Shanna K. O'Connor , Erin E. Miller , Alyssa R. Zweifel , Danielle M. Schievelbein , Anjali R. Parmar , James W. Amell
{"title":"使用人工智能处理工具来评估定性数据:学生研究人员与教师研究人员的比较","authors":"Shanna K. O'Connor , Erin E. Miller , Alyssa R. Zweifel , Danielle M. Schievelbein , Anjali R. Parmar , James W. Amell","doi":"10.1016/j.cptl.2025.102418","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><div>Artificial intelligence (AI) has emerged as a promising tool to support qualitative data analysis, yet its role in faculty-led studies that incorporate student researchers remains under investigation. This study examined differences in inductive thematic analysis generated by student and faculty researchers using AI compared to traditional faculty-led coding.</div></div><div><h3>Methods</h3><div>Three qualitative datasets were analyzed using OpenAI's ChatGPT by faculty and student researchers.</div></div><div><h3>Results</h3><div>Findings showed AI-assisted analyses identified most themes accurately, though faculty-generated AI results aligned more closely with expert-reviewed themes than student-generated AI results.</div></div><div><h3>Conclusions</h3><div>AI may be a valuable tool to enhance efficiency particularly in initial evaluation of qualitative data.</div></div>","PeriodicalId":47501,"journal":{"name":"Currents in Pharmacy Teaching and Learning","volume":"17 10","pages":"Article 102418"},"PeriodicalIF":1.3000,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Use of artificial intelligence processing tools to evaluate qualitative data: Student researchers compared to faculty researchers\",\"authors\":\"Shanna K. O'Connor , Erin E. Miller , Alyssa R. Zweifel , Danielle M. Schievelbein , Anjali R. Parmar , James W. Amell\",\"doi\":\"10.1016/j.cptl.2025.102418\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><div>Artificial intelligence (AI) has emerged as a promising tool to support qualitative data analysis, yet its role in faculty-led studies that incorporate student researchers remains under investigation. This study examined differences in inductive thematic analysis generated by student and faculty researchers using AI compared to traditional faculty-led coding.</div></div><div><h3>Methods</h3><div>Three qualitative datasets were analyzed using OpenAI's ChatGPT by faculty and student researchers.</div></div><div><h3>Results</h3><div>Findings showed AI-assisted analyses identified most themes accurately, though faculty-generated AI results aligned more closely with expert-reviewed themes than student-generated AI results.</div></div><div><h3>Conclusions</h3><div>AI may be a valuable tool to enhance efficiency particularly in initial evaluation of qualitative data.</div></div>\",\"PeriodicalId\":47501,\"journal\":{\"name\":\"Currents in Pharmacy Teaching and Learning\",\"volume\":\"17 10\",\"pages\":\"Article 102418\"},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2025-06-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Currents in Pharmacy Teaching and Learning\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S187712972500139X\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"EDUCATION, SCIENTIFIC DISCIPLINES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Currents in Pharmacy Teaching and Learning","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S187712972500139X","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"EDUCATION, SCIENTIFIC DISCIPLINES","Score":null,"Total":0}
Use of artificial intelligence processing tools to evaluate qualitative data: Student researchers compared to faculty researchers
Background
Artificial intelligence (AI) has emerged as a promising tool to support qualitative data analysis, yet its role in faculty-led studies that incorporate student researchers remains under investigation. This study examined differences in inductive thematic analysis generated by student and faculty researchers using AI compared to traditional faculty-led coding.
Methods
Three qualitative datasets were analyzed using OpenAI's ChatGPT by faculty and student researchers.
Results
Findings showed AI-assisted analyses identified most themes accurately, though faculty-generated AI results aligned more closely with expert-reviewed themes than student-generated AI results.
Conclusions
AI may be a valuable tool to enhance efficiency particularly in initial evaluation of qualitative data.