DocumentCode
2870955
Title
Enhanced Understand of Biological Systems Using Structure-Behavior-Function Models
Author
Helms, Michael ; Vattam, Swaroop ; Goel, Ashok K. ; Yen, Jeannette
Author_Institution
Design & Intell. Lab., Georgia Inst. of Technol., Atlanta, GA, USA
fYear
2011
fDate
6-8 July 2011
Firstpage
239
Lastpage
243
Abstract
An important issue in teaching interdisciplinary biologically inspired design is the external representations we use to foster understanding of biological systems. In this study we explore if functional models of biological systems, and in particular Structure-Behavior-Function (SBF) models, enable humans to better understand complex biological systems. The study compares the use of SBF models in answering questions about biological systems versus the use of textual, tabular and graphical representations. The results indicate that while no one representation is best for answering all types of questions, SBF models enable more accurate answers to questions entailing abstract and complex inferences.
Keywords
behavioural sciences computing; biology computing; biomedical education; computer aided instruction; educational courses; inference mechanisms; psychology; question answering (information retrieval); teaching; SBF models; answering questions; complex biological systems; complex inferences; graphical representations; interdisciplinary biologically inspired design; structure behavior function models; tabular representations; teaching; textual representations; Artificial intelligence; Biological system modeling; Biological systems; Computational modeling; Mathematical model; Surface contamination; biological systems; functional models; learning; question answering; understanding;
fLanguage
English
Publisher
ieee
Conference_Titel
Advanced Learning Technologies (ICALT), 2011 11th IEEE International Conference on
Conference_Location
Athens, GA
ISSN
2161-3761
Print_ISBN
978-1-61284-209-7
Electronic_ISBN
2161-3761
Type
conf
DOI
10.1109/ICALT.2011.76
Filename
5992333
Link To Document