JISARA

Abstract: The integration of hybrid chatbots into academic websites is transforming institutional communication by fusing the structured precision of rule-based systems with the generative flexibility of Artificial Intelligence. This survey examines the core design mechanisms that drive this redefinition of student support, specifically focusing on dual processing architectures, contextual adaptation, and intent recognition. It further analyzes data integration strategies used to deliver personalized experiences, such as tailored course recommendations and dynamic event suggestions. Beyond technical architecture, this study evaluates the strengths, limitations, and practical applications of hybrid chatbots in enhancing accessibility, scalability, and user satisfaction within the university environment. These insights equip researchers and developers with a strategic guide for enhancing chatbot efficacy within higher education. Distinguishing itself from generalist reviews, this survey specifically addresses the challenge of integrating academic jargon, offering a concrete blueprint for building resilient, domain-aware student support systems.

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Recommended Citation: Rao, S., Li, L., Haddad, H., He, S., (2026). Architecting the Academic Assistant: A Review of Dual-Processing Architectures and Hybrid Chatbot Design in Higher Education. Journal of Information Systems Applied Research and Analytics 19(1) pp 15-25. https://doi.org/10.62273/XQBK2345