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Do Introductory CAD Courses Offered in Community Colleges Improve Student Spatial Visualization and Does the Student's Computer Self-Efficacy and Gender Play a Significant Role in the Course Grade?


The proposed study seeks to determine if CAD courses offered at community colleges improve student spatial ability and if the student’s computer self-efficacy and gender play a significant role in the course grade. Participants in the study will be given a pre-and post test ranking on the PSVT/VR test after being given the Compeau-Higgins Self-Efficacy Test which will determine if there is a significant correlation between the student’s perceived self-efficacy and real ability as measured by the PSVT/VR. Participants in the study are community college students enrolled in CAD courses. The CAD course is the treatment variable in this study, and scores on the pre-and post PSVT will be compared when the CAD course has been completed. Also examined are whether there is a gender difference in spatial/visual learning, and whether this difference is significant. The study is based on the work of Bandura, who developed the Social Cognitive Theory, and Howard Gardner, who identified spatial intelligence among his Multiple Intelligences Theory.


Student CAD Course

As building and design technologies continue to evolve, students and others who take CAD in college will be able increase their ability of spatial reasoning and intelligence This research is aimed at analyzing secondary data instrument of computer self-efficacy as well as Purdue Spatial Visualizations Tests/Visualization of Rotations PSVT/VR spatial reasoning to determine the extent of the relationship between the effects of CAD courses offered in college upon spatial intelligence, also the students’ computer self-efficacy will be examined to see if it has a significant relation to students’ CAD course grade.

An article by Strong and Smith in the Journal of Industrial Technology (2002) states that “[s]patial visualization or the ability to perform complex mental manipulation of objects has been established as a predictor of success in several technology related disciplines. The value of this ability and changes in technology warrant attentiveness to teaching, history, and trends related to spatial visualization.” This would increasingly include the technology disciplines themselves. The use of CAD and CAD-related programs, ever being refined, are crucial in the building and design industries, and those students who can successfully use these programs, as users or as designers, are well in demand in the industrial workplace.

Ferguson (2008) also discusses the need for improvement in the spatial-visual needs of students. Industry has called for better skill-sets from students graduating from technical programs, and interventions are needed in spatial-visual literacy in order to maximize student success. Computer use has changed the way industrial problems are solved, and there are many disciplines in which complex and sophisticated computer technologies come into play. In order to be able to use these technologies appropriately, students must have a fully-developed ability to manipulate data and information in a spatial/visual context (Ferguson 2).

Computer self-efficacy—the ability to competently use computers is a strong predictor of motivational and behavioral outcomes related to these computer technologies. (Liang, 2005). But research in both how humans use visualization in order to interact with technologies and in more comprehensive constructs of computer self-efficacy have not kept pace with the technologies themselves (Ferguson 1; Liang iii). Bandura (1986) developed a model for how humans interact with their environments. Called Social Cognitive Theory, it is based on the idea that environmental influences and human behavior are reciprocal, i.e, people choose environments as well as being influenced by them. This has a significant impact on the interactive process. According to the theory, individuals are more likely to engage in behaviors which they believe will have a positive outcome. Self-efficacy, the beliefs about one’s abilities to perform in a particular environment, influences choices about which behaviors to undertake (Compeau and Higgins 1995).

Problem Statement and Research Questions

Previous studies have pointed to the need for further research in how students best acquire spatial reasoning, the types of milieu in which it flourishes, and whether self-efficacy plays a critical role in spatial/visual improvement and whether it is gender-specific. The questions which this research attempts to answer are:

1) Do Introductory CAD courses offered in community colleges improve student spatial ability and does the student's computer self-efficacy and gender play a significant role in the course grade?

2) Is self-efficacy a significant part of that improvement?

3) Is spatial improvement gender-specific?

4) Do CAD courses offer improvement, or is there some other factor which accounts for the improvement?

Literature Review

Basham (2007) reported that there is a difference in spatial ability on the method used to instruct students using the 3-D CADD modeling software. The method used concrete manipulation of objects along with computer visualization. Those students who had teacher assistance who used the introduction of software as a tool performed significantly better than their peers who had no such prior instruction. Basham concluded that working on a task with others allows for questions, clarification, social interaction, and replication of what others were doing. This led to the development of much more complex skills than a student would acquire on his/her own.

Stewart (2008) conducted a study examining computer self-efficacy and spatial visualization ability on student perceptions of 2D-3D CAD virtual simulations for apparel design. The sample of students studied were found to have above average confidence in their own computer skills; these students found the software easier to use than did those who did not have such confidence. In other measures, spatial ability in general did hot have an apparent influence on technology acceptance. Stewart concludes by saying that a tutorial combined with instructor assistance is more effective and meaningful for students using the software.

Another study, by Koch (2006), looked at the effects of solid modeling and visualization on solving technical problems. In this study, which asked students to solve design problems using solid models, as opposed to sketching or other means, it was found that visualization is a significant predictor of technical problem solving. There was no significant difference between solid modeling and sketching as a problem solving technique. Visualization is a better predictor of success than the method chosen to solve the problem. Using solid modeling software to design a solution did not ameliorate low visualization scores.

Onyancha et. al (2009) did a study to examine and determine optimal training methods to improve the spatial ability of students. The study involved students who were given a specialized spatial ability both before and after training or enrollment in a CAD course. The study showed that targeted training (the CAD course) resulted in a significant improvement in spatial ability scores and that the improvements occurred regardless of specific object geometries or rotation types. Students who chose not to take the course or training scored significantly lower than did the sample students. The most significant score differential occurred with questions which were more difficult to answer at the beginning of training.

Scribner (2004) conducted a study of novice drafters and the influence of instructional methods and learner styles. She used the Purdue Spatial Visualization Test (PSVT) and the Perceptual Modality Preference Survey v 1.1 to determine which was more significant, spatial ability to recognize 3-D objects and 2-D representations was more a function of instructional method or learning style. She found no significant statistical difference between spatial ability and instructional method, but did find a significant difference between spatial ability and learning style and also spatial ability and prior instruction.

Sutton and Williams (2007) reviewed several studies that looked at outcomes which supported learning in spatial ability. The study examined performance on a number of spatial cognition tasks that are deemed important to designers. These results helped to validate a psychometric test designed to measure spatial concepts involved in graphical communication. The researchers concluded that the traditional approach to learning be replaced by active learning using interactive computer models that allow the students to control manipulations of shapes.

Eraso (2007) conducted an extensive study that examined the connection between visual and analytic reasoning. His research hypothesis was that connecting these two types of reasoning might result in an improvement in spatial visualization abilities which would not be likely when that connection isn’t made. Again, the PSVT was used both as a pre- and post-test. The results showed significant differences in gender, with males below the 50th percentile on the pretest making the greatest gains, while girls were significantly more sophisticated on three dimensional visual/analytic processing strategies. The author recommends that spatial-visualization training begin much earlier in a student’s life, as early as the middle grades.

Kraft (2001) did a survey of traditional industrial arts educators to determine their perceptions if IA programs and whether they believe that traditional methods of teaching IA and if those methods still have value. The findings indicated that technology instructors support for the traditional industrial arts is still relevant and perceive as important, and that traditional methods have a place in contemporary industrial arts education.

Albert Bandura (1977) developed a theory which ascribed behavior in terms of self-efficacy, or a person’s coping behavior and confidence in the personal outcome of such coping behavior. Self-efficacy, according to Bandura, is derived from four principal sources of information: 1) performance accomplishments, 2) vicarious experience, 3) verbal persuasion, and 4) physiological states. The self-efficacious person is one who is confident in his or her abilities, feels at ease in an environment where success has been experienced, and is more likely to take risks in such an environment. Self-efficacy has a positive correlation with success and perceptions of success.

Conceptual Framework

Bandura’s Social Cognition Theory and concepts of self-efficacy are important and germane to any discussion of student achievement. Given the need for industries to have a pool of fully skilled engineers, designers and others who have computer abilities with spatial and visualization acuity available to them, it begs the question of whether students ought to learn these skills in college courses. It goes without saying that such an educated pool is the main responsibility of colleges and community colleges. The point, and the subject of this study, is to determine the best way of preparing these students so that they are ready to enter the workforce upon graduation without further technical education, and which students are most prepared and by which means.

Bandura’s ideas of self-efficacy encompass several other ideas pertinent to this discussion: the environment in which students will find themselves, their confidence and comfort level with their own abilities, and the influences of others around them. The research is fairly clear that without teacher assistance or other preparation, students do not do as well as with these aids; the opportunities to observe, evaluate, and interact with others seems to be a critical point in learning computer skills. The question remains in what setting this is most appropriate, at what age is learning acquired most easily, and whether gender plays a significant role in learning.

The current research relies on Bandura’s ideas as a basis for learning spatial and visualization skills in the classroom. Those who have competence in computer use should perform better than their peers on a pretest which measures such skills. In accordance with results found in other studies, treatments with teacher assistance or other ways of familiarizing students with software which will measure their skills, interaction with models and with problem solving activities, and time for reflection with others ought to close the skill gap as measured by the test. At the end of the training, a significant number of students should be at a passing level. It is the purpose of this study to determine such things.

Howard Gardner (1983) conceived of and developed a theory of multiple intelligences. According to Gardner, intelligence is not one global aspect of a human being, but rather a set of abilities that are disparate and unique as compared with the others. One of these intelligences which he identified was spatial intelligences, the ability to manipulate pictures in the mind. This idea has a significant impact on this study. Self-efficacy as related to computer use, which is largely a visual medium, may be a byproduct of spatial intelligence, and those who perform well on measures such as the PSVT/VR may be those who would score well on spatial intelligence scales and who would be attracted to coursework and careers that emphasized spatial/visual skills.


Relevant hypotheses are:

1) CAD courses offered in community colleges do not significantly improve student spatial abilities. Alternative: CAD courses offered in community colleges significantly improve student spatial abilities.

2)Self-efficacy as measured by the Compeau-Higgins Self-Efficacy Test is not a significant part of spatial/visual improvement? Alternative: Self-efficacy as measured by the Compeau-Higgins Self-Efficacy Test is a significant part of spatial visual improvement.

3) There is no significant difference in spatial improvement as measured by the PSVT/VR between male and female students. Alternative: There is a significant difference in spatial improvement as measured by the PSVT/VR between male and female students.

4) The specific CAD course offered is not a significant factor in spatial/visualization improvement among community college students. Alternative: The specific CAD course offered to community college students is a significant factor in improving spatial/visual improvement.


The proposed study will examine whether or not the CAD course has any effect on the spatial ability/intelligence by using PSVT/VR instrument both at the beginning and end of the CAD course term. The control group will be a random study of students from the same college (s) not presently taking and have never taken CAD course. The control group will be subjected to same instrument PSVT/VR both at the beginning of their term and at the end of their term. Since the Strong and Smith article in 2002, it is certain that the trend they recognized has continued, and with increasing competition among colleges and universities for the best-equipped students, recent relevant data on this topic is necessary for intelligent decision-making. The study will analyze who was successful in CAD courses by studying the students’ term course grade. Since the spatial reasoning test that will be given at the beginning and end will show whether the CAD course had a significant impact on the students’ spatial reasoning abilities influence on their success.

Also administered will be the Compeau-Higgins Self-Efficacy Test (1995) which will measure each student’s own assessment of his or her abilities. These scores will then be compared with the derived scores on the PSVT/VR to determine if self-efficacy plays a significant role in spatial/visual improvement.

A study conducted by Glenn Gordon Smith (2001) looked at interaction in a computer-like situation to discern efficacy of student learning in visually-manipulative tasks in three different scenarios—students alone, students with consultants, or students with participating partners. There was a significant difference at the 0.05 level when students were paired with co-participants, while there was less success with students alone or with a consultant only. It appeared that non-constant repetition (trading off) had the greatest positive effect on developing spatial visualizing ability in these students. This ability to learn the use of manipulating objects in space is significant for students learning to use CAD programs. Should CAD courses include this kind of scenario within the course, student success seems much more likely.


It is proposed that participants in the study be community college and university students enrolled in CAD courses and the control group will be in the same college and university not taking the CAD course. Age of the student could be a mitigating factor at some level, and so there may need to be a provision for reducing sample size based on characteristics of familiarity of computer use among the older students. A sample size of between 60 to 80 students should be sufficient for this study for the treatment group. A control group will have about the same size of students. According to the Strong and Smith study, age, gender, experience and individual differences are factors in visual manipulative ability, so as mentioned above, some provision may need to be made to take their grade scores into account.


The dependent variable for this study will be the student’s spatial intelligence tested by the PSVT/VR instrument. The IV’s will be the introductory CAD course, student’s computer self-efficacy, and gender has any effect on the outcome. The control variable include that CAD course will be introductory course that must include a curriculum section on orthographic projection. The cut-off range for success will be considered to be at the 80% mark. Significance will be determined at the 0.05 level.

Limitations, Delimitations, Significance

The study is limited by the sample size of those who are participating. This will have an impact on the external validity of the study. There may also be a tenuous link between gender in the differences in scores obtained. Studies (see above) have been ambivalent about this, some showing that there is no difference, others showing a significant difference. These differences may be due to some other factor, such as prior educational experience or perceived role expectation.

There may also be a bias toward community college students. Community colleges are sometimes perceived as colleges students attend in order to prepare them for four-year colleges, suggesting that these students are intellectually incapable of succeeding at the college level, and that they would not, by association, make good engineering/design students.


Every effort will be made to ensure that all participants in the study are not identifiable.


Bandura, A. Self-efficacy: toward a unifying theory of behavioral change. Psychology Review, 1977, Vol 84, No 2, 191-215

Basham, K.L. (2007). The effects of 3-dimensional CADD modeling software on the development of spatial ability of ninth-grade technology discovery students. Dissertation, Louisiana State University.

Compeau, D.R. and Higgins, C.A. Computer self-efficacy: development of a measure and initial test. MIS Quarterly.

Eraso, M. (2007). Connecting visual and analytic reasoning to improve students spatial visualization abilities: a constructivist approach. Dissertation, Florida International University.

Ferguson, C.W. (2008). A comparison of instructional mthods for improving the spatial/visualization ability of freshman technology seminar students. Dissertation, Western Carolina University.

Gardner, Howard. Frames of Mind: The Theory of Multiple Intelligences. New York: Basic,1983 Koch, D.S. (2006). The effects of solid modeling and visualization on technical problem-solving. Dissertation, Virginia Polytechnic University.

Kraft, T.E. (2001). Technology educators’ perceptions of traditional industrial arts programs, purposes and projects. Dissertation, University of Nebraska.

Liang, X. (2005). Development and validation of a new computer self-efficacy scale for use in complex technology contexts. Dissertation, University at Albany, State University of New York.

Onyancha, R.M., Derov, M., and Kinsey, B.L. (2009). Improvements in spatial ability as a result of targeted training and computer-aided design software use: analysis of object geometries and rotation types. Journal of Engineering Education, April 2009.

Scribner, S.A. (2004). Novice drafters’ spatial visualization development: influence of instructional methods and individual learning styles. Dissertation, Southern Illinois University, Carbondale.

Smith. G.G. (2001). Interaction evokes reflection: learning efficiency in spatial visualization. Interactive Multimedia Electronic Journal of Computer Enhanced Learning.

Stewart, S. ((2008). Effects of computer self-efficacy and spatial visualization ability on student perceptions of 2D/3D CAD virtual prototype simulations for apparel design. Thesis, Iowa State University.

Strong, S. and Smith, R. (2002). Spatial visualization: fundamentals and trends in engineering graphics. Journal of Industrial Technology.

Sutton, K. and Williams, A. (2007). Research outcomes supporting learning in spatial ability. Proceedings of 2007 AaeE Conference, Melbourne.