This conceptual article develops a model of positive LinkedIn communication, arguing that responsive, affirming, and authentic interaction—organized into two higher-order behavioral dimensions—strengthens perceived support and trust, thereby shaping professional outcomes (e.g., recruitment, collaboration, and commercial opportunities). By shifting attention from static profile signals to communicative behaviors enacted in posts, comments, and messages, the framework advances testable propositions and specifies mechanisms, boundary conditions, and potential trade-offs that invite empirical evaluation across organizational and cultural contexts.

This article examines how artificial intelligence is transforming instructor-student communication and student evaluation in higher education. By comparing traditional and AI-mediated communication practices, the study synthesizes current literature on opportunities, challenges, and ethical considerations. The analysis highlights the need for digital literacy, emotionally intelligent AI tools, and balanced pedagogical strategies. Practical and theoretical propositions are provided to guide educators in leveraging AI while preserving human-centered teaching values.