1. Comparing new tools of artificial intelligence to the authentic intelligence of our global health students
- Author
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Shilpa R. Thandla, Grace Q. Armstrong, Adil Menon, Aashna Shah, David L. Gueye, Clara Harb, Estefania Hernandez, Yasaswini Iyer, Abigail R. Hotchner, Riddhi Modi, Anusha Mudigonda, Maria A. Prokos, Tharun M. Rao, Olivia R. Thomas, Camilo A. Beltran, Taylor Guerrieri, Sydney LeBlanc, Skanda Moorthy, Sara G. Yacoub, Jacob E. Gardner, Benjamin M. Greenberg, Alyssa Hubal, Yuliana P. Lapina, Jacqueline Moran, Joseph P. O’Brien, Anna C. Winnicki, Christina Yoka, Junwei Zhang, and Peter A. Zimmerman
- Subjects
Computer applications to medicine. Medical informatics ,R858-859.7 ,Analysis ,QA299.6-433 - Abstract
Abstract Introduction The transformative feature of Artificial Intelligence (AI) is the massive capacity for interpreting and transforming unstructured data into a coherent and meaningful context. In general, the potential that AI will alter traditional approaches to student research and its evaluation appears to be significant. With regard to research in global health, it is important for students and research experts to assess strengths and limitations of GenAI within this space. Thus, the goal of our research was to evaluate the information literacy of GenAI compared to expectations that graduate students meet in writing research papers. Methods After completing the course, Fundamentals of Global Health (INTH 401) at Case Western Reserve University (CWRU), Graduate students who successfully completed their required research paper were recruited to compare their original papers with a paper they generated by ChatGPT-4o using the original assignment prompt. Students also completed a Google Forms survey to evaluate different sections of the AI-generated paper (e.g., Adherence to Introduction guidelines, Presentation of three perspectives, Conclusion) and their original papers and their overall satisfaction with the AI work. The original student to ChatGPT-4o comparison also enabled evaluation of narrative elements and references. Results Of the 54 students who completed the required research paper, 28 (51.8%) agreed to collaborate in the comparison project. A summary of the survey responses suggested that students evaluated the AI-generated paper as inferior or similar to their own paper (overall satisfaction average = 2.39 (1.61–3.17); Likert scale: 1 to 5 with lower scores indicating inferiority). Evaluating the average individual student responses for 5 Likert item queries showed that 17 scores were
- Published
- 2024
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