The Relationship Between AI and Coursework

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Abstract

This marketing research project explores the role and impact of AI within students' coursework and examines how concepts learned from using AI apply to the efficiency at which students complete assignments. It explores how AI use affects GPA and vice versa, and how these factors tie into demographics.

Primary data was collected through a survey (382 responses, 285 fully completed) and analyzed in SPSS using Pearson correlation, paired-samples t-tests, independent-samples t-tests, and multiple regression. The findings indicate that students generally view AI as beneficial, especially for coursework, and recommend GSU put policies in place to encourage responsible experimentation with AI while teaching students the line between assistance and academic dishonesty.

Research Objectives

1. Examine students' awareness, usage, and attitudes towards AI in academic settings.
2. Assess how AI use varies across student demographics.
3. Explore how students' attitudes towards AI relate to their broader academic engagement and satisfaction.
4. Provide insights for professors and administration on how AI is affecting undergraduate education.
5. Discuss next steps to ensure students are educated on when AI use is appropriate.

Method

The study began with 40 qualitative interviews that informed a 52-question paper survey (attitude items on a seven-point Likert scale) distributed via convenience sampling to undergraduate business students at Georgia State on October 8, 2025. 382 surveys were collected; responses were coded and analyzed in SPSS.

Key Findings

Students who find AI's explanations clearer than their textbooks are also more likely to use it regularly for coursework, and peer use and professor encouragement both correlate with higher AI adoption. Students clearly distinguish between AI as a time-saving tool (strong agreement) and AI as a way to avoid learning the material (much more ambivalent), and students with lower GPAs reported significantly more last-minute assignment behavior than higher-GPA students.

A multiple regression predicting AI use for assignments found professor encouragement, proofreading support, and peer influence as the strongest positive predictors, while ethical objections and environmental-impact concerns were associated with lower use, explaining 53.4% of the variance. A second regression found that belief in AI's educational value was the strongest driver of support for professors teaching ethical AI use, and that concerns about unfair advantage over classmates were not significant, suggesting students see AI as a legitimate tool rather than a shortcut.

Managerial Recommendations

Georgia State should consider introductory AI literacy coursework interspersed through required core classes (rather than confined to one Freshman Experience course), faculty development workshops on integrating AI into instruction, and clear campus-wide AI usage guidelines, so that student behavior and faculty expectations around AI stay aligned as it becomes more widespread.

Limitations

Data collection happened in a single convenience-sampling window (one day, on-campus), around 17% of respondents came from outside the Robinson College of Business, and participation was voluntary with only a small token of appreciation, all of which limit how representative the sample is of the broader student population.