Analyzing CAD competence with univariate and multivariate learning curve models
(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:
https://lup.lub.lu.se/record/1442311
- author
- Hamade, Ramsey F. ; Jaber, Mohamed Y. and Sikström, Sverker LU
- organization
- publishing date
- 2009
- 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
- 2016-04-01 13:22:05
- date last changed
- 2022-03-21 18:13:02
@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}}, keywords = {{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}}, doi = {{10.1016/j.cie.2008.09.025}}, volume = {{56}}, year = {{2009}}, }