givenapproximately three assignments throughout the semester that required them to sketchorthographic projections and isometric views of objects. These assignments were designed tohelp improve spatial visualization ability. However, the class was generally focused on 3Dmodeling skills and SolidWorks operation, and not on spatial visualization ability.A survey was also administered to assess self-efficacy and to ask the students about how helpfulthey found the different learning activities in the course. We measured self-efficacy regarding 3Dgraphics topics using the three-dimensional modeling self-efficacy scale described by Densenand Kelly [21]. We will refer to this scale as the 3DM-SES in this paper. Agreement on eachitem of the nine items of this survey
, such as single inclined objects (p=0.036), doubleaxis rotations (p=0.016) and short 90 rotations (p=0.013) showed statistically significantdifferences with the Experimental group scoring higher than the Control group. Page 13.1200.2Methodology Two web-based tools with automated data collection were used to obtain a measure of auvwfgpvÓu"urcvkcn"cdknkv{"cpf"ugnh-efficacy9. The two tests used were a subset of the PurdueSpatial Visualization Test (PSVT)13 and a Self-Efficacy Test (SET) developed for this research.These two tests were administered to mechanical engineering freshmen at the beginning and atthe end of the fall semesters in
and their impressionsof the app. Students found the app engaging, easy to use, and something they would do wheneverthey had “a free moment”. 95% of the students recommended the app to a friend if they arestruggling with spatial visualization skills. This paper will describe the implementation of themobile Spatial Vis™ sketching app in a large college classroom and highlight the app’s impactin increasing self-efficacy in spatial visualization and sketching despite the small screen size.IntroductionThe use of mobile devices and specifically touchscreen technology in education has increasedtremendously over the years due to their increase in ubiquity and computing capabilities. Asurvey was conducted online within the United States by Harris Poll
, including student scoreon the pretest three-dimensional modeling self-efficacy (3DSE) assessment, gender, age, andwhether or not the student had a parent with professional engineering backgrounds. The three-dimensional self-efficacy instrument consisted of nine questions, each being a 7-point Likerttype item, designed to measure students’ self-efficacy related to modeling three-dimensionalobjects [11]. Logistic regression could not identify for which subgroups of students the variableswere most significant. For these reasons, machine learning analytics software was used toexamine the predictors, and their interactions, that led to persistence in engineering degreeprograms. Machine learning has gained popularity over recent years due to its ability
. 7, no. 1, pp. 9, 2016.[9] N. Honken, P. S. Ralston, “Freshman engineering retention: A holistic look,” Journal of STEM Education: Innovations & Research, vol. 14, no. 2, pp 29-37, 2013.[10] M. W. Ohland, C. E. Brawner, M. M. Camacho, R. A. Layton, R. A. Long, S. M. Lord, and M. H. Wasburn, “Race, gender, and measures of success in engineering education,” Journal of Engineering Education, vol. 100, no. 2, pp. 225, 2011.[11] T. D. Fantz, T. J. Siller, and M. A. Demiranda, “Pre-Collegiate Factors Influencing the Self- Efficacy of Engineering Students,” Journal of Engineering Education, vol. 100, no. 3, pp. 604–623, 2011.[12] S. Freeman, S. L. Eddy, M. Mcdonough, M. K. Smith, N. Okoroafor, H. Jordt, and M. P
canbetter devise pedagogical strategies targeted at improving self-efficacy and retention of femalestudents.The objective of this study is to determine if women do in fact put more effort into anintroductory engineering graphics class, and to determine if this extra effort can compensate fortheir lower average spatial visualization ability, resulting in equal course outcomes such as examand homework grades. We hypothesize that: 1) female students put more effort (measured asquiz scores, time spent on homework, attendance, and homework scores) into engineeringgraphics courses; and 2) that this greater effort by female students results in roughly equalaverage course and exam grades for men and women. While other studies have observed
and Reflection Strategies for Creativity in Student Design Projects, In 4th international conference on design creativity, Atlanta, GA.5. Linsey, J. S., Tseng, I., Fu, K., Cagan, J., Wood, K. L., and Schunn, C. (2010) A Study of Design Fixation, Its Mitigation and Perception in Engineering Design Faculty, Journal of Mechanical Design 132, 041003-041003.6. Carberry, A. R., Lee, H.-S., and Ohland, M. W. (2010) Measuring Engineering Design Self- Efficacy, Journal of Engineering Education 99, 71-79.7. Newell, A., and Simon, H. A. (1972) Human problem solving, Vol. 104, Prentice-Hall Englewood Cliffs, NJ.8. Simon, H. A. (1973) The structure of ill structured problems, Artificial intelligence 4, 181-201.9
-improvement and personal growth were found to be highly valued. In comparison with extrinsicgoals from the same study, further differences were found between intrinsic and extrinsicmotivation. Other studies have found that student motivation is directly linked to seeing valueand meeting goals and beliefs about the importance of a given task or subject.The value of motivation can be conceptualized through various approaches (e.g., learning vs.performance goals, intrinsic vs. extrinsic orientation, and interests); this motivational componenteffectively concerns students' motives for the completion of a task7. Self-efficacy has a majorrole in student motivation at both intrinsic and extrinsic levels. Students’ perceived self-efficacyinfluences as the
courses have noticed a marked increase in students’ confidencelevels over the course of the spatial training. Could a student’s confidence (and therefore theirspatial skills) influence their success and their career choices?Studies have shown the impact of confidence or self-efficacy on student success. For example,Lent et al. (1984)7 found that students reporting high self-efficacy (confidence in their ability to Page 22.1314.2successfully complete various scientific and engineering degrees) achieved higher grades andpersisted longer in scientific and technical programs than those that reported low self-efficacy.Additionally, Towle et al
building blocks for the development of self-efficacy 44.Further indication of this effect is the subsequent formation of a 3D printing club by anumber of the students in the class, in order to continue their design activities in anextracurricular fashion.No specific assessment of self-efficacy (in particular in relation to the reported genderdifferences) was conducted, as the survey instrument of this work in progress wasdesigned to only probe for student preferences. Future work however will considerexpanding the analysis to include these assessments.Conclusion and future workThe intention of this work-in-progress was to qualify changes in SV caused by thegeometric design projects and the 3D printing interventions, and the student survey
, 26, 20-29.4. Potter, C., Van Der Merwe, E., Kaufman, W., and Delacour, J. (2006). A LongitudinalEvaluative Study of Student Difficulties with Engineering Graphics. European Journal ofEngineering Education. 31(2), 201-214.5. Kozhevnikov, M., Kozhevnikov, M., Yu, C.J., and Blazhenkova, O., (2013). Creativity,Visualization Abilities, and Visual Cognitive Style. British Journal of Educational Psychology.83, 196-209.6. Frey, G., and Baird, D. (2000). Does Rapid Prototyping Improve Student VisualizationSkills. Journal of Industrial Technology. 16(4), 2-6.7. Towle, E., Mann, J., Kinsey, B., O’Brien, E et.al. (2005). Assessing the Self Efficacy andSpatial Ability of Engineering Students from Multiple Disciplines. 35th ASEE Frontiers inEducation
Visualization Effectiveness Using EEG and Cognitive Load. Eurographics, 2011. 30(3): p. 791-800.16. Guttormsen, S. and P.G. Zimmerman, Investigating Means to Reduce Cognitive Load from Animations: Applying Differentiated Measures of Knowledge Representation. Journal of Research on Technology in Education, 2007. 40(1): p. 64-78.17. Baddeley, A., Working Memory: Looking Back and Looking Forward. Nature Reviews: Neuroscience, 2003. 4: p. 829-839.18. Hoffman, B. and G. Schraw, The influence of self-efficacy and working memory capacity on problem solving efficiency. Learning and Individual Differences, 2009. 19: p. 91-100.19. Hoffman, B. and G. Schraw, Conceptions of Efficiency: Applications in Learning and Problem
- Visualization of Rotations: Mental Rotation Test and the MotivatedStrategies for Learning Questionnaire (MSLQ) Attitude Survey were paired and administeredto university undergraduate technology, engineering, and design education and engineeringstudents. Similarly, a determination of student intrinsic goal orientation, extrinsic goalorientation, task value, control of learning beliefs, self-efficacy learning performance, andtest anxiety was conducted and paired with abilities of students to visualize rotated three-dimensional objects to highlight associations/relationships among student motivation andlearning and mental rotation ability. The supplemental study data collection allowed forsubgroup investigation of the at-risk population, therefore
students stillhave access to help if they need it. Logistics of group work in an online class will need to becarefully considered using video conferencing software.References[1] M. Holdhusen. “A “flipped” statics classroom,” presented at the 122nd ASEE Annual Conference and Exposition, Seattle, WA, June 14-17, 2015. Paper ID #12162.[2] M. Radu. “Applying the Flipped Classroom Pedagogy in a Digital Design Course,” presented at the 126th ASEE Annual Conference and Exposition, Tampa, FL, June 15-19, 2019. Paper ID #25080.[3] H. Ozyurt and O. Ozyurt. “Analyzing the effects of adapted flipped classroom approach on computer programming success, attitude toward programming, and programming self- efficacy.” Comput
using an online testing toolthey developed. They found there was no significant differences in performance, howeverstudents spent more time on the online test.Other studies have found some differences in on-line versus paper exams. Deutsch, Herrmann,Frese, and Sandholzer4 found gender differences in students taking online exams. These genderdifferences were attributed to differences in computer-self efficacy, but they found thedifferences were reduced considerably after students had a single experience taking an onlineexam. McDonald5 considered score equivalence between paper and computer-based assessmentsand concluded that individual differences in computer experience, computer anxiety, andcomputer attitudes could impact the potential of some
reflections, and observations by the instructor while they work in class as well as students’ responses to a survey related to the assignment. Formative assessments are in the form of discussions with the members of the individual groups .14II. Emerging technologies for virtual active learning Pilot results were impacted by variability in students’ competency and self-‐efficacy with the new tools presented to them under tight time constraints. In order to establish baseline student competency with, and thereby measure the effectiveness of, A) the digital tablet and stylus and B) the Moodle Discussion Forum as collaborative ideation tools, units of
undergraduate students, developed the TESS (Teaching Engineering Self-efficacy Scale) for K-12 teachers, and rescaled the SASI (Student Attitudi- nal Success Inventory) for engineering students. As a program evaluator, she has evaluated the effects of teacher professional development (TPD) programs on K-6 teachers’ and elementary students’ attitudes to- ward engineering and STEM knowledge. As an institutional data analyst, she is investigating engineering students’ pathways to their success, exploring subgroup variations. Page 26.707.1 c American Society for Engineering Education, 2015
Educational Research Association, April, Boston, Massachusetts (ERIC Document Reproduction Service No. ED189166.)28. Battista, M. The Interaction between Two Instructional Treatments of Algebraic Structures and Spatial- Visualization Ability. Journal of Educational Research, 74(5), May/June 1981, 337-341.29. Towle, E., et al. Assessing the self efficacy and spatial ability of engineering students from multiple disciplines. 35th ASEE/IEEE Frontiers in Education Conference, October 19-22, 2005, Indianapolis, Indiana.30. Hamlin, A., Boersma, N., & Sorby, S. Do spatial abilities impact the learning of 3-D solid modeling software? Proceedings of the 2006 ASEE Annual Conference & Exposition, June 18-21, Chicago
spatial skills for engineering students”. International Journal of Science Education. Vol 31(3), pp 459-80, Feb. 2009.[8] L. Van Den Einde, N. Delson, L. Cowan, “Sketching App to Teach Spatial Visualization Skills Suitable for Remote and In-Person Instruction”, Proceedings of INTED 2021, virtual conference, March 8-9, 2021.[9] N. Delson, L. Van Den Einde, E. Cowan, J. Tara “eGrove Education.” [Online] Available www.egrove.education.[10] J. Power, J. Buckley, and N. Seery. “Visualizing Success: Investigating the Relationship between Ability and Self-Efficacy in the Domain of Visual Processing”. 70th ASEE Engineering Design Graphics Division Midyear Conference, Embry-Riddle Aeronautical University, FL, January, 2016.[11