version of the PSVT:R administeredto first-year engineering students at a mid-sized, public university in the United States. We usean exploratory factor analysis (EFA) to determine the number of latent variables being measuredby the instrument in our data. We determine the number of latent variables to be one, with goodreliability, which is consistent with the paper-based instrument. In future work, we plan to use aconfirmatory factor analysis (CFA) to show evidence of validity of the computer-based PSVT:R.Introduction It is well-established in literature that spatial skills are strongly correlated with academicsuccess in STEM. In particular mental rotation (MR) has been shown to correlate with coursegrades and retention in engineers [1
skills [2]. Technical knowledge is the most crucialcharacteristic for a competent civil and construction engineer, followed by decision-makingskills, knowledge of teamwork, planning and scheduling abilities, and leadership skills [3].According to research, the most commonly identified competency categories for constructionmanagers are technical knowledge, leadership skills, effective communication, management andorganization, planning abilities, teamwork, and a strong sense of determination [2]. Thesecompetencies are critical for ensuring successful construction projects delivery. However,despite ongoing criticism, engineering programs in undergraduate studies continue to prioritizetechnical skills over non-technical skills, resulting in
590 engineering degree program studentsenrolled in an engineering graphics course, whose distribution among grade levels is inTable 1. Data for the sample arrives from the existing IUSE project and the universityOffice of Institutional Research and Planning (OIRP). Table 1 Distribution of Students by Grade Level (n=590) Grade Level f % Grade Level f % Freshman 132 22.37 Junior 111 18.81 Sophomore 297 50.34 Senior 50 8.47 Table 2 describes the dependent variables that will undergo a descriptiveanalysis and survival analysis to identify rates and potential patterns related to retentionand
manufacture. Theproject work attempts to bridge the gap between the virtual skill set and understandingengineering requirements while at the same time making the class more engaging and fun.Desired Learning OutcomesWith the ability to have students work in the Baxter Innovation Lab, the CLC EngineeringGraphics lesson plans were re-evaluated with the following desired learning outcomes in mind: • Analyze the engineering functions of existing products. • Create functional description of the design intent, including design objectives and constraints. • Display competency and safe practices using essential shop equipment • Apply sketching, 3D solid modeling, and CAD drawing skills to convey design ideas effectively
in solving mental rotation problems grew significantly. This papershared detailed results, implications, as well as curricular plans. 21. Introduction1.1 BackgroundSpatial thinking refers to a set of mental skills that allow us to understand the position of objectsand how the objects relate to each other [5] [7]. These skills are required for STEM-relatedcareers, ranging from engineers visualizing how components are assembled, how a circuitdiagram can be represented on a circuit board, scientists visualizing molecular structures, andcomputer programmers visualizing the structure of the code they are writing. Studies from thepast six decades
. However, learning experiences and external factors, such as background, race, andgender, also affect self-efficacy. The SCCT has models including the interest, choice, and self-management models,and the “the self-management model emphasizes the factors that lead people to enact behaviors that aid their owneducational and occupational progress (e.g., planning, information-gathering, deciding, goal-setting, job-finding,self-asserting, preparing for change, negotiating transitions) beyond field or job selection alone” [9, pp. 558].General self-efficacy refers to our beliefs about our ability to attain positive outcomes and meet our goals.According to psychologist Albert Bandura [10] the first proponent of the concept, self-efficacy is the product of
moreaccurately assess whether the online sketching questions are indeed measuring what we intendthem to measure.As noted previously, the first five weeks of the semester in EGT 120 are devoted solely to handsketching, before introducing CAD work, and the sketching activities continue throughout thesemester. Considerable time is spent in class providing formative and summative feedback withthese conventional sketching practices. Because of the importance of sketching in developingvisualization abilities, even with the success of the format change on exams, there are no plans toreplace current lecture and lab sketching activities with items and exercises similar to those beingused on exams.References[1] N.L. Veurink, A.J. Hamlin, J. C. M. Kampe, S. A
. Plans are for the instrument to besystematically and regularly administered throughout the course of study of MET students.Currently, PSVT:R results are solely used as diagnostic instruments within the department.Having a publication validating use of the PSVT:R can potentially help use of instrument beyondthe department and college of engineering.In addition to its traditional role in assessing spatial aptitude, this research explores potentialcorrelations between improved spatial skills and broader skill sets, including enhanced motorskills, tactile abilities, and the capacity to perform mechanical tasks. Aspects often emphasized byindustry representatives, these qualities are integral for developing well-rounded MET graduates.BackgroundThe
that allows a basic level of autonomy andownership among the teaching staff. Changes and reasons for change must be clearlycommunicated to the students as they are stakeholders in the process and need to know whythings change, just as they would in an industry setting to foster support for the change ratherthan frustration.In the future, we plan to distribute assignments as sets of requirements in the PDM system,which students must meet and link their file to, thus introducing the students to additional morecomplex digital thread concepts. The use of the PDM system also enables the integration of otherengineering systems. For example, ITI CADIQ can be employed to detect and report on modelintegrity, which can assist in the automation of
. Results4.1. Courses where SketchTivity was implementedThe first instructor was a mechanical engineering professor who taught a freshman-levelcomputer-aided design-based class. This course was one of the first courses taken by primarilyfreshman students in the mechanical engineering program, more than 80%; but also by civil andaerospace engineering majors, including those who plan to change majors in the future. Thesecond instructor taught a three-course sequence in first-year engineering mechanics, whichincluded a lecture and a lab. The third instructor taught in a first-year industrial designtwo-course sequence of labs in the fall and spring semesters, which met for two hours per weekand were primarily for industrial design majors.4.2. Significant
geometry in comparison to adding constraints. Examination of the models show different strategies with Design 3 favoring simpler sketches spread over more features. This is illustrated in Figure 9. More complex sketches would require significantly more time to fully constrain particularly for a novice. Interestingly, this potential advantage in more efficient sketching did not yield the best overall modeling time for Designer 3 as can be seen from the Total Modeling Time in Table 3. This time includes the effort taken to first develop a modeling strategy i.e. the features that will be used and the sequencing. It may be that Designer 3 took more time to develop this when planning their strategy with the goal of using simpler
with most things of a complex nature there are many problems that we maynot foresee. In doing our best to avoid these issues, diligent planning and research-basedsolutions will be utilized to provide students with an environment that is conducive tocollaborative learning. While the development of 3-D modeling skills and spatial ability areintegral to this project it is important to keep in mind that at the heart of the ABLE project is thedevelopment of a collaborative learning experience that can potentially help us addresschallenges we face as a global community.Figure 1Community Water TankFigure 2Automated Milk Line REFERENCESAllen, D. E., Donham, R. S., & Bernhardt, S. A. (2011). Problem
substitute for its desktop counterpart. While the curriculaacquainted students with robotics programming basics in VR, the software lacks substantialfollow-up content, limiting the students’ educational journey post-completion of these initiallabs.The absence of fundamental programming or path planning tools in the current release raisesquestions regarding the substantive benefits of VR beyond serving as an immersive simulationviewer. For instance, the inability to accurately position the robot’s tool in VR to align with thesimulation's geometry poses a significant barrier for further content essential for authentic robot-oriented tasks. Although it is possible to maneuver the robot in VR and record points withoututilizing the "object snaps