Improving student learning using finite element learning modules: An update in research findings

Document Type

Conference Presentation

Conference Title

Annual Meeting of the American Society of Engineering Education

Organization

American Society of Engineering Education

Location

San Antonio, TX

Date of Presentation

6-1-2012

Abstract

The landscape of contemporary engineering education is ever changing, adapting and evolving. We are indeed living in interesting and exciting times. At the focal point of these times is the concept of active learning methods. This poster session and paper describes a novel approach to improving student learning using active learning finite element learning modules. This poster session summarizes the improved student learning over the past six years at nine engineering schools and colleges. These active learning finite element modules were originally developed using MSC Nastran, followed by development efforts in SolidWorks® Simulation, ANSOFT, ANSYS©, and other commercial FEA software packages. Researchers, with National Science Foundation support, have created over twenty-eight active finite element learning modules which continue to improve student understanding of difficult engineering concepts across engineering disciplines. Finite element theory and application has often been the focus of graduate-level courses in engineering programs; however, industry needs B.S. engineering graduates to have skills in applying this essential analysis and design technique. We have used the Kolb Learning Cycle as a foundation element to improve student learning of difficult engineering concepts, along with gaining essential knowledge of finite element analysis and design content knowledge. We discuss the implementation, improved student knowledge, impact, and assessment across demographics, learning styles and personality preference types. These learning modules are incorporated into undergraduate machine design, mechanical vibrations, heat transfer, bioelectrical engineering, electromagnetic field analysis, structural fatigue analysis, computational fluid dynamics, rocket design, chip formation during manufacturing, and large scale deformation in machining. Key assessment results show improvements in student knowledge of difficult engineering concepts measured with performance on pre- and postlearning module quizzes. © 2012 American Society for Engineering Education.

Comments

© 2012 American Society for Engineering Education

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