AMTP Proceedings 2026

Document Type

Conference Proceeding

Publication Date

Spring 2026

Abstract

Artificial intelligence (AI) has rapidly expanded its use in higher education. This study investigates whether students are willing to recommend AI tools for academic purposes, given their growing use and recognized educational benefits. The specific objectives of the study are to: 1) Determine the extent to which students are likely to recommend the use of AI tools to other students for their coursework; 2) Examine whether this likelihood is correlated with perceived benefits and ethical concerns; 3) Identify whether perceived benefits and ethical concerns are significant predictors of students’ likelihood of recommending AI tools; and 4) Assess whether students’ likelihood of recommending AI tools and Net Promoter Score (NPS) differ across demographic characteristics such as gender, class level, and college affiliation.

To address the Study objectives, a survey instrument was developed, comprising newly created questions and items drawn from the relevant literature. Data were collected from college students at a private university who used AI tools in their coursework; non-users were excluded from the survey. The survey link was sent to the entire student body, resulting in 244 usable responses.

Results indicate an overall negative NPS of -37.9 (Promoters – Detractors), indicating that detractors far outnumber promoters. Perceived benefits, especially improvements in academic performance, understanding complex concepts, and problem-solving skills, are positively related to students’ likelihood of recommending AI tools. Conversely, ethical concerns about academic integrity and perceived plagiarism significantly reduce the likelihood of recommendations. Demographic analysis reveals limited variation in recommendation behavior, with some differences by gender and college affiliation, but no significant differences by class level. Overall, the findings suggest that, while students recognize the academic value of AI tools, ethical concerns remain a major barrier to peer recommendation in higher education.

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