Chien-Hong Lee, M. Low, Benjamin Tze Chin Soon, LiMing Lu, H. Lee, Nadya Shaznay Patel
{"title":"Development of a Chatbot to Train Physiotherapy Students in Clinical Questioning and Reasoning","authors":"Chien-Hong Lee, M. Low, Benjamin Tze Chin Soon, LiMing Lu, H. Lee, Nadya Shaznay Patel","doi":"10.1109/TALE54877.2022.00084","DOIUrl":null,"url":null,"abstract":"This paper presents the development of a chatbot to train physiotherapy students in clinical questioning and reasoning. The features in this tool consist of semi-scripted practice conversations between a physiotherapist and virtual patient to determine a clinical diagnosis on a given scenario, automated scoring and feedback on their performance, and instructor tracking of students’ progress. Challenges and lessons learned in developing this chatbot are discussed. Experimental evaluation on whether the use of the chatbot improves students’ self-efficacy in clinical questioning and reasoning is ongoing.","PeriodicalId":369501,"journal":{"name":"2022 IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TALE54877.2022.00084","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper presents the development of a chatbot to train physiotherapy students in clinical questioning and reasoning. The features in this tool consist of semi-scripted practice conversations between a physiotherapist and virtual patient to determine a clinical diagnosis on a given scenario, automated scoring and feedback on their performance, and instructor tracking of students’ progress. Challenges and lessons learned in developing this chatbot are discussed. Experimental evaluation on whether the use of the chatbot improves students’ self-efficacy in clinical questioning and reasoning is ongoing.