Implementation of Artificial Intelligence (AI) in HyFlex-Based Final Project Guidance - Sunusi, Seny Luhriyani; Azhari, Ahmad; Sembiring, Surya Anantatama; Safitri, Citra Dwi (Celebes Journal of Language Studies, 2025)
This study aims to analyze the application of artificial intelligence (AI) in HyFlex-based final project guidance and identify the challenges experienced by supervisors and students during the process. The research uses a mixed methods approach involving 12 supervisors and 38 students who actively use AI in the preparation of thesis. Data collection was carried out through structured questionnaires and in-depth interviews, then analyzed using descriptive statistics and qualitative analysis techniques of the Miles & Huberman model. The results showed that the majority of students (94.7%) used AI to help prepare thesis, especially in compiling writing frameworks, improving grammar, understanding theory, and speeding up the revision process. Lecturers also use AI, but more carefully, especially to provide examples of writing improvements and help clarify basic concepts. Although AI has been shown to improve the effectiveness of HyFlex tutoring, both groups face different challenges: students tend to face technical barriers such as unstable networks, device limitations, AI answer errors, and difficulty creating precise prompts; while lecturers face academic challenges such as false references, theoretical inaccuracies, and the risk of student dependence on AI. Overall, the study concludes that AI has great potential to improve the quality, flexibility, and efficiency of final project guidance, but its use still requires strong digital literacy, academic verification, and clear ethical guidelines.