Teaching Advanced Topics in Numerical Engineering Using Project-Based Learning

被引:1
作者
Apostolatos, Andreas [1 ]
Gross, Sebastian [1 ]
机构
[1] MathWorks, Acad Grp, Natick, MA 01760 USA
来源
2024 IEEE GLOBAL ENGINEERING EDUCATION CONFERENCE, EDUCON 2024 | 2024年
关键词
project-based learning; hybrid teaching; interactive notebooks; auto-graded assignments; finite element methods; computer-aided design; isogeometric analysis; computational fluid dynamics; physics-informed neural networks; LOCKING; NURBS;
D O I
10.1109/EDUCON60312.2024.10578612
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This case study discusses the use of computational platforms and resources for the organization and delivery of lectures in Numerical Engineering using Project-Based Learning (PBL). Additionally, this paper introduces elements of Flipped Classroom. The goal is to demonstrate how modern teaching techniques can enhance the quality of education for students and provide lecturers with an efficient method to set and evaluate Learning Objectives using Bloom's Taxonomy. The evaluation of Learning Outcomes, with a focus on Formative Assessment, is herein extensively discussed. The methods and results presented herein are based on the preparation and delivery of the master-level courses Advanced Finite Element Methods (AFEM) and Advanced Finite Element Methods Lab (AFEM-Lab) that took place in Summer Semester 2023 and Winter Semester 2023-24, respectively, at the Technical University of Munich (TUM). The results presented herein clearly show the effectiveness of using computational platforms and formative assessment both for PBL and Flipped Classroom in the context of advanced academic teaching.
引用
收藏
页数:10
相关论文
共 36 条
[1]  
Acheson DavidJ., 1991, Elementary fluid dynamics
[2]  
Anderson L., 2001, TAXONOMY LEARNING TE
[3]  
Apostolatos A., 2022, 2022 IEEE GERM ED C, P1
[4]  
Hussin AA, 2018, International Journal of Education and Literacy Studies, V6, P92, DOI [10.7575/aiac.ijels.v.6n.3p.92, 10.7575/aiac.ijels.v.6n.3p.92, DOI 10.7575/AIAC.IJELS.V.6N.3P.92, 10.7575/aiac.ijels.v.6n.3p.92/]
[5]  
Bischoff M., 2004, ENCY COMPUTATIONAL M
[6]  
Bishop JL, 2013, ASEE ANNU CONF EXPO
[7]   A unified approach for shear-locking-free triangular and rectangular shell finite elements [J].
Bletzinger, KU ;
Bischoff, M ;
Ramm, E .
COMPUTERS & STRUCTURES, 2000, 75 (03) :321-334
[8]   Large-Scale Machine Learning with Stochastic Gradient Descent [J].
Bottou, Leon .
COMPSTAT'2010: 19TH INTERNATIONAL CONFERENCE ON COMPUTATIONAL STATISTICS, 2010, :177-186
[9]   On the Assumed Natural Strain method to alleviate locking in solid-shell NURBS-based finite elements [J].
Caseiro, J. F. ;
Valente, R. A. F. ;
Reali, A. ;
Kiendl, J. ;
Auricchio, F. ;
Alves de Sousa, R. J. .
COMPUTATIONAL MECHANICS, 2014, 53 (06) :1341-1353
[10]  
Codina R., 2018, Encyclopedia of computational mechanics, Vsecond, P1