Engage, Reflect, Improve: Enhancing Statistical Consulting Courses with AI Simulations.

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Bibliographic Details
Title:	Engage, Reflect, Improve: Enhancing Statistical Consulting Courses with AI Simulations.
Authors:	Guerrero, Matheus Bartolo^1,2, Le, Sunny Nguyet³, Jaynes, Jessica³
Source:	Ohio Journal of School Mathematics. Summer2026, Vol. 103, p1-24. 24p.
Subject Terms:	Student engagement, Graduate education, *Ethical problems, Simulation methods & models, Professional practice, Statistical services, Justification (Theory of knowledge)
Abstract:	This paper describes an AI-infused simulation designed to enhance graduate-level statistical consulting education by bridging theoretical learning with realistic professional practice. Piloted in a master's-level capstone course, the simulation engaged students in consultations with an AI client, requiring them to practice communication, problem framing, methodological justification, and decision-making under authentic conditions. Evidence drawn from interaction transcripts and student reflections showed growth in consulting skills and technical confidence, alongside challenges such as an overly knowledgeable AI client, conversational limitations, and ethical questions raised by participants. The paper details the simulation's structure, instructional integration, and evaluation, offering a model that can be adapted across graduate statistics curricula to strengthen students' preparation for professional practice. [ABSTRACT FROM AUTHOR]
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Database:	Education Research Complete

Description
Abstract:	This paper describes an AI-infused simulation designed to enhance graduate-level statistical consulting education by bridging theoretical learning with realistic professional practice. Piloted in a master's-level capstone course, the simulation engaged students in consultations with an AI client, requiring them to practice communication, problem framing, methodological justification, and decision-making under authentic conditions. Evidence drawn from interaction transcripts and student reflections showed growth in consulting skills and technical confidence, alongside challenges such as an overly knowledgeable AI client, conversational limitations, and ethical questions raised by participants. The paper details the simulation's structure, instructional integration, and evaluation, offering a model that can be adapted across graduate statistics curricula to strengthen students' preparation for professional practice. [ABSTRACT FROM AUTHOR]
ISSN:	24725986