Visualization in Technology Education:  Scientific and Technical Visualization Concepts and Ideas (STEM Education)

Dr. Aaron C. Clark
Department of Mathematics, Science, and Technology Education
NC State University, Raleigh, NC  27695

“Try out your ideas by visualizing them in action.”  David Seabury 

Visualization in Technology Education

Graphic Communications and the study of visualization has a long history in both technology and engineering education, with graphics (i.e. visualization) being employed as both the final outcome and the intermediate stag for numerous technological design activities (Sanders, 1997; Garner, 1993).  Articles discussing design and visualization in technology education are common themes among many of our professional journals and magazines.  Most of these articles define visualization as the process of abstract mental representations of human experiences, as they relate to some form of technology.  This can be in the form of creating virtual or physical models that are either two-dimensional (2D) or three-dimensional (3D) that encompass areas of engineering analysis, rendering, animation, virtual modeling and prototyping (Hall & Obregon, 2002).  But, is visualization for technology education more than just an abstract process that provides avenues for conveying information between phases of the engineering design process?  Visualization is not mental imagery, although using it effectively requires an ability to “see” how concepts and principles are associated.  The goal of visualization for technological areas including technology education is to be able to accurately and effectively communicate different types of information through the creation of graphic representations for a wide variety of audiences.  Using visualization for this specific purpose is often referred to in today’s academic and business worlds as “scientific and technical visualization” (Clark & Matthews, 2000).

Visualization in technology education is more that the teaching of mechanical and architectural computer-aided design (i.e. CAD), but a more broad approach designed to better communicate ideas and concepts through the use of a variety of powerful graphic tools, design concepts and integrated disciplinary practices.  Considering this thought, the ability to “breakdown” and problem solve and communicate these ideas and concepts are the main factors behind any definition for visualization as it relates to technology and technological literacy (Clark & Wiebe, 2000).  For example, the engineering design process focuses heavily on visual skills and capabilities.  Since the 1960’s, the engineering design process model has gone through many iterations and customizations for specific purposes, but all engineering design models have the following five phases that we as technology educators should consider to be principle elements for defining how visualization is to be distinct and taught in our technology education classrooms.  These phases are:  needs assessment- the need to define and establish a solution, problem formation- using good design techniques to help define what is the “real” problems associated with a task, synthesis- developing general concepts and alternative solutions, analysis- comparing and evaluating designs, and finally, implementation- developing and distributing the final solution (Voland, 2004).  These phases of the engineering design process can lead us into how we see and define visualization and the use of visualization in our curricula approaches.  Consider that if students can develop their visual skills and capabilities, as well as the ability to create and recreate concepts and ideas, that this is the main thrust for visualization in technology education.  This can be best demonstrated by having students know when, where, and how to create different types of visualizations in order to communicate information.  Figure 1 shows a model for the types of visualizations that technology education students can use to determine the best process and produce for communicating conceptual and data-driven models.

Figure 1:  Types of Visualization Models for Technology Education

Visualization in technology education can be best describe as a process, not the development of simple graphical representations.  The process should begin with students knowing the different fundamental types of models that can be created so that good communication can happen with the intended audience.  The creation of visualizations can be broken-down into two types of models for visualization.  The first is conceptual modeling.  Conceptual graphic models (such as the flow of fluids across a foil, visualization of scientific and technological phenomena, artifact or structure) permit one to demonstrate technological and scientific concepts and principles that normally which would be difficult or impossible to replicate with text, mathematical or spatial models.  Conceptual models are created when a topic or idea cannot be easy explained with words or in mathematics, but as a picture or animation to better communication the idea or process.  These conceptual models can be either 2D or 3D based upon the complexity of the topic.  Also, conceptual models are either static or dynamic, or better defined as either a picture (static) or an animation (dynamics) (See Figure 2).  An example of a conceptual-based topic would be the explanation of a chemical chain reaction.  We know that this takes place, but usually is not seen and therefore, harder to explain without the use of visualizations.  Another example of a conceptual model would be the topic of a human virus.  No one has ever seen a virus, but we know they exist, so a model can be created showing the designer intent for what the virus would look like in his or her interpretation (Wiebe, Clark, Petlick, & Ferzli, 2004).

Figure 2:  Examples of conceptual models from students (i.e. plant cells and wall insulation)

The second type of fundamental modeling or visualization creation that students in our technology education classrooms need to recognize and be able to create is called data-driven modeling.  Data-driven models use data sets to convey a large set of numerical information into a small comprise way that is easily understood.  The many different types of charts and graphs are used to show this type of information.  Data-driven models can also be either two-dimensional (2D) or three-dimensional (3D), based upon the number of independent variables to be shown within the visualization (See Figure 3).  An example of a data-driven model would be empirical data collected at a farm with different soil samples taken looking at Ph levels in the soil and a chart created to show all this information in an easily understood form.  Another example would be the creation of bar charts to show information collected from the last census and explaining that large amount of information with these simplified charts.  Whether the visualization is conceptual or data-driven, students need to know the fundamentals of how best to show the type of information they are given as a problem, and then develop a model and present it well to the intended audience using the appropriate techniques, this is role visualization has in the discipline of technology education (Clark & Wiebe, 2000).

Figure 3:  Examples of data-driven models from students (i.e. monthly temperature ranges and radiation comparisons)

Meeting Standards for Technological Literacy

With the recent release of the Standards for Technological Literacy (STL), the need for America’s students to develop a deeper knowledge of the nature, creation, and potentials of technology and its symbiotic role in human society, as well as develop a broader range of technological skills (ITEA, 2000) has never been more apparent.  Although many people in the general population still see technology as computers, it is the belief among many professionals in technology education that most of these same people also see computers and communications as being the one of the same (Newberry, 2001).  Visualization, or as defined generally in this paper as communications, can help bridge this gap between what technological literacy really is, and what society says or sees it as.  Visualization is easily seen in our communications system courses as well as in our fundamental courses for technology education throughout the United States.  In North Carolina for example, 80% of all students taught each year are in a communications related course therefore, communications and visualization are key for technology-based curricula (Personal Communications with Thomas Shown on October 26, 2005). 

The role of visualization can easily be seen in the STLs.  Most predominate are standards eight through eleven that state that students will understand the attributes of design, engineering design, and the role of problem-solving and other forms of critical thinking skills.  Standard 11 directly indicates that students are to apply the design process (Dugger & Naik, 2001).  Traditionally, these standards rely upon visual-based means to convey the idea and concept, but what about the design worlds?  What about those design world standards that many in technology education were not familiar with (i.e. biotechnology and medical) or have even dealt with in a state curriculum in our field?  How can visualization help with the understanding of these technologies that seem to rely on scientific concepts for understanding as much as they do technology?  Lets look at these two design world standards to see how visualization can help with the implementation into existing technology education classrooms and meet these two standards for biotechnology and medical technology (www.ncsu.edu/viste).

While many educators utilize technology such as computers, projectors and calculators in the classroom, far fewer recognize that technology is also the machinery behind science, that which facilitates discovery and application.  In fact, never before has science and technology been so intertwined (Friedman & diSessa, 1999). Biotechnology, one of our design world standards, provides one example of the merging of science and technology.  Key biotechnology such as the Polymerase Chain Reaction (PCR)—a technique used for copying segments of DNA material builds on an already existing biological system, which can then be manipulated and modified through the use of technology.  Use of this technology has become a revolutionary tool for modern molecular biologists as well as for laboratory technicians to visually see the type of data they are working with and creating (See Figure 4).  In the area of medical technology, creating new innovations in medical areas through the creation of visualizations can be yet another way to teach this standard.  Whether its designing a new medical pump for certain situations or simulating a new internal or external prosthesis, this merging of science and technology has never been more important as we teach students the technology behind emerging scientific developments (See Figure 4). In order to address the need for students to learn about technology used in the sciences, educators can use simple and complex 2D and 3D graphic visualization tools to delve into cutting-edge technology and integrate technological design to meet these standards, as well as other design world standards.  It is the belief of some professionals in technology education and graphic communications areas that effective use of technical and scientific graphic communication promotes higher order thinking and requires students to master sophisticated computer-based technologies. The result is a deeper understanding of the underlying principles involved in the creation and manipulation of graphics and of the concept or data for which they are communicating about and in return, become technological literate citizens.  Visualization plays a key role in science for communicating scientific findings in a graphical format.  Being able to communicate is the key and is at the heart of literacy – scientific or technological (Clark & Wiebe, 2000). 

Figure 4:  Student examples of the PCR process and external prosthesis

Teaching Visualization in the Technology Education Classroom

Rapid advances in computer graphics technology in the 1980’s led to a new area of graphic visualization (McCormick, Defanti, & Brown, 1987).  While first largely confined to expensive, specialized workstations, these graphic tools diversified in terms of function and cost such that powerful graphics tools became available ordinary desktop computers by the early 1990’s. During this time period numerous technology education initiatives began exploring the use of these technologies in their curriculum. These trends in technology education and scientific visualization converged with the creation of a new curriculum in North Carolina specifically focused on the adoption of scientific visualization within the technology education framework (Clark & Wiebe, 2000; Wiebe, Clark, & Hasse, 2001).  In 2002, the National Science Foundation funded an instructional materials development project title Visualization in Technology Education (VisTE).  The VisTE Project (NSF grant #ESI-0137811) is standards-based STL (ITEA Standards for Technological Literacy) and designed to promote the use of higher order thinking and communication skills and the understanding of technology, mathematics, and science through the use of graphic visualization tools. High school and middle school students use simple and complex visualization tools, conduct research, analyze, solve problems, and communicate major topics identified in the STLs. Twelve discreet units reflecting the twenty STL standards have students engaged in activities such as aerospace engineering design, biotechnology, medical technology and the research and development of products, structures, and devices among others.  Each unit contains a matrix indicating the alignment of the material to the standards (STL’s) as well as teaching strategies and learning goals and objectives (Wiebe, Clark, Petlick, & Ferzli, 2004).  Figure 5 illustrates the STL’s that are targeted in the Medical Technology Unit, which focuses on the technology behind various medical imaging techniques.

Figure 5:  VisTE unit on medical technology and the alignment of the projects to the Standards for Technological Literacy

VisTE materials are organized as stand alone units that include introductory, intermediate and advanced level activities with a slight teacher-centered approach for the introductory level and a shift to a more student-centered approach for the advanced level (See Figure 6). Each unit also contains a project that focuses on the relationship between science, technology and society. Projects utilize the “design brief” approach which presents the

Figure 6:  Organization of instruction for VisTE Units

problem of communicating about a technical or scientific topic using visualization tools.  VisTE promotes scientific and technological literacy by having students design either data-driven or concept-driven 2D and 3D visualizations as previously discussed in this paper.  The problem solving, design and creation processes can be undertaken individually or as a collaborative effort.  Problem solving requires the students to take scientific and technical ideas and transform them into a graphical representation that can effectively and appropriately communicate to the target audience.  Previous research has demonstrated that the process of creating a visual representation of a science concept can often bring forth knowledge gaps that students were seemingly unaware (Wiebe, 1992; Clark & Wiebe, 2000; Wiebe, Clark, & Hasse, 2001; NC-DPI, 2000).  Such an experience within the context of problem solving acts as an effective motivator for students to seek out the missing knowledge. 

One goal of the VisTE curriculum is to attract a more diverse audience of students to technology education.  An attractive aspect of VisTE is that the projects allow science and technology concepts to be expressed and represented in formats other than the traditional written and verbal.  One way VisTE does this is by emphasizing the interplay of society and technology. VisTE brings in current controversial issues which have the potential to peak students’ interests and so promote the learning of science and technology in students who otherwise are unmotivated or unsupported by the more traditional curricula.  To date, the VisTE project has completed all of the 12 units.  Teacher’s Guides, background materials, resources, design briefs and evaluation rubrics are provided for each unit and supports all project levels within each unit from introductory level to advanced (Wiebe, Clark, Petlick, & Ferzli, 2004).  Table 1 shows the title and description for each of the VisTE units.

The VisTE project links to a number of different national and international trends in technology education (Black, 1998; Booth, 1989).  The curriculum embraces a belief of engaging students in an authentic practice, primarily with tools and techniques that would be used by engineers, technologists, and scientists. In doing so, it maintains a strong emphasis on new and emerging information technologies (Barlex & Pitt, 2001). While graphics are as old as human civilization, the emphasis in the curriculum is on new and emerging computer graphic tools and techniques. The curriculum was developed from the standpoint that the interrelationship of science and technology in these areas argued for the integration of content from both subject areas and that the process of developing visualizations can facilitate this integrated process of learning.  The VisTE project continued to build on this tradition, but responded to a number of emerging areas within technology education. First was the continued evolution and maturing of the design and technology curriculum in the UK (McCormick, 1993) and second was the development of national standards for technological literacy (ITEA, 1996; ITEA, 2000).  Influenced by both these movements, the VisTE project decided to place an increased focus on design and problem-solving as vehicles for exploring issues in technology and science, including the design of graphic communications. Similarly was the importance of putting these problem-based activities in the context of real-world issues and problems. That is, that the context in which solutions are explored responds to real-world constraints and reflects on both the historical and future impact of these technologies on society.

Table 1:  VisTE Units

Visualization:  The Catalyst for Integrating Science and Emerging Technologies

Areas of study within VisTE surround the use of science as the topic to create and develop good visualizations to better explain a given topic.  By the creation of these visualizations, students will learn to use different types of computer software that will someday be useful as they select a career path.  Also, areas within computer science, technology, mathematics, and communication will be enhanced as they learn to communicate to a variety of audiences.  Students are not only developing good visualization skills, but at the same time learning useful information and gaining skill sets what will make them a better communicator and presenter.  The overall design of VisTE materials is to link technology literacy standards to areas within scientific literacy, visual and spatial literacy, through the understanding and development of knowledge and skills in scientific and technical visualization (See Figure 6) (Wiebe, Clark, Petlick, & Ferzli, 2004).

Figure 6.  Linking VisTE to other areas of literacy

In conclusion, VisTE units are designed to enhance student’s knowledge in science, develop good visual and presentation skills, understand emerging technologies, and most of all help with the integration of standards that promote technological literacy.  Considering that technological changes are increasing in rate and impact and therefore, more than in any other discipline, technology educators are constantly challenged with providing instruction on technologies that are new and ever changing.  Meeting these challenges requires technology educators to master new material on topics they may have never received training on themselves, and also to develop instructional practices that facilitate students’ learning of emerging technologies in ways that promote technological literacy (www.ncsu.edu/viste).

References

Barlex, D., & Pitt, J. (2001). Interaction: The relationship between science and design and technology in the secondary school curriculum (Part 1) (report): Engineering Council and the Engineering Employee's Federation (EEF), UK.

Black, P. (1998). An international overview of curricular approaches and models in technology education. Journal of Technology Studies(Winter-Spring), 24-30.
Booth, B. (1989). The development of technology education in the United States. Studies in Design Education Craft and Technology, 21(2), 84-89.

Clark, A. C., & Matthews, B. (2000).  Scientific and Technical Visualization: A New Course Offering that Integrates Mathematics, Science and Technology.  Journal of Geometry and Graphics, 4(1), 89-98.

Clark, Aaron and Wiebe, Eric  (2000).  “Scientific Visualization for Secondary and Post-Secondary Schools,” Journal of Technology Studies, 26(1), 24-30.

Dugger, W. E., & Naik, N. (Sept. 2001).  Clarifying Misconceptions between Technology Education and Educational Technology.  The Technology Teacher, pg. 31-35.

Friedman, J. S., & diSessa, A. A. (1999). What students should know about technology: The case of scientific visualization. Journal of Science Education and Technology, 8(3), 175-195.

Garner, S. W. (1993). The importance of graphic modeling in design activity. In R. McCormick, P. Murphy & M. Harrison (Eds.), Teaching and learning technology (pp. 188-193). Wokingham, England ; Reading, Mass.: Addison-Wesley/Open University Press.
Hall, K. W., & Obregon, R. (April 2002).  Applications and Tools for Design and Visualization.  The Technology Teacher, pg. 7-11.

ITEA, I. T. E. A. (1996). Technology for All Americans:  A rationale and structure for the study of technology. Reston, Virginia: ITEA.

ITEA, I. T. E. A. (2000). Standards for technological literacy: Content for the study of technology. Reston, VA: ITEA.

McCormick, B. H., Defanti, T. A., & Brown, M. D. (1987). Visualization in scientific computing. (ACM) Computer Graphics, 21(6).

McCormick, R. (1993). Technology education proposals in the USA. In R. McCormick, P. Murphy & M. Harrison (Eds.), Teaching and learning technology (pp. 39-48). Wokingham, England ; Reading, Mass.: Addison-Wesley/Open University Press.

NC-DPI, NC State Department of Public Instruction. (2000). Scientific and technical visualization I (Curriculum T&I 7922): State of North Carolina.

Newberry, P. B.  (Sept. 2001).  Technology Education in the U.S.:  A Status Report.  The Technology Teacher, pg. 8-12.

Sanders, M. E. (1997). Communication technology: Today and tomorrow (2nd ed.). Mission Hills, CA: Glencoe/McGraw Hills Publishing Co.

Voland, G. (2004).  Engineering by Design, 2 ed., Pearson Prentice Hall, NJ.

Wiebe, E. N. (1992). Scientific visualization: An experimental introductory course for scientific and engineering students. Engineering Design Graphics Journal, 56(1), 39-44.

Wiebe, E. N., Clark, A. C., & Hasse, E. V. (2001). Scientific Visualization: Linking science and technology education through graphic communications. The Journal of Design and Technology Education, 6(1), 40-47.

Wiebe, E. N., Clark, A. C., Petlick, J., & Ferzli, M.  (2004).  VisTE:  Visualization for Technology Education; An Outreach Program for Engineering Graphics Education.  Proceedings of the 2004 American Society for Engineering Education Annual Conference & Exposition, session 3138.

Aaron C. Clark

Aaron C. Clark is an Associate Professor of Graphic Communications at North Carolina State University in Raleigh.  He received his B.S. and M.S. in Technology and Technology Education from East Tennessee State University.  He earned his doctoral degree from NC State University.  His teaching specialty is in engineering graphics and design, with emphasis in 3-D modeling and animation.  Research areas include graphics education and scientific/technical visualization.  He presents and publishes in both vocational/technology education and engineering education.  Dr. Clark is the Principle Investigator for the VisTE:  Visualization in Technology Education Program and Co-PI for the STEM-Community College Grant, both are National Science Foundation Grants.