Xiang Wan

Wan G, Grassi M, Golden T, Barnes T, Kahveci M, Wan X, Colacchio B (2025)

This **participatory action research** (PAR) study, conducted at a Midwestern U.S. university, aimed to bridge the gap between **generative artificial intelligence (GenAI) tools and academic integrity**. Using mixed methods, researchers analyzed participants’ **perceptions and strategies** for using GenAI tools while upholding academic integrity. The study highlighted the institution’s strengths, weaknesses, opportunities, and challenges in grappling with the issue, pointing to the need for the **critical use of GenAI tools** and clear guidelines. The findings contribute to the field by providing strategies to **empower educators and learners** in navigating the ethical landscape of GenAI in education.

Source: J. Sci. Pub., 56(2): 320-376.

Wan G, Kahveci M, Colacchio B, Grassi M, Golden T, Wan X (2024)

This proposal investigates the impact of **generative AI tools** (such as ChatGPT) on **academic integrity** in a U.S. college setting. The authors adopt a **participatory action research** approach, involving various university stakeholders in data collection and analysis. The study aims to explore the benefits and challenges of using AI tools for teaching and learning, and to suggest ways to promote the ethical and appropriate use of information. It also examines current academic integrity policies and practices in the context of AI development. The proposal is informed by a critical media/information literacy perspective and contributes to the literature on academic integrity in the age of AI.

Source: Paper presented at PUPP International Summit. Gatineau-Ottawa, Canada. May 21 - 24, 2024.