Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

레고 마인드스톰 NXT를 활용한 기초설계 교과목에서의 효과적인 공학설계과제 선정방안 연구open accessA Study on Selection of Effective Engineering Design Problem based on LEGO Mindstorm NXT for Basic Design Education

Other Titles
A Study on Selection of Effective Engineering Design Problem based on LEGO Mindstorm NXT for Basic Design Education
Authors
신연순손대근이경호홍성호이강우정진우
Issue Date
Mar-2016
Publisher
한국공학교육학회
Keywords
Engineering Design; Engineering Education; LEGO Mindstorm; Olympic Sports
Citation
공학교육연구, v.19, no.2, pp 60 - 69
Pages
10
Indexed
KCI
Journal Title
공학교육연구
Volume
19
Number
2
Start Page
60
End Page
69
URI
https://scholarworks.dongguk.edu/handle/sw.dongguk/16314
DOI
10.18108/jeer.2016.19.2.60
ISSN
1738-6454
2713-8283
Abstract
This paper deals with the selection method of effective engineering design problem based on LEGO Mindstorm NXT for basic design education. By YouTube case study of various LEGO-based engineering designs for olympic sports, performance criteria have been developed including programming complexity, structural complexity, sensor/actuator complexity and variety of game operation. Programming complexity includes range of programming code length and possible program variety. Structural complexity includes variety of structural elements such as length, shape, weight, and volume to overcome design restrictions. Sensor/actuator complexity includes variety of sensor used and number of possible actuator assemblies. Variety of game operation includes game complexity and required creativity to make LEGO robots. Based on these performance criteria, four representative sports were selected as the candidates for effective engineering design problem. Finally, feasibility and attributes of each candidate were verified by real implementation examples.
Files in This Item
There are no files associated with this item.
Appears in
Collections
College of Advanced Convergence Engineering > Department of Computer Science and Artificial Intelligence > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Jung, Jin Woo photo

Jung, Jin Woo
College of Advanced Convergence Engineering (Department of Computer Science and Artificial Intelligence)
Read more

Altmetrics

Total Views & Downloads

BROWSE