Applied Tests of Design Skills—Part II: Visual Thinking

2013 ◽  
Vol 135 (7) ◽  
Author(s):  
Jami J. Shah ◽  
Jay Woodward ◽  
Steven M. Smith
Keyword(s):  
Visual Memory ◽  
Divergent Thinking ◽  
Engineering Students ◽  
Spatial Reasoning ◽  
Standardized Test ◽  
Mental Image ◽  
Qualitative Reasoning ◽  
Difficulty Level ◽  
Visual Thinking ◽  
Design Skills

A number of cognitive skills relevant to conceptual design have been previously identified: divergent thinking, visual thinking, spatial reasoning, qualitative reasoning, and problem formulation. A battery of standardized test has been developed for each of these skills. This is the second paper in a series of papers on testing individual skill level differences in engineers and engineering students. In the first paper, we reported on the theoretical and empirical basis for divergent thinking test, as well as, on test formulation, data collection, norming studies, and statistical validation of that test. This paper focuses similarly on the efforts related to the visual thinking and spatial reasoning in engineering context. We have decomposed visual thinking into six categories: visual comprehension including perceptual speed, visual memory (that is, the visual memory system), visual synthesis mental image manipulation/transformation, spatial reasoning, and graphical expression/elaboration. We discuss the theoretical basis of a comprehensive test for engineers, test composition, trial runs, and computation of reliability measures. The alpha version was given to a small set of subjects to determine clarity of the questions and gauge difficulty level. The beta version was used for norming and test validation from over 500 samples that included engineering students and a smaller number of practicing engineers. Construct validation was achieved through basing the construction of our instrument off other well-known measures of visual thinking, while content validity was assured through thoroughly sampling the domain of visual thinking and including a variety of items both pertinent and specific to the engineering design process. The factor analysis reveals that there are possibly two eigenvalues above 1.0, an indication that it is a stable and accurate instrument. We emphasize that these tests are not just dependent on native abilities, but on education and experience; design skills are teachable and learnable.

Applied Tests of Design Skills—Part 1: Divergent Thinking

2012 ◽  
Vol 134 (2) ◽  
Author(s):  
Jami J. Shah ◽  
Roger E. Millsap ◽  
Jay Woodward ◽  
S. M. Smith
Keyword(s):  
Cognitive Skills ◽  
Divergent Thinking ◽  
Engineering Students ◽  
Spatial Reasoning ◽  
Problem Formulation ◽  
Qualitative Reasoning ◽  
Indirect Measures ◽  
Confirmatory Factor ◽  
Design Skills ◽  
Direct Measures

A number of cognitive skills relevant to conceptual design were identified previously. They include divergent thinking (DT), visual thinking (VT), spatial reasoning (SR), qualitative reasoning (QR), and problem formulation (PF). A battery of standardized tests is being developed for these design skills. This paper focuses only on the divergent thinking test. This particular test has been given to over 500 engineering students and a smaller number of practicing engineers. It is designed to evaluate four direct measures (fluency, flexibility, originality, and quality) and four indirect measures (abstractability, afixability, detailability, and decomplexability). The eight questions on the test overlap in some measures and the responses can be used to evaluate several measures independently (e.g., fluency and originality can be evaluated separately from the same idea set). The data on the twenty-three measured variables were factor analyzed using both exploratory and confirmatory procedures. A four-factor solution with correlated (oblique) factors was deemed the best available solution after examining solutions with more factors. The indirect measures did not appear to correlate strongly either among themselves or with the other direct measures. The four-factor structure was then taken into a confirmatory factor analytic procedure that adjusted for the missing data. It was found to provide a reasonable fit. Estimated correlations among the four factors (F) ranged from a high of 0.32 for F1 and F2 to a low of 0.06 for F3 and F4. All factor loadings were statistically significant.

Applied Tests of Design Skills: Divergent Thinking Data Analysis and Reliability Studies

2010 ◽  
Author(s):  
Jami J. Shah ◽  
Roger E. Millsap ◽  
Jay Woodward ◽  
S. M. Smith
Keyword(s):  
Cognitive Skills ◽  
Divergent Thinking ◽  
Engineering Students ◽  
Form Factors ◽  
Qualitative Reasoning ◽  
Visual Thinking ◽  
Factor Solution ◽  
Indirect Measures ◽  
Design Skills ◽  
Direct Measures

A number of cognitive skills relevant to conceptual design were identified. They include Divergent Thinking, Visual Thinking, Spatial Reasoning, Qualitative Reasoning and Problem Formulation. A battery of standardized tests have been developed for these skills. We have previously reported on the contents and rationale for divergent thinking and visual thinking tests. This paper focuses on data collection and detailed statistical analysis of one test, namely the divergent thinking test. This particular test has been given to over 500 engineering students and a smaller number of practicing engineers. It is designed to evaluate four direct measures (fluency, flexibility, originality, quality) and four indirect measures (abstractability, afixability, detailability, decomplexability). The eight questions on the test overlap in some measures and the responses can be used to evaluate several measures independently (e.g., fluency and originality can be evaluated separately from the same idea set). The data on the 23 measured variables were factor analyzed using both exploratory and confirmatory procedures. Two variables were dropped from these exploratory analyses for reasons explained in the paper. For the remaining 21 variables, a four-factor solution with correlated (oblique) factors was deemed the best available solution after examining solutions with more factors. Five of the 21 variables did not load meaningfully on any of the four factors. These indirect measures did not appear to correlate strongly either among themselves, or with the other direct measures. The remaining 16 variables loaded on four factors as follows: The four factors correspond to the different measures belonging to each of the four questions. In other words, the different fluency, flexibility, or originality variables did not form factors limited to these forms of creative thinking. Instead the analyses showed factors associated with the questions themselves (with the exception of questions corresponding to indirect measures). The above four-factor structure was then taken into a confirmatory factor analytic procedure that adjusted for the missing data. After making some adjustments, the above four-factor solution was found to provide a reasonable fit to the data. Estimated correlations among the four factors (F) ranged from a high of .32 for F1 and F2 to a low of .06 for F3 and F4. All factor loadings were statistically significant.

Rethinking the Comprehensive Test on Qualitative Reasoning for Designers

2013 ◽  
Author(s):  
Maryam Khorshidi ◽  
Jami J. Shah ◽  
Jay Woodward
Keyword(s):  
Time Allocation ◽  
Cognitive Skills ◽  
Analogical Reasoning ◽  
Divergent Thinking ◽  
Engineering Students ◽  
Deductive Reasoning ◽  
Qualitative Reasoning ◽  
Lessons Learned ◽  
Abductive Reasoning ◽  
Technical Problems

A battery of tests assessing the cognitive skills needed for the conceptual design is being developed. Tests on Divergent thinking and visual thinking are fully developed and validated. The first version of the qualitative reasoning test has also been developed; this paper focuses on the lessons learned from testing of the first version of the test (alpha version) and the improvements made to it since then. A number of problems were developed for each indicator of the qualitative reasoning skill (deductive reasoning, inductive reasoning, analogical reasoning, and abductive reasoning). Later, a protocol study was done with the problems to make sure that the problems assess the desired skills. The problems were also given to a randomly chosen population of undergraduate senior-level or graduate-level engineering students. Data was collected from the test results on the possible correlations between the problems (e.g. technical and non-technical problems); feedback on clarity, time allocation, and difficulty for each problem was also collected. Based on all of the observed correlations, the average performance of the test takers, and test parameters such as validity, reliability, etc. the beta version of the test is constructed.

Applied Tests of Design Skills—Part III: Abstract Reasoning

2014 ◽  
Vol 136 (10) ◽  
Author(s):  
Maryam Khorshidi ◽  
Jami J. Shah ◽  
Jay Woodward
Keyword(s):  
Analogical Reasoning ◽  
Divergent Thinking ◽  
Design Thinking ◽  
Test Construction ◽  
Abductive Reasoning ◽  
Difficulty Level ◽  
Future Research ◽  
Test Problems ◽  
Visual Thinking ◽  
Abstract Reasoning

Past studies have identified the following cognitive skills relevant to conceptual design: divergent thinking, spatial reasoning, visual thinking, abstract reasoning, and problem formulation (PF). Standardized tests are being developed to assess these skills. The tests on divergent thinking and visual thinking are fully developed and validated; this paper focuses on the development of a test of abstract reasoning in the context of engineering design. Similar to the two previous papers, this paper reports on the theoretical and empirical basis for skill identification and test development. Cognitive studies of human problem solving and design thinking revealed four indicators of abstract reasoning: qualitative deductive reasoning (DR), qualitative inductive reasoning (IR), analogical reasoning (AnR), and abductive reasoning (AbR). Each of these is characterized in terms of measurable indicators. The paper presents test construction procedures, trial runs, data collection, norming studies, and test refinement. Initial versions of the test were given to approximately 250 subjects to determine the clarity of the test problems, time allocation and to gauge the difficulty level. A protocol study was also conducted to assess test content validity. The beta version was given to approximately 100 students and the data collected was used for norming studies and test validation. Analysis of test results suggested high internal consistency; factor analysis revealed four eigenvalues above 1.0, indicating assessment of four different subskills by the test (as initially proposed by four indicators). The composite Cronbach’s alpha for all of the factors together was found to be 0.579. Future research will be conducted on criterion validity.

CAD Platform Independent Software for Automatic Grading of Technical Drawings

2017 ◽  
Author(s):  
Sanchit Ingale ◽  
Anirudh Srinivasan ◽  
Diana Bairaktarova
Keyword(s):  
Engineering Students ◽  
Spatial Reasoning ◽  
Learning Experience ◽  
Spatial Visualization ◽  
First Year ◽  
Spatial Skills ◽  
First Year Students ◽  
Pedagogical Tool ◽  
Students Success ◽  
Mechanical Objects

Spatial visualization is the ability of an individual to imagine an object mentally and understand its spatial orientation. There have been multiple works proving that spatial visualization skills can be improved with an appropriate training. Such training warrant a critical place in the undergraduate engineering curricula in many engineering schools as spatial skills are considered vital for students’ success in the technical and design fields [1–4]. Enhanced spatial skills help not only professionals in the engineering field but also everyone in the 21st century environment. Drawing sectional views requires mental manipulation and visual thinking. To enhance students spatial reasoning, one of the authors of this study, conducted a class in spatial visualization. The course-learning goal aimed at improving first-year engineering students’ spatial reasoning through instruction on freehand drawings of sectional view. During the semester, two teaching assistants had to grade more than 500 assignments that consisted of sectional views of mechanical objects. This was a tedious and a time consuming task. Motivated by this experience, this paper proposes a software aiming at automating grading of students’ sectional view drawings. The proposed software will also give live feedback to students while they are working on the drawings. This interactive tool aims to 1) improve the learning experience of first year students, with limited CAD knowledge, and 2) introduce a pedagogical tool that can enhance spatial visualization training.

scholarly journals Design Integrated in the Mechanical Engineering Curriculum: Assessment of the Engineering Clinics

2007 ◽  
Vol 129 (7) ◽  
pp. 682-691 ◽  
Author(s):  
Jennifer Kadlowec ◽  
Krishnan Bhatia ◽  
Tirupathi R. Chandrupatla ◽  
John C. Chen ◽  
Eric Constans ◽  
...  
Keyword(s):  
Survey Data ◽  
Mechanical Engineering ◽  
Engineering Students ◽  
Integrated Design ◽  
Curriculum Assessment ◽  
Rowan University ◽  
Core Courses ◽  
Team Environment ◽  
Design Skills ◽  
The Impact

At Rowan University, design has been infused into the curriculum through an eight-semester course sequence called the Engineering Clinics. Through this experience, students learn the art and science of design in a multidisciplinary team environment and hone their design skills throughout their 4-year career. This paper describes the objectives of the clinics, types of projects, and how the clinics complement traditional core courses in the curriculum. Impacts and benefits of the clinics on students and faculty are discussed, including retention and graduate study rates comparing Rowan University mechanical engineering students to their peers nationally. An assessment of the clinics is presented based on survey data and accreditation objectives and outcomes. Survey data from students were assessed to determine levels of students’ satisfaction and confidence based on the clinics. Results of alumni and employer surveys also provide valuable feedback for assessing and improving the clinics as well as confirmation of the impact of clinics after graduation. Survey data are discussed along with challenges of the clinics at Rowan and adaptability of them at other institutions. Overall, the clinics are a positive and integrated design experience in the curriculum and assist students in achieving the program objectives.

A Visualization-Based Approach to Engineering Kinematics Using Cognitive Models

2004 ◽  
Author(s):  
Dileep Sathyanarayana ◽  
Sundar Krishnamurty
Keyword(s):  
Engineering Students ◽  
Spatial Reasoning ◽  
Cognitive Models ◽  
Molecular Structures ◽  
Science Literature ◽  
Pedagogical Approach ◽  
Web Based ◽  
Psychology Education ◽  
Computer Based ◽  
Gear Trains

Visualization and spatial reasoning are integral to developing an understanding of contemporary sciences. They form the basis for understanding a wide variety of topics across science, mathematics and engineering, including molecular structures, topologies, motion and forces, and manufacturing processes. Within engineering, it can be argued that challenging and time consuming topics such as kinematics can be better taught by faculty, and hence better understood and appreciated by students, by advancing our understanding of human visualization and spatial reasoning and using this knowledge to develop computer-based visualization instruction in ways that maximize their effectiveness. The achievement of such a goal will require importing proven extant theories from other fields such as psychology, education, engineering and computer science. This paper presents the results of one such effort for teaching engineering kinematics. The motivation for this work can be found in cognitive science literature, where motion comprehension has been identified and studied as a mental task. Accordingly, a major task in doing this work involved the study of cognitive models of motion comprehension, and identifying key stages present in them. Mapping such key stages in motion comprehension on to kinematics domain, this paper presents the framework for the visual comprehension based pedagogical approach to kinematics. A web-based gear-trains tutor has been developed to demonstrate this concept. Results from the tests on a controlled population of engineering students are presented and the efficacy of a visual comprehension based approach as an instructional tool is discussed.

scholarly journals Smell-Based Memory Training: Evidence of Olfactory Learning and Transfer to the Visual Domain

2020 ◽  
Vol 45 (7) ◽  
pp. 593-600
Author(s):  
Jonas K Olofsson ◽  
Ingrid Ekström ◽  
Joanna Lindström ◽  
Elmeri Syrjänen ◽  
Anna Stigsdotter-Neely ◽  
...  
Keyword(s):  
Visual Memory ◽  
Difficulty Level ◽  
Memory Training ◽  
High Performing ◽  
Sense Of Smell ◽  
Visual Spatial ◽  
Visual Tasks ◽  
High Level ◽  
Visual Domain ◽  
Olfactory Training

Abstract Human and non-human animal research converge to suggest that the sense of smell, olfaction, has a high level of plasticity and is intimately associated with visual-spatial orientation and memory encoding networks. We investigated whether olfactory memory (OM) training would lead to transfer to an untrained visual memory (VM) task, as well as untrained olfactory tasks. We devised a memory intervention to compare transfer effects generated by olfactory and non-olfactory (visual) memory training. Adult participants were randomly assigned to daily memory training for about 40 days with either olfactory or visual tasks that had a similar difficulty level. Results showed that while visual training did not produce transfer to the OM task, olfactory training produced transfer to the untrained VM task. Olfactory training also improved participants’ performance on odor discrimination and naming tasks, such that they reached the same performance level as a high-performing group of wine professionals. Our results indicate that the olfactory system is highly responsive to training, and we speculate that the sense of smell may facilitate transfer of learning to other sensory domains. Further research is however needed in order to replicate and extend our findings.

scholarly journals Chess Players Increase the Theta Power Spectrum When the Difficulty of the Opponent Increases: An EEG Study

2019 ◽  
Vol 17 (1) ◽  
pp. 46 ◽  
Author(s):  
Juan Pedro Fuentes-García ◽  
Santos Villafaina ◽  
Daniel Collado-Mateo ◽  
Ricardo Cano-Plasencia ◽  
Narcis Gusi
Keyword(s):  
Power Spectrum ◽  
Divergent Thinking ◽  
Brain Regions ◽  
Difficulty Level ◽  
P Value ◽  
Alpha Power ◽  
Theta Power ◽  
Creative Ideation ◽  
Chess Players ◽  
Alternative Solutions

The present study aimed to analyze differences in the electroencephalogram (EEG) power spectrum (theta, alpha, and beta) between participants who won (winning group) and those who lost (losing group) in three different chess games: against their same Elo (100% chess games), 25% over their Elo (125% chess games), and 25% under their Elo (75% chess games). EEG was assessed at baseline and during the chess games. Method: 14 male chess players (age: 35.36 ± 13.77 and Elo: 1921 ± 170) played three games of 3 min, plus two additional seconds per move, while EEG was assessed. There were three difficulty levels (75%, 100%, and 125%), with two games (one with white pieces and another with black pieces) per level. The winning group showed higher theta power in the frontal, central, and posterior brain regions when difficulty increased (p-value < 0.05). Besides this, alpha power showed higher values (p-value < 0.05) in 125% games than in 75% chess games in C3, T3, T4, T5, and T6. The losing group showed a significant decrease (p-value < 0.05) in the beta and alpha power spectrum in frontal, central, parietotemporal, and occipital areas, when the opponent’s difficulty increased. Moreover, between groups, analyses showed higher theta power in the losing group than in the winning group, in C3, T5, T6, P4, and Pz (p-value < 0.05). Therefore, the winning group was able to adapt to each difficulty level, increasing theta power in the frontal, central, and posterior brain areas, as the efficiency hypothesis postulated. These changes were not observed in the losing group. Moreover, increases in alpha power during the most difficult games, in comparison with the easier, could have been caused by creative ideation and divergent thinking, as participants looked for alternative solutions against a higher-skilled opponent.

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