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Approach for developing coordinated rubrics to convey quality criteria in MCAD training
Affiliation:1. Institute of New Imaging Technology, Universitat Jaume I, Castellón, Spain;2. I3BH, Universitat Politècnica de València, Valencia, Spain;3. Texas A&M University, Zachry Department of Civil Engineering, USA;4. Dpto. Ingeniería Mecánica y Construcción, Universitat Jaume I, Castellón, Spain;1. Dipartimento di Automatica e Informatica, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy;2. Dipartimento di Ingegneria Gestionale e della Produzione, Corso Duca degli Abruzzi 24, 10129 Torino, Italy;1. College of Basic Science, Tianjin Agricultural University, Tianjin 300384, China;2. School of Business, Ningbo University, Ningbo 315211, China;3. College of Computer and Information, Zhejiang Wanli University, Ningbo 315100, China;4. Lithuanian Institute of Agrarian Economics, V. Kudirkos Str. 18/2, LT-03105 Vilnius, Lithuania;1. Baidu Inc, China;2. Hong Kong University of Science and Technology, Hong Kong;3. London School of Economics and Political Science, UK
Abstract:This paper describes an approach to convey quality-oriented strategies to CAD trainees by embedding quality criteria into rubrics so as to force CAD trainees to understand them early in their instruction. To this end, the paper analyzes how CAD quality criteria can be organized around quality dimensions and embedded into rubrics in order to enforce quality modeling during the CAD training of novice product designers. Hence, the ambit of this study is training with history-based parametric feature-based MCAD systems, although the general conclusions are believed to be adaptable to other CAD training scenarios. Furthermore, it introduces an approach based on progressive refinement, which results in an assertions map that indicates quality dimensions vs. sequence of tasks for CAD models. The map illustrates how the expand–contract strategy adapts the rubrics to CAD trainee progress and assists them in comprehending the different dimensions of the rubrics. The paper also highlights lessons learned on the suitability of using separate rubrics for different tasks, the need of accurately timing the expand–contract process, and on the convenience of supporting rubrics with suitable teaching, which must convey good practices and evaluation tools through rubrics. The experiments describe the different lessons learned and illustrate the suggested process for replicating our approach for further developing rubrics adapted to other scenarios.
Keywords:CAD model  Quality  Design intent  Rubric
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