Application of Deep Learning-Based Tolerance Values to Support Classroom Management in Class VI SDN Beji 01 Ungaran Timur
DOI:
https://doi.org/10.62951/icgel.v2i2.192Keywords:
Classroom Management, Deep Learning, Inclusive Education, Pedagogical Approach, Tolerance ValuesAbstract
This study aims to describe the application of deep learning based tolerance values with a pedagogical approach in supporting classroom management in grade VI of SDN Beji 01 East Ungaran. The deep learning approach is understood as a pedagogical strategy that emphasizes the cognitive, affective, and social engagement of students through meaningful learning experiences. This study uses a descriptive qualitative approach with data collection techniques in the form of semi-structured interviews, observations, and documentation. The research subjects include grade VI teachers, principals, and students with diverse social and cultural backgrounds. The results of the study show that the application of tolerance values through deep learning strategies is able to create an inclusive, safe, and conducive classroom climate. The implementation is reflected through the practice of random seating arrangements, a culture of sharing learning media, deliberation in conflict resolution, fair study timing, and strengthening mutual respect between students. These findings confirm that the integration of deep learning-based tolerance values contributes significantly to the effectiveness of classroom management and the strengthening of the social character of elementary school students.
References
Bank, J. A. (2015). Cultural diversity and education: Foundation, curriculum, and teaching (6th ed.). Routledge.
Bank, J. A., & Bank, C. A. M. (2019). Multicultural education: Issues and perspectives (10th ed.). Wiley.
Baker, R. S., & Invented, P. S. (2014). Educational data mining and learning analytics. In J. A. Larusson & B. White (Eds.), Learning analysis: From research to practice (pp. 61–75). Springer.
Carter, N., Bryant-Lukosius, D., DiCenso, A., Blythe, J., & Neville, A. J. (2021). The use of triangulation in qualitative research. Oncology Nursing Forum, 48(3), 234–243. https://doi.org/10.1188/21.ONF.234-243
Charles, C. M. (2011). Building classroom discipline (10th ed.). Pearson.
Creswell, J. W., & Poth, C. N. (2021). Qualitative inquiry and research design: Choosing between five approaches (4th ed.). SAGE Publications.
Dreikurs, R. (2011). Democratic classroom management. In C. M. Charles, Building classroom discipline (10th ed.). Pearson.
Evertson, C. M., & Weinstein, C. S. (2013). Classroom management handbook: Research, practice, and contemporary issues. Routledge.
Fullan, M., Quinn, J., & McEachen, J. (2018). Deep learning: Engage the world, change the world. Corwin.
Hamre, B. K., & Pianta, R. C. (2009). Class Assessment System (CLASS) Manual: Basic. Paul H. Brookes Publishing.
Hoplock, L., Evans, A., & Stewart, M. (2021). Learning digital diversity to foster social empathy in primary education. Journal of Educational Technology Development and Exchange, 14(1), 45–59.
Kagan, S., & Kagan, M. (2009). Pembelajaran kooperatif Kagan. Penerbitan Kagan.
LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521(7553), 436–444. https://doi.org/10.1038/nature14539
Levinson, M., & Bolgrien, J. (2020). Visual narrative learning for the teaching of social values in schools. Journal of Moral Education, 49(3), 289–304.
Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: Arguments for AI in education. Pearson.
Miles, M. B., Huberman, A. M., & Saldaña, J. (2020). Qualitative data analysis: Method source book (4th ed.). SAGE Publications.
Mustafiz, M., & Dugan, J. P. (2020). Project-based learning for character education in elementary schools. Journal of Character Education, 16(2), 67–82.
Putri, A., Suyanto, S., & Rahmawati, D. (2021). Dynamic seating arrangements and social interaction in elementary school classrooms. Journal of International Instruction, 14(3), 233–248.
Rawani, F., Kurniawan, R., & Saputra, H. (2023). Technology-based character learning in multicultural basic education. Journal of Multicultural Education, 17(2), 98–113.
Riyanti, D., & Hartono, H. (2024). Cross-identity project collaboration in basic digital learning tasks. Journal of Educational Innovation, 21(1), 45–60.
Riyanti, D., Hartono, H., & Sulastri, S. (2022). Crossing the boundaries of identity in the collaboration of digital projects of elementary students. International Journal of Basic Education, 6(2), 134–146.
Rukajat, A. (2022). Qualitative research approach. Deepublish.
Sari, D., & Nugroho, A. (2022). Internalize the values of tolerance through visual media in elementary schools. Journal of Character Education Research, 8(1), 55–66.
Septiani, R., Lestari, D., & Wahyuni, S. (2022). Reflective digital media in basic character education. Journal of Educational Media and Technology, 6(2), 89–102.
Siemens, G. (2005). Connectivityism: Learning theory for the digital age. International Journal of Instructional Technology and Distance Learning, 2(1), 3–10.
Tomlinson, C. A. (2014). Different classes: Responding to the needs of all learners (2nd ed.). ASCD.
UNESCO. (1995). Declaration of principles on tolerance. UNESCO publications.
Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Harvard University Press.
Wentzel, K. R., & Looney, L. (2007). Socialization in the school environment. In J. E. Grusec & P. D. Hastings (Eds.), Handbook of socialization (pp. 382–403). Guilford Press.
Zawacki-Richter, O., Marin, V. I., Bond, M., & Gouverneur, F. (2019). A systematic review of the applications of artificial intelligence in higher education. International Journal of Educational Technology in Higher Education, 16(39), 1–27. https://doi.org/10.1186/s41239-019-0171-0
