This research project, AI, Anxiety, and motication, will be conducted under the principle investigator Dr. Mocko. It will be conducted through the information systems and operations management department at the University of Florida. Mya has been looking forward to starting this research since last spring, when she took Dr. Mocko's undergraduate business statistics class. She will start aiding in this research in August of of 2027. 

The central research question for this project aims is how much are students using LLM models to help with the workload in an online statistics class, either to provide study guides, create extra practice questions, or other methods to study?

 Specifically, it will answer the following questions: What are the self-regulated learning profiles based on components of motivation and learning strategies? To what extent is the variability of the self-regulated learning profiles explained by AI use, anxiety about taking a statistics course and/or technology integration? What learning strategies are students using with and without AI?

Additionally, this topic will investigate self-regulated learning specifically the habits and behaviors students use to plan, execute, and reflect on their learning when it is not being directly facilitated by an instructor (Shuy et al., 2010). Furthermore, does the anxiety surrounding statistics classes, particularly online statistics classes, contribute to this usage of AI?

A survey will be distributed to students in online statistics classes at the University of Florida (specifically QMB 3250,Statistics for Business Decisions, and STA 2023, Introduction to Statistics). The survey will include the Motivated Strategies for Learning Questionnaire by Pintrich, SASO (Lindsay et al., 2024). The first section of the survey asks about the student’s motivation while the second section investigates student learning. The student learning section ues cognitive, metacognitive, and resource management scales. Due to the dual- nature of this survey, it has been proven to show detailed information about the learning strategies students are using, contributing to the goal of understanding their leaning strategies, and how they are different when pertaining to LLM models. Mya will contribute to this research by gathering data for the literature review, specifically on Artificial intelligence in Education, and motivation in statistics education. Mya will also help determine coding scheme to analyze results, as well as perform K-means clustering and conducting MANOVA.

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This example shows how the motivated Strategies for Learning Questionnaire may be presented to students:

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This question is important because it bridges the gap between instructors and students when it comes to using LLMS to study. While many higher education instructors are apprehensive about their students’ use of AI and LLMs, there is very little understanding within professionals in education surrounding the ways in which their students are using AI. Instructors (specifically statistics instructors) will be able to modify instructional materials to better address students’ needs and wants in their self-regulated learning.

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This video explains what statitical anxiety, a central part of this research, is and how it affects students: 

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