paper test in 2014 withthose taking the paper test in 2013 were found.Table 1: Comparison of average PSVT:R scores for first-time students (maximum scorepossible = 30) Type of test and year Average PSVT:R Average PSVT:R Average PSVT:R taken score score of females score of males LMS in 2014 22.5* 20.3 23.4** (s=4.88, n=430) (s=4.74, n=116) (s=4.66, n=314) Paper in 2014 23.8 20.8 24.5 (s=4.32, n=454) (s=4.39, n=90) (s=3.96, n=364) Paper in 2013 23.7 21.2 24.3
, quizzes (fixed-choice questions from the original workbook), and the software should be madeavailable to students on the university LMS.References[1] I. M. Smith, Spatial ability: its educational and social significance. San Diego, Calif.: R.R. Knapp, 1964.[2] D. L. Shea, D. Lubinski, and C. P. Benbow, “Importance of assessing spatial ability in intellectually talented young adolescents: A 20-year longitudinal study,” Journal of Educational Psychology, vol. 93, no. 3, pp. 604–614, 2001.[3] M. Kozhevnikov, M. A. Motes, and M. Hegarty, “Spatial Visualization in Physics Problem Solving,” Cognitive Science, vol. 31, no. 4, pp. 549–579, 2007, doi: https://doi.org/10.1080/15326900701399897.[4] S. Y. Yoon and E. L. Mann, “Exploring
with real-world examplesas compared to theoretical examples traditionally employed in introductory engineering graphicscourses.This material is based upon work supported by the National Science Foundation under Grant No.1725874. Any opinions, findings, and conclusions or recommendations expressed in thismaterial are those of the author(s) and do not necessarily reflect the views of the NationalScience Foundation.References[1] J. V. Ernst, T.O. Williams, A. C. Clark, and D. P. Kelly, “Psychometric properties of the PSVT:R Outcome Measure: A preliminary study of introductory engineering design graphics,” in 70th EDGD Midyear Conference Proceedings, Daytona, FL, USA, January 24-26, 2016.[2] S. A. Sorby and B. J. Baartmans
selection paths based on specific class or numerical valueof selected parameter (e.g., final test score). Each node represents a splitting rule for one specificattribute (e.g., answer to a test question). This analytic tool has as well the option to reducepredictive errors by searching for an optimal decision-tree development, according to a specifiedcriterion [12].The objective in this study is to search for dominant factors that predict positive test scoreimprovement when comparing pre-intervention to post-intervention evaluation of students’spatial visualization skills. Another goal is to identify influential test question(s) and/ordemographic factors that will move the predictive modeling efforts into a broader identificationand grouping of
their thinking. As students review each other‟s screencasts, their own thinking and metacognition will be re-evaluated from another learner‟s perspective who is not necessarily a teacher or a textbookauthor. Learning from peers is more authentic and more sustainable than learning from atextbook or from a teacher17. In addition, receiving peers‟ comments on their own screencastadds to these metacognitive items that will eventually help improve their CAD knowledge andskills. In this National Science Foundation (NSF) project, two mechanical engineering faculty andtwo learning scientists have collaborated to implement a student-centered instructional strategy,namely peer-generated screencast strategy in teaching CAD in the undergraduate
students (PostBac not included) PostBac 2.49 2.00 2.21 2.23 0.36 2.29 students Significance Not Not Not Not significant significant significant significant at 5% at 5% at 5% at 5% We will track dental school graduation rates of the PostBac program students. Furthermore, we intend to investigate the differences in gender and corresponding scores.References1. Bennett, G.K., Seashore, H. G., & Wesman, A. G. (1973). Differential aptitude tests, forms S and T. New York: The Psychological Corporation.2. Gray, S. A
program than GPA, such as grades in specificcourses.AcknowledgementsThis work was conducted under IRB 2017-011(N) and grew out of work started under the NSFEngage Project, Award #0833076, at Stevens Institute of Technology.References[1] Sorby, S., “Educational Research in Developing 3-D Spatial Skills for Engineering Students,” International Journal of Science Education, vol. 31, no. 3, 2009, pp. 459-480.[2] Norman, K.L., Spatial visualization – A gateway to computer-based technology. Journal of Special Educational Technology, XII(3), 1994, pp. 195–206.[3] Smith, I.M., Spatial ability - Its educational and social significance. London: University of London, 1964.[4] Wai, J., Lubinski, D., and Benbow, C.P., “Spatial ability for STEM
the excitement and energy generated by this extracurricular project to amplifytechnical skill development. Project outcomes and perspectives from students and faculty arepresented.IntroductionPersons with malformed upper extremities have significant variation with some havingfunctional wrist joints while other are limited to only elbow joint(s). Therefore, personalizing thefit of any prosthetic type device often requires significant modifications even if a proven designsuch as the UnLimbited Arm 2.0 - Alfie Edition [1] is available. These modifications are oftendone after parts have been fabricated and are an accepted part of the fitting process. It’s a generaltenet of engineering that the sooner in the engineering process a change can be
visualizationskills, both, for development of imagination and creativity, as well as development ofcompetencies directly related to technical fields such as engineering graphics and design.In this field of graphics and design, which is more linked to STEM education, there are acceptedtest such as the Purdue Spatial Visualization Test - Rotations PSVT:R (Guay, 1977), the MentalCutting Test (MCT) (Sorby, 1999) and the Shepard-Metzler Rotation (S-M) Test (Shepard, 1971)and its modification (Vandenberg, 1978). All of these tests have been used to measure thevisualization skills in an individual at a given time, thus providing a reference for comparison. Theunderlying concept in these tests is the mental rotation of 3D given objects. PSVT:R is perhapsone of the
received the 2015 Presidential Award for Excellence in Science, Mathematics, and Engineering Mentoring.Miss Dana Corrina Dimitriu Dana Dimitriu is a third-year mechanical engineering student at the University of Texas at San Antonio. She is currently working on receiving her bachelor’s degree in Mechanical Engineering with a minor in Psychology. She has interests in biomechatronics, prosthetics, 3D visualization, and graphic design. c American Society for Engineering Education, 2020 A Simple Method to Help Students Improve 3-D Visualization SkillsAbstractSpatial visualization skills and attention to detail can be effectively improved using variousspecialized methods. Starting in the 1990’s multiple
features that would promote more meaningful engagement in the app, show the importance of high quality design and implementation of technology tools for learning and research. References [1] S. Sorby, N. Veurink, and S. Streiner, “Does spatial skills instruction improve STEM outcomes? The answer is ‘yes,’” Learning and Individual Differences , vol. 67, pp. 209–222, 2018. [2] M. Berkowitz and E. Stern, “Which cognitive abilities make the difference? Predicting academic achievements in advanced STEM studies,” Journal of Intelligence , vol. 6, no. 4, p. 48, 2018. [3] S. Sorby, B. Casey, N. Veurink, and A. Dulaney, “The role of
components of the voluntary workshopthat need to be further considered. Moving forward, it would be interesting to assess the effect ofa mixed-methods approach (CAD/origami) in our context and to develop a larger sample usingthe indirect (origami) method (n=19 in this study).AcknowledgementsThis work was conducted under IRB 2017-011(N) and grew out of work started under the NSFEngage Project, Award #0833076, at Stevens Institute of Technology.References1. Sorby, S. A. (2009). Educational research in developing 3‐D spatial skills for engineering students. International Journal of Science Education, 31(3), 459-480.2. Smith, I.M. (1964). Spatial ability - Its educational and social significance. University of London Press.3. Wai, J., Lubinski, D
derived by the analytics software.Figure 1 displays all initial variables with first-generation college students as the root node. Theclassification tree splits the observations into binary categories based on the variable values ineach observation. In figure 1’s case, the binary classification is persistence in engineering [Yes]and non-persistence [No]. For categorical variables, the split is which variable value existswithin a particular observation. For continuous variables, the algorithm applies a regressionanalysis that determines the splitting point at a mathematically logical point. This model providesthe advantage of adaptive ability and will self-adjust with new data. The darker color implies agreat proportion of persistence. Next to the
/4. Campbell, C., Senior Mechanical Engineer, iRobot, Email Correspondence, 20165. Chester, I. (2007). Teaching for CAD expertise, International Journal of Technology and Design Education, Volume 17, Issue 1, pp 23-356. Devine, K PhD., Illinois State University, Telephone Interview, 20167. Gaughran, W. F. (2002). Cognitive modeling for engineers, Proceedings of the 2002 American Society for Engineering Education Annual Conference and Exposition.8. Harris, S., Co-Founder and VP of OnShape, Telephone Interview, 20169. Hinkle, K., Senior Designer, Senior Aerospace, Email Correspondence, 201610. Krish, S. (2011). A practical generative design method, Computer-Aided Design, Volume 43, Issue 1, pp 88- 10011. PTC. (2011
score: 147.00 / 205 (71.71%) 139.00 / 195 (71.28%) Mode score: occurred 22 time(s) occurred 20 time(s) Standard deviation: 23.15 25.48 Reliability coefficient (KR21): 0.9264 0.9428 Range: 205 193 Interquartile range: 29 33Table 2. Descriptive/demographic data for the ADDA AAD certification exam.The exam is a criterion referenced exam in that the exam taker must respond correctly to 300 ofthe 400 items (75%) to be certified. Achieving the 75% threshold is not require for each of the 20competencies, however. For program assessment, the exam can be used as a
Figure 7 – Selection from a student’s digital media portfolio for PN4011Not only was it observed that students with below average spatial skills benefited Page 26.286.9significantly from this extra class time, we also found that those students with high spatialskills also valued the activities. This is supported in some of the comments extracted fromstudents’ reflective diaries:“My strengths are the lab 1’s, I enjoy these and have no issues as I work through theworkbook. I also find my sketching a strong point as I am confident enough to try anythingeven if I make a mess of it ill still try again and give it another go.” Student 8 (Male) – Pre-Test
doingspatial reasoning tasks, so it is possible that this extra time is a contributing factor in the reportedgains. On the other hand, students gained substantially simply by taking the class, so the benefitsof the app on its own are not clear.Another direction for further research should focus on additional development of the app.Possibilities include adaptive presentation of lessons based on student progress, further use ofgamification to enhance motivation and engagement, and building assessment into the app itself.References[1] S. Sorby, B. Casey, N. Veurink, and A. Dulaney, “The role of spatial training in improvingspatial and calculus performance in engineering students,” Learning and Individual Differences,vol. 26, pp. 20–29, 2013.[2] O. Ha
emotional intelligence in children with autism. Entertainment Computing. 38.Janssen, S., de Ruyter van Steveninck, J., Salim, H. S., Bloem, B. R., Heida, T., & van Wezel, R. J. (2020). The beneficial effects of conventional visual cues are retained when augmented reality glasses are worn. Parkinson’s Disease, 2020.Kimiko Ryokai, Hayes Raffle, and Robert Kowalski.(2012).StoryFaces: pretend-play with ebooks to support social-emotional storytelling. In Proceedings of the 11th International Conference on Interaction Design and Children (IDC '12). Association for Computing Machinery, New York, NY, USA, 125–133.Miller, J. D., Godfroy-Cooper, M., & Szoboszlay, Z. P. (2019). Augmented-Reality Multimodal Cueing
learningand also assists the Center with its assessment needs.The Assessment Partners program entails three stages. First, faculty partners identify theSLO that most closely aligns with their course learning objectives. They agree to createan assessment for that SLO in their course through an assignment aligned closely with therubric (exam question(s), project, assignment, etc.) that they can easily share with SLSCenter. A Center staff member meets with each faculty partner to review the assignmentand ensure that it will work well with the rubric. Student work products for multiplecourses aligned with a particular SLO are then scored by a team of SLS staff and facultypartners collaboratively, using the rubric (faculty do not score the work of their
. Horlin, J. Hutchison, J.A. Murray, L. Robson, M.K. Seery, J. MacKay, "Ten simple rules for supporting a temporary online pivot in higher education”, PLOS Computational Biology, October 1, 2020, Retrieved from https://doi.org/10.1371/journal.pcbi.1008242.[2] D. Schaffhauser, “Educators Feeling Stressed, Anxious, Overwhelmed and Capable”, The Journal: Transforming Education, June 6, 2020, Retrieved from https://thejournal.com/articles/2020/06/02/survey-teachers-feeling-stressed-anxious- overwhelmed-and-capable.aspx.[3] C. Cahill, S. Jackson, N. Summerall, K. Harruna, “Helping Career and Technical Education Programs Meet this Moment”, JFF, September 1, 2020, Retrieved from: https://www.jff.org/what-we-do/impact
technologiesand provide ample reason to reexamine the opportunities for self-directed learning.! !Candy (2004) suggested that self-directed learning “provides a more direct route intounderstanding the actual dynamics of and relationship(s) between learning andtechnologies.” Technology can constrain the direction and focus, allowing for a user toquickly find and record relevant information, yet it also can be a distracting environmentthat leads to inefficiency or reduces motivation. Technology affords incredible access forlearners to connect with others, explore topics of interest, and participate in opportunitiesotherwise unavailable to them. In addition, technology provides vast amounts of resources,both information and people, to serve as materials for
assistance in the development of the SVT digital curriculum, datacollection, and for serving as teaching assistants during the course; Monica A. Sweet, Ph.D. forguidance with assessment; Christine Alvarado. Ph.D. for guidance with App development;Jessica Block, Deborah Forster Ph.D, Jurgen Schultz Ph.D., and Philip Weber (QualcommInstitute) for getting the software and project off the ground; Sheryl Sorby and Cengage LearningInc. and for use of exercises from their workbook; and the Qualcomm Institute at UC San Diego,the Academic Senate at UC San Diego, and Engaging Students in Engineering (ENGAGE) fortheir financial support for the development of the Spatial Visualization Trainer (SVT) andcorresponding studies.References:[1] Sorby, S. A. (2009
holistically in a 3D sense.In terms of future study, this case suggests that the use of blindfolded activities may be areasonable curricular option to explore to help sighted students develop spatial abilities.AcknowledgementsThe author wishes to thank Jason Varnado at the Center for Student Academic Success office atGonzaga University for his unfailing support in developing curricular materials for the blindstudent. Without his efforts, the course content would have been diminished. The author alsowishes to thank the blind student for her efforts in the course and explaining how parts andswelled drawings were perceived throughout the course.References[1] S. A. Sorby, "Educational research in developing 3‐D spatial skills for engineering
the need for student accountabilitymeasures to be part of the flipped classroom design. Students and faculty are used to that modelof instruction and there is evidence that a more behaviorist approach to the online content is acomponent of the flipped classroom model.4 More research and development of the flippedclassroom model is needed to determine the most effective methods and theoretical framework(s)from which to best design and implement the flipped classroom instructional model in highereducation.Conclusion It is clear that the flipped classroom instructional model is being used in engineeringgraphics education at the university level. The extent of its use and how the model isoperationalized across the field is not clear. This
. Toyota Material Handling Europe, Toyota Production System and what it means for business, www.toyota -forklifts.eu, 2014.2. Harry P. Bahrick, Lorraine E. Bahrick, Audrey S. Bahrick, Phyllis E. Bahrick, “Maintenance of a Foreign Language Vocabulary and the Spacing Effect,” Psychological Science, Vol. 4, No. 5, Sept 1993, 316-21.3. N.J Cepeda, E.Vul, D. Rohrer, J.T. Wixted, and H. Pashler, “Spacing Effects in learning: A temporal ridgeline of optimal retention,” Psychological Science, 19, 2008, 1095-1102.4. Henry Roediger, III, and Jeffrey D. Karpicke, “The Power of Testing Memory: Basic Research and Implications for Educational Practice,” Perspectives on Psychological Science, Vol. 1, No. 3, 2006, 181-210.5. Henry Roediger, III, and
., & Camba, J. D. (2014), A Review of the Design Intent Concept in the Context of CAD Model Quality Metrics, Paper presented at 2014 ASEE Annual Conference, Indianapolis, Indiana. https://peer.asee.org/199925. Kirstukas, S. (2013). A Preliminary Scheme for Automated Grading and Instantaneous Feedback of 3D Solid Models, Proceedings of the Midyear Conference of the Engineering Design Graphics Division of ASEE, pp. 53- 58.6. Baxter, D., & Guerci, M. (2003). Automating an Introductory Computer Aided Design Course to Improve Student Evaluation, Paper presented at 2003 Annual Conference, Nashville, Tennessee. https://peer.asee.org/11479