Williams, Sutton, & Allen. Spatial Ability: Issues Associated with Engineering and Gender
Spatial Ability: Issues Associated with Engineering and Gender Anthony Williams University of Newcastle, Newcastle, Australia
[email protected] Ken Sutton University of Newcastle, Newcastle, Australia
[email protected] Rebecca Allen University of Newcastle, Newcastle, Australia
[email protected] Abstract: The link between students’ spatial ability and their success in a range of engineering courses has been recognised in recent years but its full impact is not understood. This paper reports on research into the spatial abilities of novice designers, engineering students being a major component of this group. The paper focuses on the relationship of spatial ability to gender as well as spatial ability and UAI. This paper also provides an overview of the spatial abilities according to discipline.
Introduction An important aptitude for students studying engineering courses is spatial ability, often referred to as simply visualisation. Spatial ability can be defined (Sutton & Williams, 2007) as the performance on tasks that require: • the mental rotation of objects, • the ability to understand how objects appear in different positions, and • the ability to conceptualise how objects relate to each other in space. A substantial part of spatial ability is three-dimensional (3D) understanding. 3D understanding is the ability to extract information about 3D properties from two-dimensional (2D) representations (Sutton, Heathcote, & Bore, 2005). This skill requires perceptual abilities to interpret what is seen, and spatial abilities to mentally manipulate graphical representations.
Importance of Spatial Ability In many of the engineering fields, there is a level of graphical communication used to communicate concepts and to document designs. As such, graphical communication is a core component of many of these programmes. The imperative to prepare students with these skills is invested in the graphical communication courses offered by universities (Sutton & Williams, 2006). Sorby (2006) reports evidence that 3D spatial skills are critical to success in engineering. Her research reveals the importance of advanced spatial reasoning and visualisation skills to these disciplines, although these skills are not handled well by many novices. There is also evidence of high failure rates in these types of courses and evidence to support the value of early spatial ability training. Despite there being a vast amount of research on spatial ability, there is very little known about the effects of spatial ability in engineering and how it is developed through appropriate education programmes. Furthermore, previous research in spatial ability tends to focus on one or two test types and neglects test types that specifically target spatial cognition relevant to engineering disciplines (Allahyar & Hunt, 2003). These findings emphasise the need for further research into higher spatial thinking (Sutton & Williams, 2006).
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Williams, Sutton, & Allen. Spatial Ability: Issues Associated with Engineering and Gender
Overview of Spatial Ability Spatial intelligence forms part of general intelligence (Kellogg, 1995) and is characterised by a number of elements. Maier (1998) acknowledges the debate among the literature surrounding the exact characterisation of spatial ability. Such debate continues today (Akasah & Alias, 2006). According to Maier (1998), as presented in Table 1, there are 5 main components of spatial ability. Table 1: The 5 Factors of Spatial Ability Factor Spatial Ability Component 1 Spatial Relations (SR) 2 Spatial Perception (SP) 3 Spatial Visualisation (SV) 4 Mental Rotation (MR) 5 Spatial Orientation (SO) From the above model, Olkun (2003) classifies the two main components of spatial ability to be Spatial Relations (SR) and Spatial Visualisation (SV). Spatial relations is generally defined in terms of mental integration (Olkun, 2003). This definition is typically three-fold referring to: • the perception of a target object in relation to another object on a dimension such as size, distance, volume, order, position or other distinguishing feature (Kosslyn, Chabris, Marsolek, & Koeing, 1992). • the relationship between a target object and the environment (Kosslyn et al., 1992). • the relations among the parts of a single object (Nagy-Kondor, 2007). Spatial visualisation is typically defined in terms of object rotations or movement (Nagy-Kondor, 2007). Again there is some debate in the literature as to the actual definition of SV. The most widely accepted definition was provided by McGee (1979). McGee (1979) defines SV as “an ability to mentally manipulate, rotate, twist, or invert pictorially presented visual stimuli” (p. 3). This may involve “imagining the rotations of objects in space” (West, Morris, & Nichol, 1985, p. 29), or “visualising a configuration in which there is movement of or displacement among (internal) parts of the configuration … [such that the] spatial relations between the objects are changed” (Maier, 1998, p. 70). As such, SV typically relates to the movement of an object in a particular spatial context or the repositioning of internal parts. While SR and SV have been identified as the principal components of spatial ability, the literature continues to support the 5-factor model contained in Table 1. Blasko, Holliday-Darr, Mace, and Blasko-Drabik (2004) acknowledge the importance and role of a further two components of spatial ability in the overall make-up of spatial intelligence: mental rotation and spatial perception. Mental rotation refers to the ability to rotate visual images mentally (Nagy-Kondor, 2007). These images may be 2D or 3D (Maier, 1998). Mental rotation ability is generally defined in terms of speed and accuracy (Adanez & Velasco, 2002). There is much debate in the literature as to the classification of MR as a distinct and separate spatial skill. Mental rotation is generally considered in the literature as representative of the broader spatial skill category of SR (Olkun, 2003) and also of SV (Akasah & Alias, 2006). However, Blasko et al. (2004) argue the prevalence and importance of MR in spatial ability and spatial learning warrants its classification as a specific component of spatial ability referred to as mental rotation ability (MRA) rather than as a sub-category of SR and/or SV. The Maier (1998) model presented in Table 1 supports the classification of MR as a specific factor of spatial ability. Spatial perception is defined by Blasko et al., (2004) as “the ability to determine spatial relationships among objects despite distracting information” (p. 256). More specifically, SP is the ability to mentally fix the vertical or horizontal position of an object which is depicted at varying degrees of orientation (Nagy-Kondor, 2007). What results is that while the “relation of the subject’s [visual position] to the objects changes, the spatial relations between the object’s [internal parts] do not change” (Maier, 1998, p. 70).
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Williams, Sutton, & Allen. Spatial Ability: Issues Associated with Engineering and Gender
Support for the existence of the final component of the Maier (1998) model, spatial orientation, has also been found in the literature (Nagy-Kondor, 2007). Spatial orientation is defined by Maier (1998) as “the ability to orient oneself physically or mentally in space” (p. 71). The challenge of the task is that “the person’s own spatial position is necessarily an essential part of the task” (Maier, 19981, p. 71). This tests the individual’s mental agility to adapt to “changing orientations in which a configuration may be presented” (McGee, 1979, p.4). The Maier (1998) model presented in Table 1 outlines the five main factors of spatial ability. The specific role of each factor within an engineering context is yet undetermined. Given the importance of spatial ability in engineering and the limited knowledge of the spatial ability of novice designers (Sorby, 2006), further assessment of a range of spatial tasks is essential to examine the role of each factor of spatial ability within a design context and to profile the spatial skills of novice designers.
Measuring Spatial Ability Performance The measurement of spatial ability within design-based disciplines is the focus of the current research. This study feeds into a larger project funded by the Australian Learning and Teaching Council (ALTC). One major objective of the ALTC project is to develop a 3D Ability Test (3DAT) for novice designers that will underpin the development of learning tasks to improve visualisation skills. The 3DAT research began with a preliminary study consisting of nine subtests and 119 test items. Through item analysis, the 3DAT was reduced to six subtests and 45 test items. Results of both choice accuracy and reaction time (RT) were considered, and reliability and correlation procedures were conducted to assist in this reduction of items. Following this study, a web version of the 3DAT was developed and comparisons were made with the earlier laboratory-tested version. Validity and reliability measures were encouraging. Smaller Honours projects followed, one investigating predictive, convergent and divergent validity, while others investigated gender differences and the impact of initial 3D learning tasks on spatial ability performance. Procedures and sequencing were deliberate to conform to the standards required for psychometric test development. Continued development of the 3DAT is currently taking place under the larger ALTC funded project. The 3DAT is being developed to measure spatial ability as it applies to graphical communication using a range of spatial cognition tasks. The range of spatial tasks reflects the various aspects of spatial ability outlined in Table 1. The 3DAT addresses all the skills emphasised in traditional training in design and engineering fields, such as understanding of different types of projections, the concept of true length, folding and unfolding, and the properties of coordinate systems. In essence, the items are matching, recognition, and visualisation tasks requiring varying forms of spatial ability. The final version of the 3DAT will consist of groups of test items called subtests that represent different components of spatial ability relevant to engineering and design-based disciplines.
Current Study A study was conducted with first year design students. The engineering fields represented in the sample included Mechatronics, Mechanical Engineering, and Chemical Engineering. The creative design fields included Architecture, Construction Management and Design and Technology (D&T) Education. The study was aimed at profiling the spatial ability of the groups with a further aim of examining the spatial abilities of the engineering students in consideration with other design disciplines. If the 3DAT test identifies a significant difference in performance of the engineering students this may raise some issues for design education in secondary schools. An opportunity was also taken in this study to examine differences in gender performance across both groups: engineering and creative. The literature constantly refers to gender bias favouring males for visualisation tasks. It was always intended that the final version of the 3DAT would identify where training was needed to bring about visualisation improvement for poor performers and female students. The study was computer-based and tested 6 spatial subtests consisting of 6 test items each and measured choice accuracy and RT. The subtests were a combination of tasks that researchers elected to re-test with students having prior learning experience, and tasks that were being trialled for the first time. For tasks previously used, the degree of difficulty was increased. The six subtests were named: mental rotation (MR), visualisation (VZ), dot coordinate (DC), mental cutting (MC), fold unfold (FU) and true length (TL). The subtests were varied in design which would help identify differing components of spatial
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Williams, Sutton, & Allen. Spatial Ability: Issues Associated with Engineering and Gender
ability if they existed in this research. The study had ethics approval to be conducted in normal tutorial classes because of the educational value to participating students. They received a rationale for the study, an explanation of its relevance to their curriculum, and the opportunity to calculate their performance overall and for each of the subtests. The sample consisted of 114 participants (68 engineers and 46 creative) and of these 87 were male and 27 were female.
Results Since there were six test items for each of the six subtests, the maximum score possible on each subtest was six. Figure 1 shows the plot of mean scores for each group of participants. Clearly shown is the consistently better performance for the engineer group in comparison to the creative group. The performance across all subtests was statistically significant (t (112) = 4.37, p = .000) in favour of engineers. However, when each subtest is considered individually, only DC and MR task are significant (t (112) = 7.47, p = .000 and t (112) = 2.52, p = .013 respectively) with VZ trending towards significance. Most notable was the subtest DC with an effect size (practical significance) of 1.4 which is well above the criteria for large effect (low = 0.2, medium = 0.4, large = 0.8). In comparison, effect size for MR was 0.47 and for VZ, it was 0.30. A review of the remaining subtests (MC, FU and TL) indicated that many test items failed to discriminate and were near ceiling for degree of difficulty. However, the results are encouraging since they support the hypothesis that engineers will do better on tasks that target their spatial attributes. In other words, the results go some way towards establishing predictive validity which is a requirement of psychometric test development.
Figure 1: Plot visualisation tasks for engineering and other participants.
Relationship of Spatial Ability to UAI The tests were conducted with the range of students and the analysis conducted to consider if the performance of the groups differed significantly. Analysis does not provide conclusive evidence that there was a significant interaction between subtests and student University Admission Scores (UAI). Results are shown in Figure 2.
Figure 2: Plot of mean correct for subtests showing UAI as a factor.
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Williams, Sutton, & Allen. Spatial Ability: Issues Associated with Engineering and Gender
What is indicated in these results are: 1. The trend is generally as UAI increases, so does performance. Though interaction is only significant for UAI = 91 to 100, therefore the trend is upward and should only be considered a trend. 2. What is indicated in the data in that there were very few scores if any below 3 meaning very little spread in the results. 3. The results indicate that UAI probably matters, but the results are still not absolutely conclusive. 4. What is shown is that the higher UAI students did perform better at the tasks done less well by the group, or what could be considered the “harder” tasks or problems, the Dot Coordinate task being the best example of this situation. What is evident in the results when considering the relationship between UAI and success is only retesting with all subtests being made more difficult would answer this question with any certainty.
Gender The third issue identified in this study relates to gender bias with spatial abilities. As reported above there is evidence from previous research that there is a bias favouring males in relation to spatial abilities. This study aligns with these findings, clearly shown in Figure 3. The plot in Figure 3 shows mean correct scores for male and female participants across the total sample. Female performance is consistently below that of males on all subtests reaching statistical significance on all subtests except TL. Accordingly, statistical significance can be reported across subtests when considered collectively (t (112) = 4.74, p = .000). Noteworthy again is subtest DC with a high effect size of 0.99. Unfortunately, these results support the literature that provides evidence of gender bias favouring males. Ideally, it would be good to be reporting a trend in the opposite direction where females were moving closer to the performance levels of males on visualisation tasks. However, the sample size for females was small in comparison which may have some implications for these findings.
MEAN CORRECT
6
5
4 Male Female 3
2 MR
VZ
DC
MC
FU
TL
SUBTESTS
Figure 3: Plot of mean correct and standard error on visualisation tasks for male and female participants. From the analysis conducted, female performance is shown to be consistently below that of males on all subtests achieving statistical significance on all subtests except TL. D&T teachers in schools need to be aware of this situation as the success of their teaching in a range of design issues would be inhibited by the ability of the female students, in the class, being able to understand the spatial components of the problems. This would be most evident in technical drawing classes or in classes where there is a need to understand the relationship of objects or components to each other. Females would be disadvantaged in such classes and would potentially receive lower marks in the classes with this situation leading to avoidance of the types of subjects that require these skills. Historically this has been the situation with lower female participation in careers in engineering. This is not always the case as with such careers as interior design where females make up the larger percentage of the population. An examination of the issues confronting such disciplines as engineering identify that there is very low female students and therefore low participation rates in the professions.
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Williams, Sutton, & Allen. Spatial Ability: Issues Associated with Engineering and Gender
Conclusion What can be established is that a student with a high UAI entry score may not necessarily have a high level of spatial ability. Also there is a need to acknowledge that female students may not have the same spatial ability skills as their male counterparts. When establishing first years learning sequences it may be important for the programme designers to be conscious of these facts and provide further support. These finding support the need for the development of strategies to support spatial skills in design based programmes.
References Adanez, G. P., & Velasco, A. D. (2002). Predicting academic success of engineering students in technical drawing from visualisation test scores. Journal of Geometry and Graphics, 6(1), 99-109. Allahyar, M., & Hunt, E. (2003). The assessment of spatial orientation using virtual reality techniques. International Journal of Testing, 3(3), 263-275. Akasah, Z. A., & Alias, M. (2006, December). Bridging the spatial visualisation skills gap through engineering drawing using the whole-to-parts approach. Paper presented at the 17th Australasian Association of Engineering Education Conference (AAEE06), Auckland University of Technology, New Zealand Blasko, D. G., Holliday-Darr, K., Mace, D., & Blasko-Drabik, H. (2004). VIZ: The visualization assessment and training website. Behavior Research Methods, Instruments, & Computers, 36(2), 256-260. Kellogg, R. T. (1995). Cognitive Psychology. Thousand Oaks, CA: Sage Publications Inc. Kosslyn, S. M., Chabris, C. F., Marsolek, C. J., & Koeing, O. (1992). Categorical versus coordinate spatial relations: Computational analyses and computer simulations. Journal of Experimental Psychology: Human Perception and Performance, 18(2), 562-577. Maier, P. H. (1998). Spatial geometry and spatial ability: How to make solid geometry solid? In E. CohorsFresenborg, K. Reiss, G. Toener, & H.-G Weigand (Eds.), Selected papers from the Annual Conference of Didactics of Mathematics 1996, Osnabreck, 63-75. McGee, M. G. (1979). Human spatial abilities: Sources of sex differences. New York, NY: Praeger Publishers. Nagy-Kondor, R. (2007). Spatial ability of engineering students. Annales Mathematicae et Informatica, 34, 113122. Olkun, S. (2003, April). Making connections: Improving spatial abilities with engineering drawing activities. International Journal of Mathematics Teaching and Learning. Retrieved January 16, 2008, from http://www.cimt.plymouth.ac.uk/journal/sinanolkun.pdf Sorby, S. (2006). Developing 3-D spatial skills for engineering students. Paper presented at the Australasian Association of Engineering Education Conference, Auckland University of Technology, New Zealand. Sutton, K., Heathcote, A., & Bore, M. (2005). Implementing a web-based measurement of 3D understanding. Australian Computer-Human Interaction Special Interest Group Conference Canberra, Australia 2005. Sutton, K., & Williams, A. (2006). Impact of spatial ability on students doing graphics based courses. Paper presented at the Australasian Association of Engineering Education Conference, Auckland University of Technology, New Zealand. Sutton, K. J, & Williams, A. P. (2007). Spatial Cognition and its Implications for Design. International Association of Societies of Design Research, Hong Kong, China (2007). West, R. L., Morris, C. W., & Nichol, G. T. (1985). Spatial cognition on nonspatial tasks: Finding spatial knowledge when you’re not looking for it. In R. Cohen (Ed.), The development of spatial cognition. Hillsdale, NJ: Lawrence Erlbaum Associates. Copyright © 2008 A. Williams, K. Sutton, & R. Allen: The authors assign to AaeE and educational non-profit institutions a nonexclusive licence to use this document for personal use and in courses of instruction provided that the article is used in full and this copyright statement is reproduced. The authors also grant a non-exclusive licence to AaeE to publish this document in full on the World Wide Web (prime sites and mirrors) on CD-ROM and in printed form within the AaeE 2008 conference proceedings. Any other usage is prohibited without the express permission of the authors.
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