SIKASIH (Sistem Informasi Kejadian Siswa Terkasih) As A Learning Development Based on Overcoming Toxic Behavior on Social Media

Penulis

  • Asep Risman Somantri Sociology Education, Faculty of Social Science Education, Universitas Pendidikan Indonesia, Indonesia http://orcid.org/0000-0003-3614-6530
  • Elly Malihah Sociology Education, Faculty of Social Science Education, Universitas Pendidikan Indonesia, Indonesia
  • Siti Nurbayani Sociology Education, Faculty of Social Science Education, Universitas Pendidikan Indonesia, Indonesia

DOI:

https://doi.org/10.33394/jp.v11i1.9586

Kata Kunci:

Sikasih, Learning Model, Toxic Behavior, Social Media.

Abstrak

This research aims to describe in more depth students' experiences in dealing with toxic behaviour on social media then the researchers created a learning model based on handling toxic behaviour on social media. This research used a qualitative approach with descriptive methods because this research describes a realistic view of the social world experienced by the resource person so that this experience can then be used as a reference for researchers in developing a learning model based on handling toxic behaviour on social media. The subjects of this research involved 1200 students in the Bandung Regency area. The data collection techniques were observation, document analysis, and in-depth interviews. The data analysis technique refered to interactive model data analysis, while the data validity technique is triangulation. The findings showed that students' responses in dealing with toxic behaviour experience difficulties because there were no clear rules. So, starting from this experience, the SIKASIH model is created as a learning model based on handling toxic behaviour on social media.

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Unduhan

Diterbitkan

2024-01-10

Cara Mengutip

Somantri, A. R., Malihah, E., & Nurbayani, S. (2024). SIKASIH (Sistem Informasi Kejadian Siswa Terkasih) As A Learning Development Based on Overcoming Toxic Behavior on Social Media. Jurnal Paedagogy, 11(1), 197–206. https://doi.org/10.33394/jp.v11i1.9586

Terbitan

Vol 11 No 1 (2024): January

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