach for an Eco-friendly Multi-factor Adaptive E-Learning System. Procedia Computer Science, 236(2023), 533–540. https://doi.org/10.1016/j.procs.2024.05.063

Fischer, I., Sweeney, S., Lucas, M., & Gupta, N. (2024). Making sense of generative AI for assessments: Contrasting student claims and assessor evaluations. International Journal of Management Education, 22(3), 101081. https://doi.org/10.1016/j.ijme.2024.101081

Han, J., Liu, G., Liu, X., Yang, Y., Quan, W., & Chen, Y. (2024). Continue using or gathering dust? A mixed method research on the factors influencing the continuous use intention for an AI-powered adaptive learning system for rural middle school students. Heliyon, 10(12), e33251. https://doi.org/10.1016/j.heliyon.2024.e33251

Hasanah, R., Munawwaroh, I., Qushwa, F. G., & Agus R, A. H. (2024). Pengembangan Career Adaptability Melalui Inovasi Sumber Daya Manusia. EDUKASIA: Jurnal Pendidikan Dan Pembelajaran, 5(1), 169–178. https://doi.org/10.62775/edukasia.v5i1.734

Honig, C., Desu, A., & Franklin, J. (2024). GenAI in the classroom: Customized GPT Roleplay for Process Safety Education. Education for Chemical Engineers, 49(August), 55–66. https://doi.org/10.1016/j.ece.2024.09.001

Köhler, T. (2024). Multilevel qualitative research: Insights from practice. European Management Journal, March. https://doi.org/10.1016/j.emj.2024.03.011

Lai, C. Y., Cheung, K. Y., & Chan, C. S. (2023). Exploring the role of intrinsic motivation in ChatGPT adoption to support active learning: An extension of the technology acceptance model. Computers and Education: Artificial Intelligence, 5(October), 100178. https://doi.org/10.1016/j.caeai.2023.100178

Liu, Y., Razman, M. R., Syed Zakaria, S. Z., Lee, K. E., Khan, S. U., & Albanyan, A. (2024). Personalized context-aware systems for sustainable agriculture development using ubiquitous devices and adaptive learning. Computers in Human Behavior, 160(February), 108375. https://doi.org/10.1016/j.chb.2024.108375

Naseer, F., Khan, M. N., Tahir, M., Addas, A., & Aejaz, S. M. H. (2024). Integrating deep learning techniques for personalized learning pathways in higher education. Heliyon, 10(11), e32628. https://doi.org/10.1016/j.heliyon.2024.e32628

Obourdin, G., de Maeyer, S., & Van den Bossche, P. (2024). Unlocking the power of immersive learning: The FAIRI instructional design proposition for adaptive immersive virtual reality. Computers and Education: X Reality, 5(December 2023), 100084. https://doi.org/10.1016/j.cexr.2024.100084

Pimdee, P., Sukkamart, A., Nantha, C., Kantathanawat, T., & Leekitchwatana, P. (2024). Enhancing Thai student-teacher problem-solving skills and academic achievement through a blended problem-based learning approach in online flipped classrooms. Heliyon, 10(7), e29172. https://doi.org/10.1016/j.heliyon.2024.e29172

Saifi, A. G., Khlaif, Z. N., & Affouneh, S. (2024). The effect of using community-based learning program in science students’ achievement according to Kolb’s learning styles. Social Sciences and Humanities Open, 10(July), 101125. https://doi.org/10.1016/j.ssaho.2024.101125

Salem Abdullah Bajaber, S. (2024). Factors influencing students willingness to continue online learning as a lifelong learning: A path analysis based on MOA theoretical framework. International Journal of Educational Research Open, 7(July), 100377. https://doi.org/10.1016/j.ijedro.2024.100377

Soori, M., Jough, F. K. G., Dastres, R., & Arezoo, B. (2024). AI-Based Decision Support Systems in Industry 4.0, A Review. Journal of Economy and Technology. https://doi.org/10.1016/j.ject.2024.08.005

Tian, X. (2024). Personalized translator training in the era of digital intelligence: Opportunities, challenges, and prospects. Heliyon, 10(20), e39354. https://doi.org/10.1016/j.heliyon.2024.e39354

Zhang, Y., Lucas, M., Bem-haja, P., & Pedro, L. (2024). The effect of student acceptance on learning outcomes: AI-generated short videos versus paper materials. Computers and Education: Artificial Intelligence, 7(June), 100286. https://doi.org/10.1016/j.caeai.2024.100286




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