Improving Teaching Engagement and Professional Core Competencies in Higher Vocational Humanities Courses Based on AI Chatbots

AI chatbots are increasingly entering higher vocational humanities courses, providing new possibilities for improving interaction, engagement, and professional core competencies. This study combines natural language processing and instructional design theory to construct an AI chatbot-assisted teaching framework. Using a quasi-experimental design, questionnaire measurement, behavior-log analysis, and academic performance evaluation are employed to examine the influence of chatbots on classroom engagement and competency development. The results show that chatbot-assisted learning significantly improves behavioral, cognitive, and affective engagement, and positively affects critical thinking, communication expression, and autonomous learning ability. Interaction frequency, feedback immediacy, and professionalized task-context design are identified as key moderating variables. The study confirms that natural-language dialogue systems can provide personalized support and real-time learning feedback in humanities instruction. From an engineering perspective, the findings contribute to human-machine interaction design, latency-sensitive feedback systems, and networked learning platforms.