This study explored faculty perceptions of using Facial Recognition Technology (FRT) for tracking medical student attendance at a private Saudi medical college. Using a mixed-methods approach, researchers surveyed 112 faculty members and conducted focus groups with 26 participants. The findings revealed a balanced but divided perspective. While a slight majority (51.8%) showed good acceptance, a significant minority (48.2%) did not. Faculty rated the technology highly for its perceived ease of use (85.7%) and effectiveness (75%). However, significant privacy concerns were a major issue for over half of the respondents (55.3%). Qualitative data highlighted key themes, including initial staff reactions to FR technology, the need for better staff communication and training, the balance between efficiency and technical challenges, and deep-seated ethical and privacy concerns related to surveillance. The study concludes that, while faculty see the potential benefits of FRT, successful implementation depends on addressing their legitimate concerns. To succeed, institutions must develop comprehensive strategies that include transparent privacy policies, reliable technology, and robust training for staff. Prioritizing stakeholder engagement and creating culturally sensitive implementation plans are crucial for balancing the benefits of FRT with privacy and ethical considerations.

Proficiency in history-taking is foundational to safe clinical practice, yet traditional teaching methods offer infrequent opportunities for deliberate practice. This study evaluated whether an AI-powered virtual patient chatbot with a custom knowledge base could improve history-taking competence among fifth-year medical students during general medicine rotations. A mixed-method, quasi-experimental, non-equivalent control group design was used. The experimental group (N ≈ 157) engaged with four custom knowledge-based chatbot scenarios, while a control cohort (N ≈ 156) followed traditional training within the same curriculum. Assessment was performed using a validated Objective Structured Clinical Examination across two standardized cases, and user perceptions were gathered using an adapted Technology Acceptance Model survey from 105 students, with qualitative feedback from 32 trained students in a focus group. Compared to the control group, the experimental group demonstrated significant improvements in direct assessments (79.2% vs. 74.8%, p = 0.002) and indirect assessments (81.2% vs. 79%, p = 0.026). Participants reported a high user-perception score (80%) across usefulness, ease, attitude, and behavior. Focus group findings highlighted the chatbot’s value as a safe, flexible, feedback-rich tool. The chatbot-based training improved students’ performance and satisfaction and should serve as a supplementary aid rather than a substitute for real patient interactions.