{"title":"Active learning modules for a numerical methods course","authors":"Matthew R Haney, Heather E Dillon, Jakob Kotas","doi":"10.1177/03064190231205368","DOIUrl":null,"url":null,"abstract":"Education research has suggested that students who receive a wider variety of sensory inputs during the learning process will be able to make more connections and more deeply understand course content. To this end, three physical hands-on laboratory learning modules were designed for a computational numerical methods course to help students develop intuition for physical systems, to allow for a comparison of real data against numerical solutions of physics equations, and to increase student engagement. These modules were designed to reinforce specific topics covered in the numerical methods curriculum, including numerical differentiation and numerical solution of ordinary differential equations. Pre- and post-tests showed an increase in student knowledge after module completion. In addition, end-of-term surveys showed that a strong majority of students believed modules helped them visualize and understand key numerical methods concepts, and that most would be interested in learning new material with similar modules in the future.","PeriodicalId":75028,"journal":{"name":"The International journal of mechanical engineering education","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The International journal of mechanical engineering education","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/03064190231205368","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
Education research has suggested that students who receive a wider variety of sensory inputs during the learning process will be able to make more connections and more deeply understand course content. To this end, three physical hands-on laboratory learning modules were designed for a computational numerical methods course to help students develop intuition for physical systems, to allow for a comparison of real data against numerical solutions of physics equations, and to increase student engagement. These modules were designed to reinforce specific topics covered in the numerical methods curriculum, including numerical differentiation and numerical solution of ordinary differential equations. Pre- and post-tests showed an increase in student knowledge after module completion. In addition, end-of-term surveys showed that a strong majority of students believed modules helped them visualize and understand key numerical methods concepts, and that most would be interested in learning new material with similar modules in the future.