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Engineering Educational Design

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ISDDE all rights reserved E DUCATIONAL DESIGNER JOURNAL OF THE INTERNATIONAL SOCIETY FOR DESIGN AND DEVELOPMENT IN EDUCATION Engineering Educational Design Christian Schunn University of Pittsburgh
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ISDDE all rights reserved E DUCATIONAL DESIGNER JOURNAL OF THE INTERNATIONAL SOCIETY FOR DESIGN AND DEVELOPMENT IN EDUCATION Engineering Educational Design Christian Schunn University of Pittsburgh Abstract Various analogies have been applied to educational research, the most prominent current one being medical clinical trials. What about the design and development of educational materials? There are many design principles being developed for educational materials, but the process of design is much less codified or systematic. By contrast, engineering as a discipline has created very systematic processes for doing design work, whether the design of products, processes, systems, or services, similar to the systematic scientific processes that are applied across the sciences. This paper overviews major findings from the study of engineering design practices and then presents an analysis of the extent to which engineering design processes may and may not be usefully applied to the process of educational design. Design as a Verb Design as a verb is the process of going from initial ideas to a fully realized product. It is sometimes referred to as design and development, but is sometimes abbreviated with just the term design. The term educational design is typically concerned with design as a noun (e.g., Davis & Krajcik, 2005) that is with the thing being produced, be it a unit of study, an assessment, a whole curriculum, a professional development workshop, an educational building, or some combination of these products into a larger system. In attending to the products themselves, much attention is given to relatively general design elements that should be contained in a good design (e.g., a good design should help teachers recognize and build upon conceptual diversity in student thinking). The discussion of good design elements sometimes focuses on particular subsystems of the larger product (e.g., assessment, lecturing within a curriculum), but also on principles and values that cut across subsystems (e.g., scaffolding as a principle and critical thinking as a value). However, just as the word design has two main meanings (as a noun and as a verb), so too does educational design. To further unpack the verb meaning, consider the verb definitions of design from Marriam-Webster ( Design, 2008): 1. To create, fashion, execute, or construct according to plan. 2. To conceive and plan out in the mind. 3. To indicate with a distinctive mark, sign, or name. 4. To make a drawing, pattern, or sketch of. The first meaning highlights the planful nature of designing there is system to the madness. The second meaning highlights the important mental activities of the designer(s). The third meaning is archaic and perhaps less relevant; however, design is very ego-involving and the designer often tries to bring a distinctive mark to the project. The fourth meaning highlights that the process of design is often focused on creation/manipulation of prototypes of the final product rather than directly on the final product itself. None of these meanings of design as a verb reveal much about the subcomponents of design as an activity: Does a design process have meaningful steps along the way, and is there a sensible organization to these steps? It is likely that design is not further unpacked in the definition for two reasons. First, people generally do not have good direct access to or awareness of mental processes that they follow even when there is strong regularity and organization to their behavior (Anderson, Page 1 Lebiere, & Lovett, 1998). Second, it may be very difficult to find components that are true of all designing, across the range of things that can be designed and the range of quality of designers. However, despite our inability to fully and directly reflect on design processes, and despite the likely variety of design processes that occur, I would like to submit that there is great value in thinking more rigorously about design processes. In all areas of human activity, processes that people follow have a great influence on both the quality of products that are produced and the speed with which the products are produced (Ericsson & Charness, 1994). Further, there are very large individual differences (Hayes, 1985; Simonton, 1997): some individuals regularly produce high quality products quickly and others take a long time to produce very mediocre products at best. Because these individual differences repeat across instances, there must be something reliably different about the processes being followed (rather than just stochastic strokes of good or bad luck). If we are to generally improve the quality and time-to-completion of designs, we must find out what better designers are doing and transfer those practices to weaker designers. Why Educational Design Should Consider The Analogy To Engineering Design How do educational designers develop their expertise? The lack of scholarship on the process of educational design suggests that it is primarily a craft-based kind of expertise. That is, it is likely that educational designers develop their process expertise through trial-and-error and through apprenticing with other educational designers. Disciplinary education (e.g., education in mathematics, physics, composition, etc.) pays little attention to educational issues and no attention to the design of educational objects. Some books on the educational design process exist and are popular (e.g., Wiggins & McTighe, 2005), but the research base underlying the content of those books is not clear. Schools of education rarely offer courses on educational design, and when they do, the content is craft-based knowledge and sometimes the focus is on design as a noun what makes for a good or bad product rather than a process that leads to good products. Craft-based performance can be very good. Or said another way, some people can become amazing performers through apprenticeship or craft-based education. However, it is not a very efficient process of training the lessons learned by one artisan travel very slowly to other artisans within the same organization and perhaps not at all to artisans in other organizations. As an extreme example, chicken sexing used to be treated in an apprenticeship fashion and required many years to develop the ability to reliably determine visually the sex of a chick. However, through explicit instruction regarding the process used by experts, that same high level of skill can be obtained in less than a day of instruction and practice (Biederman & Shiffrar, 1987). In contrast to the lack of scholarship and formal education on educational design processes, there is considerable scholarship and formal education on engineering design processes: there are undergraduate and graduate courses on engineering design, there are textbooks that support these courses (e.g., popular offerings include The Mechanical Design Process (Ullman, 2003), Product Design (Otto & Wood, 2001), Product Design and Development (Ulrich & Eppinger, 2008), and the Design of Things to Come (Vogel, Cagan, & Boatwright, 2005)), and there are journals in which scholarship on design processes is published (e.g., Journal of Engineering Design, Journal of Mechanical Design, Design Studies, and Journal of Research in Engineering Design). Thus, engineering design is a rich model to examine for improving scholarship and practice in educational design. Clearly engineering products and educational products have differences and thus the processes of engineering design and educational design are also likely to have differences. However, there are also many similarities between engineering products and educational products, and thus the differences in effective design processes may not be so large. For example, in both settings the products are usually complex systems (with multiple, complex interacting subsystems) being designed for competing constraints (i.e., cannot all be perfectly met in one design) to be used by a range of users Page 2 (whose requirements are not well understood or entirely fixed in advance), and whose design requires bringing together expertise from a variety of disciplines. Further, engineering covers a very wide ranged of designed objects products (e.g., ipods), processes (e.g., a more efficient way of manufacturing a given chemical or scheduling flights within a network of cities), complex systems (e.g., an office building or a space shuttle), or services (e.g., an offshore call center). Design processes of relevance to that range of designed objects will likely transfer to at least a range of educational design. This paper describes some major lessons learned in the scholarship on engineering design processes and explores the mapping of these lessons to education. I have contributed to that scholarship on engineering design and have led the design of educational products in science education, writing education, and math education. The mapping exercise in this paper is heavily influenced by those experiences, and in-depth linked examples from these experiences are provided to help make more concrete the way in which these engineering processes might be realized in educational design. Why Design Process Has a Large Influence on Design Outcomes I begin with an abstract analysis of why the design process can have such a large influence on the success of design outcomes. There are two related factors to consider. The first factor is an analysis of costs and flexibility of design change. Early on in the design process, there is great flexibility in the possible designs that can be pursued there is relatively little design time or monetary cost in changing design concepts early on. However, as time goes on, as particular design concepts are developed in more detail and with increasing amounts of lab testing, field testing, marketing, and creation of production facilities, the cost of changing the fundamental design concepts becomes overwhelming (see Figure 1). Thus, it is extremely important to generate and select a good design concept relatively early on in the process committing to weak choices through an ineffective design process can have disastrous consequences. Figure 1: Cost and ease of major design idea changes over time in the project. At the same time, the early design phase is fraught with uncertainty. The marketplace may change by the time the product is released and the underlying technology may need to be developed and thus is not yet fully understood. Even worse, the range of possible design concepts is impossibly large for the mind to fully consider it is very tempting to re-employ an existing design or pursue the first seemingly workable design that comes to mind. In sum, it is very important to do a good job in the early phases of design and it is very hard to do so. Scholarship on formal engineering design processes has paid considerable attention to improving conceptual design processes, facilitating more reliable decision making early in the process. Page 3 Processes That Have Been Shown To Be Important In Engineering Design Mehalik and Schunn (2006) reviewed the empirical literature on engineering design to determine which design processes were most reliably associated with expert designers / higher quality designs. Note the plural on processes. Just as science can be best characterized as a set of processes that come together in different ways in different situations (Chinn & Malhotra, 2002), design can also be best characterized as a set of processes that are used in varying combinations depending upon the situation. In fact, one of the hallmarks of good engineering design is using an iterative/interactive design process, rather than a simple linear process. Although the design process should be iterative/interactive, there is a rough ordering of steps. I discuss the other important processes in the rough order they would typically occur, including some mapping to the educational design context. Two of them (Develop a subsystem decomposition, and Develop analytic models), however, are complex big ideas that will be discussed in major sections of their own. Create Requirements & Metrics One big idea in educational design is to be clear about the learning goals in advance: what do you want students to know and be able to do (Wiggins & McTighe, 2005)? From the engineering design literature, we know that thinking about requirements like this is a good early step. However, thinking in terms of requirements more generally reveals that learning goals are just one element of the design goals that should be clearly specified at the beginning. Formally specifying all the requirements brings attention to the full range of dimensions that must influence the choice of designs, rather than allowing the designers to forget important factors (e.g., time to market or material costs or training costs). The specific requirements are developed by interviewing customers, analyzing the market place, and through expert input. That is, they are chosen carefully to reflect what dimensions are necessary for success, and thus can place important constraints on proposed designs. Possible additional factors that might relevant include: Is it important for design to be effective with teachers with relatively little content knowledge? Is the product meant to influence student identity (e.g., desire to become a scientist or engineer)? Also note that general requirements specified in vague terms are not helpful because different specifications can require substantially different designs. For example, is it important to do well on a particular kind of test, such as a state test that is essay-based or multiple-choice-based? Specifying the requirements in terms of specific values on particular metrics (e.g., a certain effect size of learning on a particular test) allows the design team to find possible solutions that are satisfycing (i.e., good enough on all dimensions). (See Appendix A) There are several common mistakes in putting together requirements for a design task. The first common mistake is giving a solution instead of a requirement. The requirements are about the ends that must be met (e.g., students must learn X) and the constraints on resources (e.g., material cost, development time, or amount of teacher professional development that can be assumed). Sometimes, however, the designer may mistakenly list a particular way of achieving those ends as part of the requirements. For example, a science unit must include a hands-on activity, or a math unit must include a particular kind of diagram. These are solutions. Although they may be good solutions to the actual design problem at hand, listing them as requirements prevents the designer from considering alternatives (including minor variations) that might prove to be more effective overall. The second common mistake is getting confused between absolutely necessary requirements (called must-have requirements) and useful but not actually necessary requirements (called nice-to-have requirements). Many widely used curricula become difficult for teachers to learn how to use because so many bonus features get added (e.g., each lesson can be enacted in very different ways, each requiring different instructions). One can think of this problem as having added too many Page 4 nice-to-have requirements while significantly weakening some must-have requirements (e.g., the requirement that most teachers are supported in focusing on big ideas, or the requirement that most teachers understand how to enact the curriculum with rigor). As a variation of this issue, requirements are specified with both minimal values and ideal values. In thinking about tradeoffs among alternative solutions, it is important to not give up on a minimal value on one dimension in order to obtain an ideal value on another dimension. For example, it would be a bad idea to change the duration of a curricular unit to a length of time that is simply not supportable by typical school districts even if it would improve learning to some more ideal level. Explore Alternatives Across a wide variety of design problems, one of the best predictors of success in design is the number of different designs that were considered, although considering too many possibilities without carefully exploring any of them is bad, too. Alternatives can be considered virtually/mentally or they can be explored empirically in prototype form. Exactly which form is best depends upon the accuracy of evaluations on the virtual/mental form and the time cost of the empirical tests in most areas of educational design, our theories and past experiences are not highly predictive, and thus some form of empirical testing is likely to be important. But regardless of format, multiple possibilities should be explored in the early phases of design before a main choice is selected. Further, these alternatives must be explored far enough that they can be evaluated in some way with respect to the key requirements, even if only through expert judgment of how well they are likely to meet the key requirements (See Appendix B). A controversial issue related to exploring multiple alternatives early in design is group brainstorming. The typical form of brainstorming involves generation in a group while judgment is suspended. The research literature has repeatedly found that this kind of brainstorming is very ineffective, most likely because the group tends to converge on shared ideas that are not necessarily good ideas. More effective is to allow some critical evaluation or, even better, to have individuals brainstorm alone, and then have the group critically evaluate the longer listed of collectively generated ideas (Paulus & Yang, 2000). Explore Problem Representation Developing a solution that is noticeably better than past solutions is a kind of insight problem. A common feature of insight problems is that there is a large space of alternatives and no clear feedback from virtual or empirical tests of each considered option on whether one is getting closer to or further from finding a significantly better solution (Perkins, 1994). Imagine digging for gold in a random spot, finding nothing, and then having no idea about which direction to search for a better digging location. In other words, one could search a long time and still not find something better. Rather than relying on luck in finding the needle-in-the-haystack through blind search, a much more effective method is to develop a more helpful representation of the problem that highlights where solutions are likely (and unlikely) to be (Kaplan & Simon, 1990; Lovett & Schunn, 1999). To develop this better representation, some heuristics are useful: 1) what do failures (or successes) tend to have in common?, and 2) can I discard some features that tend not to matter? Good representations help predict success. For example, in the design work in our own lab, we find it useful to separate designs into the more abstract feature of curricula that act to separate the teacher from the students (bad) vs. curricula that act to bring the teacher in close regular contact with the students (good) rather than in terms of more superficial features like many different variations of video-based demonstrations (good and bad) or paper-based instructions (good and bad). Explore End-User Perspective Usually designers are not designing something for themselves or often not even for people who are like them. In educational design, we usually design materials for people much younger than us, often for people from different demographics from us, and certainly for people who know less that we do Page 5 about the topic at hand. Further, design teams are often multidisciplinary, and thus each member of the design team is removed from the end-user in a different way. Under these circumstances, it is rather easy to design a solution that is good
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