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Analyzing CAD competence with univariate and multivariate learning curve models

Hamade, Ramsey F.; Jaber, Mohamed Y. and Sikström, Sverker LU (2009) In Computers & Industrial Engineering 56(4). p.1510-1518
Abstract
Understanding how learning occurs, and what improves or impedes the learning process is of importance to academicians and practitioners; however, empirical research on validating learning curves is sparse. This paper contributes to this line of research by collecting and analyzing CAD (computer-aided design) procedural and cognitive performance data for novice trainees during 16-weeks of training. The declarative performance is measured by time, and the procedural performance by the number of features used to construct a design part. These data were analyzed using declarative or procedural performance separately as predictors (univariate), or a combination of declarative or procedural predictors (multivariate). Furthermore, a method to... (More)
Understanding how learning occurs, and what improves or impedes the learning process is of importance to academicians and practitioners; however, empirical research on validating learning curves is sparse. This paper contributes to this line of research by collecting and analyzing CAD (computer-aided design) procedural and cognitive performance data for novice trainees during 16-weeks of training. The declarative performance is measured by time, and the procedural performance by the number of features used to construct a design part. These data were analyzed using declarative or procedural performance separately as predictors (univariate), or a combination of declarative or procedural predictors (multivariate). Furthermore, a method to separate the declarative and procedural components from learning curve data is suggested. (C) 2008 Elsevier Ltd. All rights reserved. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Learning curves, Procedural knowledge, CAD, Declarative knowledge, Empirical study, training
in
Computers & Industrial Engineering
volume
56
issue
4
pages
1510 - 1518
publisher
Elsevier
external identifiers
  • wos:000266754900037
  • scopus:67349149954
ISSN
0360-8352
DOI
10.1016/j.cie.2008.09.025
language
English
LU publication?
yes
id
0ebe064d-80cf-49e9-839d-3e0a3e9f7f83 (old id 1442311)
date added to LUP
2009-07-27 11:05:01
date last changed
2017-08-06 03:58:38
@article{0ebe064d-80cf-49e9-839d-3e0a3e9f7f83,
  abstract     = {Understanding how learning occurs, and what improves or impedes the learning process is of importance to academicians and practitioners; however, empirical research on validating learning curves is sparse. This paper contributes to this line of research by collecting and analyzing CAD (computer-aided design) procedural and cognitive performance data for novice trainees during 16-weeks of training. The declarative performance is measured by time, and the procedural performance by the number of features used to construct a design part. These data were analyzed using declarative or procedural performance separately as predictors (univariate), or a combination of declarative or procedural predictors (multivariate). Furthermore, a method to separate the declarative and procedural components from learning curve data is suggested. (C) 2008 Elsevier Ltd. All rights reserved.},
  author       = {Hamade, Ramsey F. and Jaber, Mohamed Y. and Sikström, Sverker},
  issn         = {0360-8352},
  keyword      = {Learning curves,Procedural knowledge,CAD,Declarative knowledge,Empirical study,training},
  language     = {eng},
  number       = {4},
  pages        = {1510--1518},
  publisher    = {Elsevier},
  series       = {Computers & Industrial Engineering},
  title        = {Analyzing CAD competence with univariate and multivariate learning curve models},
  url          = {http://dx.doi.org/10.1016/j.cie.2008.09.025},
  volume       = {56},
  year         = {2009},
}