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written by Florin Bocaneala and Lei Bao
In this paper we test the versatility of the neural network approach to modeling the dynamics of student learning. We choose a problem from an introductory physics class and we construct a neural network model for it. Based on this simulation, we argue for the future use of neural network models in Physics Education Research and what this approach can teach us about how physics learning takes place
Physics Education Research Conference 2003
Part of the PER Conference series
Madison, WI: August 6-7, 2003
Volume 720, Pages 117-120
Subjects Levels Resource Types
Education - Basic Research
- Cognition
General Physics
- Physics Education Research
- Lower Undergraduate
- Reference Material
= Research study
PER-Central Type Intended Users Ratings
- PER Literature
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- Educators
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text/html
application/pdf
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Mirror:
http://dx.doi.org/10.1063/1.1807268
Access Rights:
Available by subscription
Restriction:
© 2003 American Institute of Physics
Additional information is available.
DOI:
10.1063/1.1807268
PACS:
01.40.Fk
Keywords:
PERC 2003, electromagnetism, modelling, neural nets, student experiments, teaching
Record Creator:
Metadata instance created June 13, 2005 by Lyle Barbato
Record Updated:
July 7, 2013 by Lyle Barbato
Last Update
when Cataloged:
September 9, 2004
ComPADRE is beta testing Citation Styles!

Record Link
AIP Format
F. Bocaneala and L. Bao, presented at the Physics Education Research Conference 2003, Madison, WI, 2003, WWW Document, (http://www.compadre.org/Repository/document/ServeFile.cfm?ID=2379&DocID=3427).
AJP/PRST-PER
F. Bocaneala and L. Bao, A computational model for physics learning, presented at the Physics Education Research Conference 2003, Madison, WI, 2003, <http://www.compadre.org/Repository/document/ServeFile.cfm?ID=2379&DocID=3427>.
APA Format
Bocaneala, F., & Bao, L. (2003, August 6-7). A computational model for physics learning. Paper presented at Physics Education Research Conference 2003, Madison, WI. Retrieved October 2, 2014, from http://www.compadre.org/Repository/document/ServeFile.cfm?ID=2379&DocID=3427
Chicago Format
Bocaneala, Florin, and Lei Bao. "A computational model for physics learning." Paper presented at the Physics Education Research Conference 2003, Madison, WI, August 6-7, 2003. http://www.compadre.org/Repository/document/ServeFile.cfm?ID=2379&DocID=3427 (accessed 2 October 2014).
MLA Format
Bocaneala, Florin, and Lei Bao. "A computational model for physics learning." Physics Education Research Conference 2003. Madison, WI: 2003. 117-120 Vol. 720 of PER Conference. 2 Oct. 2014 <http://www.compadre.org/Repository/document/ServeFile.cfm?ID=2379&DocID=3427>.
BibTeX Export Format
@inproceedings{ Author = "Florin Bocaneala and Lei Bao", Title = {A computational model for physics learning}, BookTitle = {Physics Education Research Conference 2003}, Pages = {117-120}, Address = {Madison, WI}, Series = {PER Conference}, Volume = {720}, Month = {August 6-7}, Year = {2003} }
Refer Export Format

%A Florin Bocaneala
%A Lei Bao
%T A computational model for physics learning
%S PER Conference
%V 720
%D August 6-7 2003
%P 117-120
%C Madison, WI
%U http://www.compadre.org/Repository/document/ServeFile.cfm?ID=2379&DocID=3427
%O Physics Education Research Conference 2003
%O August 6-7
%O text/html

EndNote Export Format

%0 Conference Proceedings
%A Bocaneala, Florin
%A Bao, Lei
%D August 6-7 2003
%T A computational model for physics learning
%B Physics Education Research Conference 2003
%C Madison, WI
%V 720
%P 117-120
%S PER Conference
%8 August 6-7
%U http://www.compadre.org/Repository/document/ServeFile.cfm?ID=2379&DocID=3427


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The AIP Style presented is based on information from the AIP Style Manual.

The AJP/PRST-PER presented is based on the AIP Style with the addition of journal article titles and conference proceeding article titles.

The APA Style presented is based on information from APA Style.org: Electronic References.

The Chicago Style presented is based on information from Examples of Chicago-Style Documentation.

The MLA Style presented is based on information from the MLA FAQ.

A computational model for physics learning:


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