Piloting Free AI Tools for Open Student Course Applications

Objective: The purpose of this mixed-methods, quasi-experimental pilot study was to analyze practice outcomes after incorporating the university sponsored artificial intelligence (AI) adaptive learning platforms and assistants with the major course project of the student nurse educator development course. The study’s aim was to implement AI tools without increasing student perceptions of course work stress. Methodology: Utilizing a convenience sample of 10 graduate students from a mid-western rural, public university following structured implementation of normally assigned coursework, process modifications for implementing AI tools were shared. Surveys analyzed student perceptions of stress (specifically linked to new technology implementation) alongside the perceived beneficial outcomes of using AI in course testing development. The specific task scribed was to create NGN-style questions with real-world clinical implications using AI. Findings: Preliminary Paired T-Test study findings using aggregated Likert-type survey data analyzed via SPSS © and open-ended comments using Thematic Analysis via Dedoose©. Findings demonstrated low-to-moderate student stress rates using innovative formats of AI and that AI-powered adaptive learning platforms/assistants are useful tools in test development for many courses including simulation. Conclusion: This pilot project analyzed applications of AI course integration in a virtual classroom. Specifically, students were able to use AI to compose NGN-style questions linked to health care environments that incorporated uncertainty, ambiguity and complexity. Further project analysis is pending