WCQR2024_162319: Evaluator as Self-Detector of AI-Generated Assignments in Nursing

Описание: Evaluator as Self-Detector of AI-Generated Assignments in Nursing
Authors: Metersky, K.; Rahman, R.; Chandrasekaran, K.

Abstract:
Introduction: The recent rise in Artificial Intelligence (AI), and specifically the release of Chat Generative Pre-Trained Transformer (ChatGBT) has garnered significant attention among academic circles. ChatGBT is an AI-powered chatbot trained to provide human-like responses to text-based queries. Despite its growing popularity, there is a lack of research on whether educators can distinguish between AI-generated and student-crafted assignments.
Goals and Methods: The goal of this study is to determine whether there are noticeable differences between AI-generated and student-crafted assignments. Four students were selected from a second-year undergraduate nursing theory course in Toronto, Canada. The students submitted two copies of an assignment: one written by them, and one that was AI-generated. The assignments were anonymized by the research assistant and graded by the principal investigator (PI). The PI used a reflective methodology to describe their grading experience.
Results: There were noticeable differences between the AI-generated and student-crafted assignment particularly in the areas of writing style, paragraph structure, references used and the referencing style accuracy. This also led to differences in grades students received on both assignment versions.
Conclusions: The findings from this study provide strategies on how evaluators can become self-detectors of AI-generated assignments versus student-crafted assignments. This study provides suggestions on adjusting assignment guidelines to encourage students to cultivate critical thinking and analysis independent of AI. Ultimately, this study can serve as an important resource for educators navigating the use of AI in nursing education and implications of such use on academic integrity.

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8th World Conference on Qualitative Research (WCQR2024)
23 to 25 January 2024 | São Miguel – Azores (Portugal), Johannesburg (South Africa), and Online
3 Days dedicated to Qualitative Research!
Learn more: https://wcqr.ludomedia.org/

The World Conference on Qualitative Research (WCQR) is an annual event that aims to bring together researchers, academics, and professionals, promoting the sharing and discussion of knowledge, new perspectives, experiences, and innovations in the field of Qualitative Research. Each edition brings together researchers from 30+ countries, world-renowned authors, and research groups sharing their experiences in the field of Qualitative Research, making the WCQR one of the most relevant platforms for discussing and disseminating the best scientific production in the area.

TOPICS:
// Rationale and Paradigms of Qualitative Research
// Systematization of Approaches with Qualitative Studies
// Qualitative and Mixed Methods Research
// Data Analysis Types
// Innovative Processes of Qualitative Data Analysis
// Qualitative Research in Web Context
// Qualitative Analysis with Support of Specific Software

Learn more: https://wcqr.ludomedia.org/
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