{"title":"Implementing GRATL and artificial intelligence in experiential learning of obesity physiology and etiology.","authors":"Zhiyong Cheng, Jinying Yang, Karla P Shelnutt","doi":"10.1152/advan.00025.2025","DOIUrl":null,"url":null,"abstract":"<p><p>Learning and dissemination of obesity physiology and etiology knowledge are essential to prevention and treatment of this chronic disease through concerted efforts from both professionals and the general public. In this article, we describe an innovative Gain in Research Ability Test per Literature (GRATL) framework that integrates artificial intelligence (AI) into experiential learning (EL) of obesity physiology and etiology through community outreach projects. The GRATL framework sets seven areas of research competencies, i.e., Identify, Question, Plan, Conduct, Analyze, Conclude, and Communicate, as the anticipated learning outcomes (ALOs), and it navigates the design and implementation of research and learning activities. The quantitative matrix of GRATL navigated AI application through rigorous verification and assessed the growth of students' research ability. Our data suggest that the GRATL framework enhanced students' discipline knowledge, research ability, and career competency skills including communication, problem-solving, critical thinking, knowledge construction with AI assistance, teamwork, leadership, and self-management. In addition, the students helped the communities gain a better understanding of obesity and appreciated the roles of lifestyle behaviors in chronic disease. As the seven areas of research competencies are valued and observed across disciplines, the GRATL framework coupled with AI-assisted EL may be adjustable and scalable in teaching and learning of other subjects.<b>NEW & NOTEWORTHY</b> Obesity is a global public health issue. Concerted efforts are needed from both professionals and the public to prevent and treat the chronic disease. Here we describe a GRATL framework that engages college students and the public to learn obesity physiology and etiology through AI-assisted experiential learning and citizen science. Implementation of the GRATL framework enhances students' discipline knowledge, research ability, and career competency skills, and it also helps the public gain a better understanding of obesity.</p>","PeriodicalId":50852,"journal":{"name":"Advances in Physiology Education","volume":" ","pages":"871-878"},"PeriodicalIF":1.7000,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Physiology Education","FirstCategoryId":"95","ListUrlMain":"https://doi.org/10.1152/advan.00025.2025","RegionNum":4,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/7/25 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"EDUCATION, SCIENTIFIC DISCIPLINES","Score":null,"Total":0}
引用次数: 0
Abstract
Learning and dissemination of obesity physiology and etiology knowledge are essential to prevention and treatment of this chronic disease through concerted efforts from both professionals and the general public. In this article, we describe an innovative Gain in Research Ability Test per Literature (GRATL) framework that integrates artificial intelligence (AI) into experiential learning (EL) of obesity physiology and etiology through community outreach projects. The GRATL framework sets seven areas of research competencies, i.e., Identify, Question, Plan, Conduct, Analyze, Conclude, and Communicate, as the anticipated learning outcomes (ALOs), and it navigates the design and implementation of research and learning activities. The quantitative matrix of GRATL navigated AI application through rigorous verification and assessed the growth of students' research ability. Our data suggest that the GRATL framework enhanced students' discipline knowledge, research ability, and career competency skills including communication, problem-solving, critical thinking, knowledge construction with AI assistance, teamwork, leadership, and self-management. In addition, the students helped the communities gain a better understanding of obesity and appreciated the roles of lifestyle behaviors in chronic disease. As the seven areas of research competencies are valued and observed across disciplines, the GRATL framework coupled with AI-assisted EL may be adjustable and scalable in teaching and learning of other subjects.NEW & NOTEWORTHY Obesity is a global public health issue. Concerted efforts are needed from both professionals and the public to prevent and treat the chronic disease. Here we describe a GRATL framework that engages college students and the public to learn obesity physiology and etiology through AI-assisted experiential learning and citizen science. Implementation of the GRATL framework enhances students' discipline knowledge, research ability, and career competency skills, and it also helps the public gain a better understanding of obesity.
期刊介绍:
Advances in Physiology Education promotes and disseminates educational scholarship in order to enhance teaching and learning of physiology, neuroscience and pathophysiology. The journal publishes peer-reviewed descriptions of innovations that improve teaching in the classroom and laboratory, essays on education, and review articles based on our current understanding of physiological mechanisms. Submissions that evaluate new technologies for teaching and research, and educational pedagogy, are especially welcome. The audience for the journal includes educators at all levels: K–12, undergraduate, graduate, and professional programs.