Revitalizing Local Knowledge to Address Students’ Moral Degradation in the Metaverse Era: An Embedded Mixed Methods Digital Sociology Study
DOI:
https://doi.org/10.58258/jisip.v10i2.9993Keywords:
Moral Degradation, Metaverse, Local Wisdom, Digital Sociology, Mixed Methods.Abstract
The rapid development of digital technology, particularly the emergence of the metaverse, has fundamentally reshaped adolescents’ patterns of social interaction, cultural practices, and moral frameworks. While the metaverse provides new opportunities for learning and communication, it also raises serious concerns regarding moral degradation, especially among high school students as digital natives who are highly vulnerable to global influences. The weakening of local cultural values, which have long served as moral compasses, further exacerbates this condition. Therefore, an integrative approach is required to safeguard moral resilience in digital environments. This study aims to measure the level of students’ moral degradation, analyze the relationship between moral perception and moral construction, and explore strategies for revitalizing local wisdom as a mitigation effort. An embedded mixed methods design was employed. Quantitative data were collected from 202 students through a five-point Likert scale questionnaire and analyzed with Jamovi 2.6.44 using descriptive statistics, reliability testing, Pearson correlation, and linear regression. Qualitative data were obtained from semi-structured interviews and focus group discussions with teachers and cultural figures, then analyzed through thematic analysis following Braun and Clarke’s procedures. The results show that both moral perception and moral construction are categorized as high. However, the significant correlation (r = 0.675; p < 0.001) reveals a gap between moral awareness and behavior. Qualitative findings emphasize that local values such as Maja Labo Dahu and Nggahi Rawi Pahu have potential as cultural filters, though their application in virtual interactions remains inconsistent.Downloads
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2026-03-01
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