Pengaruh Norma Sosial Terhadap Penggunaan Artificial Intelligence
Abstract
This study examines the influence of social norms on the use of Generative Artificial Intelligence (AI) as a learning support tool in higher education. The research employed a quantitative approach using a survey method involving 33 undergraduate students from various academic programs, representing diverse disciplinary backgrounds. Data were collected through a Likert-scale questionnaire and analyzed descriptively using frequency distributions, percentages, and mean values.The results indicate that support from the learning environment is the social norm indicator with the highest mean score. This finding suggests that a supportive academic environment plays a crucial role in encouraging students to use Generative AI positively as a learning aid. In contrast, direct social pressure from lecturers or peers shows the lowest mean score, indicating that students’ use of AI is not driven by coercion but rather by personal awareness and academic needs.Regarding AI usage behavior, the findings reveal that most students use Generative AI primarily to support academic tasks and consistently apply it for learning purposes. Moreover, students tend to adjust their use of AI to align with prevailing academic norms and institutional rules. The low tendency to use AI without considering academic regulations reflects a relatively strong level of ethical awareness among students.Overall, the study demonstrates that supportive social norms exert a greater influence than coercive norms in shaping students’ behavior toward the use of Generative AI. These findings suggest that AI adoption in higher education is largely oriented toward enhancing learning quality and maintaining academic integrity, and they may serve as a reference for institutions in developing responsible and ethical AI usage policies.
Fields of Study & Subjects
Artificial Intelligence in Healthcare and Education
Educational Curriculum and Learning Methods
Technology-Enhanced Education Studies
Publication details
- Journal / source
- Figshare
- Publication date
- 1 January 2026