Predicting academic success of engineering students in technical drawing from working memory

Tests on spatial aptitude, in particular Visualization, have been shown to be efficient predictors of the academic performance of Technical Drawing stu-dents. It has recently been found that Spatial Working Memory (a construct defined as the ability to perform tasks with a figurative content that require si-multaneous storage and transformation of information) is strongly associated with Visualization. In the present study we analyze the predictive efficiency of a bat-tery of tests that included tests on Visualization, SpatialWorking Memory, Spatial Short-term Memory and Executive Function on a sample of first year engineering students. The results show that Spatial Working Memory (SWM) is the most important predictor of academic success in Technical Drawing. In our view, SWM tests can be useful for detecting as early as possible those students who will require more attention and support in the teaching-learning process.

Computer graphics applied to anatomy: a study of two bio-cad modeling methods on finite element analysis of human edentulous hemi-mandible

Modeling is a step to perform a finite element analysis. Different methods of model construction are reported in literature, as the Bio-CAD modeling. The purpose of this study was to perform a model evaluation and application using two methods of Bio-CAD modeling from human edentulous hemi-mandible on the finite element analysis. From CT scans of dried human skull was reconstructed a stereolithographic model. Two methods of modeling were performed: STL conversion approach (Model 1) associated to STL simplification and reverse engineering approach (Model 2). For finite element analysis was used the action of lateral pterygoid muscle as loading condition to assess total displacement (D), equivalent von-Mises stress (VM) and maximum principal stress (MP). Two models presented differences on the geometry regarding surface number (1834 (model 1); 282 (model 2)). Were observed differences in finite element mesh regarding element number (30428 nodes/16683 elements (model 1); 15801 nodes/8410 elements (model 2). D, VM and MP stress areas presented similar distribution in two models. The values were different regarding maximum and minimum values of D (ranging 0-0.511 mm (model 1) and 0-0.544 mm (model 2), VM stress (6.36E-04-11.4 MPa (model 1) and 2.15E-04-14.7 MPa (model 2) and MP stress (-1.43-9.14 MPa (model 1) and -1.2-11.6 MPa (model 2). From two methods of Bio-CAD modeling, the reverse engineering presented better anatomical representation compared to the STL conversion approach. The models presented differences in the finite element mesh, total displacement and stress distribution.