Academic Advising Chatbots and Student Help-Seeking Behavior

Rebecca J. Morgan

Academic Advising Chatbots and Student Help-Seeking Behavior

Author(s)	Dr. Rebecca J. Morgan
Country	United States
Abstract	Academic help-seeking is an important self-regulated learning and student-success behavior, yet students frequently delay or avoid seeking assistance because of uncertainty, inconvenience, perceived judgment, limited adviser availability, or difficulty identifying the appropriate support channel. A systematic review of college academic help-seeking identified academic performance, help resources, influencing factors, and online help-seeking as recurring themes in the literature. Artificial-intelligence chatbots create a potentially important new entry point because they can provide rapid conversational access to institutional information and can initiate proactive outreach at scales that would be difficult to reproduce entirely through human advising. Experimental evidence published in 2026 found that course-embedded chatbot outreach increased engagement with academic supports such as tutoring as well as course performance. This study examines how different academic-advising chatbot architectures could alter student help-seeking behavior. A synthetic population of 600 higher-education students and 4,800 advising opportunities was modeled across four support environments: conventional human advising and self-service portals, rule-based FAQ chatbots, generative advising chatbots without structured human escalation, and human-in-the-loop adaptive advising chatbots. Outcomes included help-seeking initiation, time to first response, issue-resolution quality, appropriate human escalation, help-seeking confidence, support equity, and inappropriate AI-only resolution. The generative chatbot without structured escalation increased accessibility but produced a substantially higher rate of inappropriate AI-only resolution. The findings support a distinction between access automation and advising replacement. Contemporary research indicates that students may increasingly select generative AI as an initial source of academic help.. A separate classroom deployment found that students used AI support extensively, but 22% of generated hints were rated unhelpful and only a small proportion of those unhelpful interactions were escalated to instructors. These findings demonstrate that availability of escalation does not guarantee appropriate escalation behavior.
Keywords	academic advising chatbot, student help-seeking, artificial intelligence in higher education, generative AI, human-in-the-loop advising, student support, academic help-seeking, chatbot adoption, higher education, student success
Field	Engineering
Published In	Volume 3, Issue 6, November-December 2022
Published On	2022-11-05

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American Journal of Advanced Multidisciplinary Innovation and Research

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Academic Advising Chatbots and Student Help-Seeking Behavior

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