This study investigates how communication driven approach can strengthen virtual mentoring through improved tutor responsiveness, interaction quality, and personalized feedback. Employing a mixed-methods design, data were drawn from usage analytics, online discussion logs, tutor profiles, and student academic records with 51 students enrolled which it had average participant about 33 students, wits one session during one semester complemented by semi-structured interviews and platform observations. Findings reveal delays in feedback, underutilization of interactive features, and student contributions dominated by brief, opinion-based responses lacking references. These limitations undermine communication quality and student engagement. The study highlights AI’s potential to automate routine feedback, provide adaptive interaction, and reduce tutor workload, thereby enabling more meaningful engagement. Practical recommendations are offered for integrating AI into distance education systems to improve communication effectiveness, enhance learner satisfaction, and support academic success at scale. Universitas Terbuka, as Indonesia’s leading public distance-learning institution, continues to face persistent challenges in ensuring effective communication and mentoring in the volatile, uncertain, complex, and ambiguous (VUCA) era.
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