An Intelligent AI Check-In Framework for Automating International Student Onboarding and Administrative Services
DOI:
https://doi.org/10.67303/jcit.v1i1.25Keywords:
Artificial Intelligence, Neural networks, natural language, natural language, AI-driven solutionsAbstract
International and transfer student check-in processes involve complex, multi-step workflows that can be streamlined with artificial intelligence (AI). This paper presents the design and implementation of an AI-driven check-in agent that automates student onboarding tasks in a university setting. The agent integrates a graphical user interface (GUI) with AI capabilities to guide students through login/authentication, document uploads, advisor assignment based on region, course pre-selection, and real-time status tracking. We provide a comprehensive literature review of similar systems in the U.S. and globally, highlighting how institutions have leveraged chatbots and AI for admissions and orientation. The system’s architecture is described with a technical focus on its Python-based implementation (Tkinter for GUI, PIL for imaging), web integration through Jupyter Notebook compatibility, and open-source API utilization (including BeeWare for cross-platform deployment). We detail each system component and discuss security measures (compliance with FERPA, GDPR) to protect educational data privacy. Challenges such as user adoption, multilingual support, and integration with cloud services are examined, along with future enhancements like machine learning-driven personalization. The paper concludes with expected benefits in institutional efficiency and student satisfaction, positioning the AI check-in agent as a valuable contribution to smart campus initiatives.
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