Cards on the Table: Understanding and Utilizing Categorization in Design Education Settings as a Basic Aspect of Teaching Design

Abstract

The ability to categorize sketches, ideas, and concepts is an essential, basic skill for designers. Novice- and intermediate-level design students may benefit from making categorization a more explicit step in their project analyses to help them integrate an already developed general skill into the decision making methods that guides their design processes. This step supports the development of more complex and informed approaches to idea generation and the subsequent iterative development of design concepts. While expert-level designers may not often refer to categorization explicitly once they have internalized this ability, articulating basic skills that later become automatic can be an effective step in teaching more complex skills and processes to emerging designers. Additionally, doing this can ensure that design processes become understandable and accessible to wider audiences, including those less inclined to engage in any form of design practice or thinking.

Introduction

Imagine you are playing a game of cards, perhaps poker, or bridge, or hearts, or gin rummy. When you pick up your cards, you see combinations of numbers, pictures, colors, and shapes. Depending on which game you are playing, you immediately begin to organize the cards in your hand, usually into sequences and suits. You recognize the suits by color and shape — black clubs or spades, red diamonds or hearts. In some games, you look to see how many you have of each specific numeral or face card, regardless of suit (four sevens, two Kings, three Aces, etc.). As you go on to play the game, you continue to make matches to the groups or sequences you have identified.

In all cases, you are exercising the underlying intellectual skill of identifying categories, noticing and separating items according to their specific features. We learn categorization skills early in life, putting things into groups that are in some way alike, or calling out differences and finding things that “don't belong” in a particular group. (“Dog, cat, rabbit, hamster, umbrella — which item doesn’t belong in this group?”) These skills are so important to everyone that the cognitive scientist Steven Harnad simply asserts: “Cognition is categorization,” explaining that, “all of our categories consist of ways we behave differently toward different kinds of things... That is all that cognition is for and about.” [1] Harnad points out that categorization and learning are “intimately” connected, either through trial and error or more explicit training, and that they are processes necessary for figuring out which features to pay attention to in particular situations. [2]

While categorization is well-studied by psychologists and other scientists who study cognition, its usefulness as an explicit tool in teaching basic design processes may be less obvious to design educators. In part, this is because many skills (such as the individual components of more complex processes) can be acquired implicitly through practice or trial and error without them ever having to be explained. [3] Even if a basic design skill or concept can be acquired implicitly, making it explicit may provide a smoother path for emerging designers to develop more advanced-level skills. In addition, expert-level designers, like experts in almost all fields, disciplines and activities, eventually come to use many skills unconsciously while engaging in their work, even those skills that had originally been acquired more explicitly.[a][4] Deconstructing those unconscious skills — reverse engineering this type of acquired and constructed expertise — has always been one of the fundamental challenges of teaching, since important basic skills often appear to be hiding in plain sight. They have become so intuitive or automatic that we are not even aware we are using them.

Employing categorization in the design process appears to be one of those hidden skills. Presenting it more explicitly to novice- and intermediate-level design students provides a viable scaffold for introducing or reinforcing basic design process concepts by connecting a familiar general skill to new discipline-specific situations.[b] Utilizing categorization as an explicit analytical tool improves students' understanding of idea generation, iteration, and project analysis and refinement.

Demonstrating Categorization

Categories themselves are not simply fixed entities in the external world (in the way we may think of the difference between rocks and trees), but instead are more flexible mental constructs that reflect our own internal understandings about the things we encounter. [5] This flexibility — along with a reminder that students are already familiar with categories — is easily demonstrated in the classroom by sweeping a number of items from an office desk (pens, pencils, markers, stapler, scissors, various clips, post-it notes, an exacto knife, etc.), laying them out on a classroom table, and asking students how they can be categorized.

One of the easiest surface characteristics to identify in a learning setting like this is color: students quickly point out objects that are red, yellow, blue, silver, or black. They also identify things by their general shape: all the long, thin objects (pens and pencils), thicker long objects like the markers, small objects like the clips, and bulkier objects like the stapler and the scissors. Another common arrangement is grouping according to materials — wood, plastic, and metal; still another involves simply grouping things by specific kind — a pile for the pencils, a pile for the pens, another for the markers. An examination of the underlying functions of these objects produces categories that get beyond formal similarities: things that cut (putting the scissors and knife together), things that bind other things together (putting the stapler together with all the various kinds of clips), and things that write or draw (putting all the pens, pencils, and markers together).

Students' initial familiarity with categories provides an interesting starting point for evaluating design work as a project moves along. As I will demonstrate, by categorizing sketchesc after each round of work, students: 1) develop methods to create additional ideas beyond their first efforts; and 2) learn to cross-reference ideas from various sketches[c], leading to more sophisticated iteration and project development.

Categorization and Idea Generation

One way many design faculty encourage novice students to generate ideas is by requiring them to produce a specific numbers of sketches for a project, thereby coaxing them to try numerous variations, and then encouraging them through critique to extend the range and the depth of their explorations. Rather than focusing on developing a single idea early in the design process, we want students to broadly understand the flexibility inherent in whatever materials they are working with, which will give them the ability to generate alternate structures or changes in meaning. Students, however, tend to search more immediately for a single effective visual and conceptually appropriate solution to whatever problem they have been challenged to address. This sets up a well-known tension: students who are looking for the “right answer” versus teachers looking for broader explorations of project materials and possibilities.

Idea generation itself — the production of multiple possible solutions or outcomes — is not an easy or obvious skill. In Conceptual Blockbusting, James Adams points out a number of barriers to generating new ideas, [6] and many authors have discussed techniques for “unlocking creativity.” [7] When students first produce a specified number of sketches for a basic project, they may feel they have done a great deal of work, or feel their work is complete. At that moment, explicit categorization of their sketches can point the way to additional ideas and open a door to understanding the value of continuing exploration. By placing the sketches in categories — small groups of work that share similar characteristics — we can: 1) demonstrate that the exploration has not been as extensive as it first appears; and 2) discover areas of the problem that may not have been explored.

Figure 1 depicts 18 sketches that emerged from the facilitation of a very basic design exercise that involves challenging students to arrange possible compositions using a fixed square in the middle of a page surrounded by any number of circles. These are shown in the order produced (viewing from left to right, top to bottom). In this exercise, both the square and the circles can be black, white, or transparent, and be rendered with or without outlines. The single square must remain fixed in the center position, the circles can be arranged in any position, size, or number. There are an infinite number of possible arrangements and resulting ideas.

Despite the openness of this exercise it is interesting to note that, after having completed 18, 20, or 30 arrangements, novice students often report they are “out of ideas” as to what to do next despite a prompt to simply develop as many different variations and approaches as possible. Some are more comfortable with the basic idea of exploration and can take their work further, while others are more easily frustrated. By paying attention to the origins of these frustrations and addressing them, we can help unlock the potential of the design process to yield a more diverse array of outcomes across a greater range of students.

Figure 2 depicts the same sketches rearranged into a few informal categories. These categories are discovered by asking students to rearrange the work in their own or another student's set of sketches. Decisions about what the actual categories should be is left up to the students engaged in the rearranging process, they are free to construct whatever groupings they notice or features they see on a visual or conceptual level. Students can begin with a simple pair of sketches they feel are similar, identify what features or ideas cause that sense of similarity, and then look for additional sketches that display some of the same features.

Once the work has been grouped into the categories shown in figure 2, it becomes clear that within this array of 18 sketches there are perhaps only four or five major ideas. This discovery — which is sometimes surprising if the student thinks he, she or they has actually created 18 different compositions — relates to the fact that there is no “one correct way” to sketch or explore ideas while compositions are being constructed. Results are often recursive as students recycle some of their initial ideas while trying to develop new ones. This is not an indication of any problem or mistake on the part of any individual student, but instead shows how individually varied different people’s ways of thinking and making compositions can be and is. It also demonstrates that it may take specific skills or analytical steps to expand the search for new ideas.

Figure 1: circle/square exercise; pages from an original student sketch file, shown in the order produced. (Designs by Jordan Stockman)

Figure 2: the same circle/square exercise sketches as shown in figure 1, rearranged into informal categories. (Designs by Jordan Stockman; categorization by the author.)

Because the initial effort at categorization “quiets the field,” leaving four or five groups to focus on rather than 18 different individual compositions, it allows for more effective, critical analysis of the work. When grouped into categories, the changes between each individual composition no longer seem as random or varied. At that point, the first important question to ask is: “What is the designer doing that is almost always the same across the entire array of work?” In figure 2, we can discern the following:

• Circles are almost always a single size in each individual composition.
• Only limited variations in line weights are employed across all the work.
• The circles are almost always touching the center square, and are often in symmetrical relationships to its center.

Expressed as prompts, the corollary to these observations provides an easy guide to additional idea generation:

• Try some variants that make use of different size circles in the same composition.
• Try some variants that deploy different line weights (within a single composition, or in different compositions).
• Try positioning the circles so they are not symmetrical in relationship to the center, or not touching the center.

Initial benefits from engaging in a simple formal categorization of a first set of sketches — which can be accomplished quickly — are:

• Idea management: by seeing similarities, the number of independent visual choices that need to be paid attention to at any one time is reduced;
• Idea generation: by recognizing gaps across the array of the work, which are more evident once the sketches are categorized, prompts for additional variations (and a number of new compositions) can be developed.

Designers, both students and professionals, need to be able to identify areas they have yet to explore within the structure of any problem they are challenged to address, whether it is a foundation exercise or a more complex communication problem. It has been shown that in initial phases of design work, professionals are often looking for a “problem framing” (conceptual, structural, or hierarchical) which will satisfy broader or deeper project goals. [8] This is an activity that requires generating many different ideas that can be tested and explored. In this exercise, the “formal” route to generating additional ideas (making changes to basic formal characteristics such as position, quantity, or line weight) is particularly effective for students who have the most difficulty with idea generation, particularly those who feel each new sketch has to be “very new,” or “immediately clever or creative,” instead of building an idea atop one or more that they have generated earlier, or combining some aspects from at least two of these into yet another idea. More facile design students — those who have less initial trouble producing multiple sketches — can also utilize categorization combined with implementing changes to formal characteristics to specific objects in a given composition to identify gaps in their work, or discover new directions they would like to explore.

Categorization and Iteration

Another benefit of using explicit categorization to guide the initial development of student work can be seen in the transition from engaging in the thought processes that guide idea generation to engaging in the thought processes that guide iteration. These two skills are closely intertwined, but they need to be understood by emerging designers as being distinct from each other. One current understanding is that an “iteration” of something is any new version of it. Understood in this way, iterating is very similar to simply generating ideas. However, another definition is that an iteration is as a step in an algorithmic process that brings you closer to a solution. [9] In this article, I refer to “idea generation” as an initial basic skill that allows one to produce multiple variations using specified materials, whereas “iteration” involves an intervening (sometimes simultaneous or unconscious) process of analysis, synthesis, and evaluation.[10],[11] Iteration implies building on new levels of insight, and going beyond simply generating alternatives.

Students who have learned to generate a variety of initial ideas often still exhibit a behavior I call “make some — choose one” that perpetuates a misconception about the iterative nature of design work. They look for the “best one” in their group of sketches, intending to continue work on that version while ignoring all the rest. As a result, they miss out on the dialogue within the array of work they have created to that point in their design process, and thus lose valuable information that has been articulated in their other sketches. Design, in its largest sense, is a much more complex process than simply generating alternatives and then picking just one from among these. First, the process of idea generation is likely to be incomplete in a single round of exploration since the search space is usually much larger than was originally anticipated, especially by an emerging designer who has likely not engaged in the kinds of thinking and understanding necessitated by engaging in the design process. Second, and equally as important, design is an indeterminate process — goals and solutions are explored together. [12] So while a particular idea may initially be appealing, eventually it might not satisfy a more refined set (or sets) of goals and criteria. And a sketch that appears less successful at first may turn out to contain the seeds of something more important in relation to emerging goals. Categorization of sketches can facilitate a more effective iterative analysis of the scope or depth of work that a student produces.

The initial step in categorization, described above, involved looking for similarities within groups and across the overall body of work produced by a given student. The next step involves examination of differences between sketches in the same body of work. Closer comparisons within a single grouping can provide new insights, especially in cases where one item in a group seems to have unique characteristics. Also, comparing single items from two separate groups can yield similarly useful understandings. Critically analyzing specific differences between two sketches and asking the question “What difference do those differences make?” can move the discussion beyond simple formal changes and begin to address key conceptually rooted themes that appear in the work.

Figure 3 depicts one group of sketches (Group B) from our larger set, chosen because all the circles in this array of four sketches have been placed within the square, with no elements visible in the surrounding area. Comparing items B3 and B4 reveals specific formal differences: two circles versus multiple circles; circles of the same size versus circles of different sizes. Addressing our specific question, “what difference do those differences make?” brings up the general theme of “order” versus “disorder or randomness.” Stepping back to look at all the sketches (figure 2, again) we notice that item B4 is the only sketch in the entire group that depicts disorder or randomness. Realizing this allows us to open a completely new avenue of exploration while building new insights into what the work has the potential to communicate visually.

Similarly, a comparison between items B2 and B3 in Figure 3 shows the differences between using solid white circles and outlined circles, as well as circles contained within the center square versus those that seem to be hidden beyond the borders of the square. In B2, the theme of developing new shapes from the perceived interactions between negative and positive shapes seems prominent. In item B3, new shapes are also evident, but the thin lines also hint at depth in virtual space, transparency, and the phenomenon of hiding and revealing. Pulling back to review the full set of sketches again, we can then find sketches in other groups that match those themes, as revealed in Figure 4. This then becomes a reorganization, or recategorization of the work the student has produced to this point. Additional ideas generated at this stage of idea development can be focused on themes that seem to be emerging from across the entire body of work itself, which is indicative of more sophisticated and ongoing iterative thinking and making. Rather than choosing only one composition upon which to focus, students can be prompted to “hold open” their explorations, to notice different strengths inherent in particular compositions, or among two or more of these, and to keep several concepts or themes in mind as they further develop their work.

As a result, the following can now be added to the initial list of the benefits that engaging in categorization can yield to emerging designers’ understandings of how to generate broadly and deeply explored ideas:

• Concept identification: by examining specific differences (comparing just two sketches) students can discover potential themes and concepts expressed through analyzing differing formal characteristics.
• Iteration support: by regrouping their thinking around emerging themes, students can develop new work that synthesizes what has come before, rather than simply making a single choice of work they prefer from the work they have generated.

Figure 3: focusing on differences within a single group can lead to new insights beyond simple formal differences. (Designs by Jordan Stockman)

Figure 4: a second level of categorization, inspired by noticing differences within initial groupings, allows new themes to emerge and be explored; these include the use of shapes formed by negative spaces occurring in the top row, and the phenomenon of transparency occurring in the second row.

Analysis

Form of the Exercise

This is an exercise designed specifically to highlight the possible benefits of explicit categorization. Using a single square and any number of circles, forms are generated that can seem to be objective and recognizable, or non-objective and non-recognizable. Novice-level students are prompted to increase the amount of their initial explorations and challenged to notice and exploit the unique qualities of the materials they are using. They are asked to pay closer attention to ideas that emerge from acts of making and engaging in the working process itself. The exercise itself is embedded in a slightly larger project sequence that encourages students to begin exploring the creation of meaning in their work so as to demonstrate that:

• variation within specific constraints can produce a variety of meaningful visual messages;
• working iteratively can help define goals for the work being explored and intensify the meanings inherent in the messages that emerge.

A few final results of how students responded to these parameters are depicted in figure 5.

One could argue the parameters that guide the students’ idea generation during the evolution of a project such as this leaves out important aspects of audience, context, and values that constitute the full range of design activity. Meredith Davis writes, “it is common in many foundation programs to introduce students to design through abstraction, through problems in the arrangement of two- and three-dimensional shapes lacking both content and context. The assumption is that students must acquire a basic vocabulary of form before later applying it in specific contexts. Typical foundation curricula and textbooks defer discussions of audience, setting, and the construction of meaning until students have mastered this aesthetic language. The problem with this approach is that students generally lack criteria for judging the merits of one abstract composition over another.” [13]

Within the contexts of the exercises described in this article, no attempt has been made to judge the perceived worth of any abstract composition on a simply formal basis. Instead, initial work is discussed in terms of quantity and variety (encouraging fluency and flexibility in variation, alone) and final work is discussed in relation to specific intentions identified by the students themselves as themes emerge from their explorations. In this exercise, these intentions become the context against which the success of the design is assessed. Visual form matters, but only insofar as it achieves meaningful goals (not as an end in itself). From the perspective of introducing emerging designers to the design process, a balance is struck between the need to have students engage in a full scope of design activity at the foundation level with the need for them to discover and scaffold the specific basic concepts beginning design students need to internalize. These concepts are idea generation and iteration in service of making meaning, with a specific technique highlighted to make those activities more effective.

Figure 5: the final results of how several students responded to the parameters articulated in the circle/square project brief. (Designs by [top row] Emily Paredes, Kaitlyn Gernatt, Gabrielle Baglieri, Kaitlyn Gernatt; [bottom row] Kaitlyn Gernatt, Emily Frid, Emily Frid, Stacia Pedersen)

Further, the technique of using categorization more explicitly can be employed as an essential aspect of any design project that requires extensive sketching and variation. How that might be employed, and when and why it might be employed most effectively, is discussed below. The “big lesson” embedded in this exercise is not about the ability to configure arrangements of circles and / or squares (they are the constraints in this particular situation), but about learning and understanding decision-making processes useful for working with materials and concepts at any level. Designers who understand and become comfortable with these processes become more effective at solving almost any kind of design problem.

Conclusion

As Koedinger, Corbet, and Perfetti point out, we cannot directly observe aspects of what a student implicitly understands about a given design process or procedure; we can only infer what is known from the results. [28] In graphic design, we — as educators — can see when a student produces work that goes beyond obvious first choices; we — as educators — can tell, as a design process develops, when a student is exploring varied ideas or effectively cross-fertilizing features from different initial ideas in order for the work to come into focus and feel resolved. This then suggests that some basic knowledge about idea generation and iteration is in place in the student’s mind, and sufficiently integrated into his, her or their understandings well enough to produce those more sophisticated results. A missing basic component, or misunderstood process, can impede that learning process considerably.

What is suggested here is that categorization is a basic component of design processes (an understanding that designers eventually deploy), and that while it does not always appear explicitly as part of those design processes, it may be helpful to give it a more explicit place early in the development of higher-level, integrated design skills. There are undoubtedly other ways to do this — the demonstration articulated here is simply one example. A single instance does not “prove the point” that explicit training is more effective than ongoing intuitive practice supported by critique — that would require more specific empirical research — but it does suggest the potential for using categorization as a teaching tool. It is a familiar skill that novice-level design students can use to grapple with the complexities of design processes while learning to generate more and better ideas. The particular examples described here provide support for idea generation, idea management, concept identification, and further iteration. While categorization of this kind does not usually show up explicitly in expert design processes, research in the science of learning points toward identification and explanation of the basic components of discipline-specific skills as an effective teaching practice, particularly for skills that may have become automatic for experts.

In a larger sense, if we are to teach students more effectively, and teach design to a wider range of students — not just those who are highly motivated or predisposed to practice professionally — then the specific components of basic design knowledge need to be better understood and articulated. We can use these to broaden the impact of design and make our teaching more effective. When playing cards, it matters how you sort your suits and sequences. When designing, it matters how you sort your ideas on the way to developing more sophisticated concepts.

References

• Adams, J.L. Conceptual Blockbusting: A Guide to Better Ideas, 5th ed. New York, New York, U.S.A: Basic Books, 2019.
• Ambrose, S.A., and Lovett, M.C. “Prior Knowledge Is More Than Content: Skills and Beliefs Also Impact Learning.” In Applying Science of Learning in Education: Infusing Psychological Science into the Curriculum, edited by V. Benassi, C. Overson and C. Hakala. pgs. 7–19. Washington, DC, U.S.A: Society for the Teaching of Psychology, 2014.
• Buchanan, R. “Wicked Problems in Design Thinking.” In The Idea of Design, edited by V. Margolin and R. Buchanan, pgs. 3–20. Cambridge, Massachusetts, U.S.A: The MIT Press, 1995.
• Cross, N. Design Thinking: Understanding How Designers Think and Work. New York, New York, U.S.A: Berg, 2011.
• Davis, M. Teaching Design: A Guide to Curriculum and Pedagogy for College Design Faculty and Teachers Who Use Design in Their Classrooms. New York, N.Y., U.S.A.: Allworth Press, 2017.
• Feltovich, P.J., Ericsson, K.A., and Prietula, M. “Studies of Expertise from Psychological Perspectives.” In The Cambridge Handbook of Expertise and Expert Performance, edited by K.A. Ericsson, N. Charness, R.R. Hoffman and P.J. Feltovich. Cambridge, UK: Cambridge University Press, 2006. Online. Available at: http://search.credoreference.com/content/entry/cupesrt/studies_of_expertise_from_pyschological_perspctives/0 (Accessed January 20, 2015).
• Harnad, S. "To Cognize Is to Categorize: Cognition Is Categorization." In Handbook of Categorization in Cognitive Science, edited by H. Cohen and C. Lefebvre, pgs. 19–43. Elsevier Science & Technology, 2005. Online. Available at: https://ebookcentral.proquest.com/lib/lesley/detail.action?docID=270070 (Accessed October 11, 2021).
• Jones, J.C. Design Methods, 2nd ed. New York, New York, U.S.A.: Van Nostrand Reinhold, 1992.
• Kober, N. Reaching Students: What Research Says About Effective Instruction in Undergraduate
• Science and Engineering. Washington, DC, USA: The National Academies Press, 2015.
• Koberg, D., and Bagnall, J. The Universal Traveler: A Soft-Systems Guide to Creativity, Problem-Solving, and the Process of Reaching Goals, 4th ed. Menlo Park, California, USA: Crisp Learning, 2003.
• Koedinger, K.R., Corbett, A.T., and Perfetti, C. "The Knowledge-Learning-Instruction Framework: Bridging the Science-Practice Chasm to Enhance Robust Student Learning." Cognitive Science, 36 (2012): Pgs. 757–798.
• Lakoff, G. Women, Fire and Dangerous Things: What Categories Reveal About the Mind. Chicago, Illinois, U.S.A.: University of Chicago Press, 1990.
• Lawson, B. How Designers Think, 2nd ed. Oxford, U.K.: Butterworth-Heinemann, 1990.
• Lee, C.H., and Kalyuga, S. “Expertise Reversal Effect and Its Instructional Implications.” In Applying Science of Learning in Education: Infusing Psychological Science into the Curriculum, edited by V. Benassi, C. Overson and C. Hakala. Pgs. 31–44. Washington, D.C., U.S.A.: Society for the Teaching of Psychology, 2014.
• Perkins, D.N., and Salomon, G. “Are Cognitive Skills Context-Bound?” Educational Researcher, 18.1 (1989): pgs. 16–25. Online. Available at: https://www.jstor.org/stable/1176006. (Accessed March 17, 2021).
• Polanyi, M. The Tacit Dimension. Gloucester, Massachusetts, U.S.A.: Peter Smith, 1983.
• Reber, A.S. “Psychology Of Tacit Knowledge.” In International Encyclopedia of the Social & Behavioral Sciences, vol. 23. pgs. 15431-35. Oxford, U.K: Elsevier Science, Ltd., 2001.

Biography

Geoffry Fried is Professor Emeritus of Design at Lesley University College of Art and Design in Cambridge, Massachusetts, U.S.A. His areas of research interest include design philosophy, definitions of design activity, and developing basic curriculum in graphic design education. He has made numerous presentations at design conferences, and his essays are included in The Education of a Graphic Designer, The Education of an E-Designer, and The Education of a Typographic Designer. His areas of professional practice include publication, environmental, exhibition, and user interface design. email: [email protected]

• a

  As a person develops expertise in any subject area a cognitive transformation called "chunking" occurs, which allows them to mentally package certain groups of information or relationships in such a way that they no longer need to be aware of each specific detail of an operation. This lessens "cognitive load" (remembering all the details individually), making room to connect to and learn new information.

• b

  Ambrose and Lovett write: “In fact, prior knowledge is one of the most influential factors in student learning because new information is processed through the lens of what one already knows, believes, and can do.” Ambrose, S.A. & Lovett, M.C. “Prior Knowledge is More Than Content: Skills and Beliefs Also Impact Learning,” ed. Victor Benassi, Catherine Overson, and Christopher Hakala, Applying Science of Learning in Education: Infusing Psychological Science into the Curriculum (Society for the Teaching of Psychology, 2014).P. 7.

• c

  The term “sketch” is used throughout this paper to denote any process for prototyping various ideas, at any level, whether these are hand-drawn, digitally rendered, physically constructed, etc.

• d

  Polanyi wrote: “The skill of a driver cannot be replaced through schooling in the theory of the motorcar; the knowledge I have of my own body differs altogether from the knowledge of its physiology; and the rules of rhyming and prosody do not tell me what a poem told me, without any knowledge of its rules.” Polanyi, M. The Tacit Dimension (Gloucester: Peter Smith, 1983). P. 20.

• e

  Koedinger, Corbett, and Perfetti correlate “knowledge components” (units of understanding) with “learning events” (types of cognitive learning processes), and match those to the most effective types of instructional principles supported by science of learning research in specific subject areas. They use detailed analysis of domain-specific tasks to determine the components that need to be understood and the detailed processes that support eventual understanding. Knowledge components and learning events themselves are not visible, but are inferred from specific instruction events (particular teaching interventions or tactics) and resulting assessments (such as explanations, performance on specific tasks, or tests) that demonstrate understanding. The framework aims to identify components at an empirically observable scale, to see how students are acquiring basic knowledge components, and what they need to understand in order to combine those components into more complex, integrated skills.

1. Harnad, S. “To Cognize is to Categorize: Cognition is Categorization,” in Handbook of Categorization in Cognitive Science, ed. Henri Cohen and Claire Lefebvre (Elsevier Science & Technology, 2005). P. 20. ProQuest Ebook Central.

2. Harnad, “To Cognize is to Categorize: Cognition is Categorization.” P. 22.

3. Reber, A.S. "Tacit Knowledge, Psychology of," International Encyclopedia of the Social & Behavioral Sciences 23 (2001). 15432-15433 (section 1.3).

4. Feltovich, P.J., Ericsson, K. A. & Prietula, M. “Studies of Expertise from Psychological Perspectives,” in The Cambridge Handbook of Expertise and Expert Performance, ed. K. Anders Ericsson et al. (Cambridge, U.K.: Cambridge University Press, 2006). See sections on “Integrated Cognitive Units” and “Automated Basic Strokes.” Credo Reference

5. Lakoff, G. Women, Fire and Dangerous Things: What Categories Reveal about the Mind, Paperback ed. (Chicago, Illinois, U.S.A.: University of Chicago Press, 1990). Chapter 17.

6. James L. Adams, Conceptual Blockbusting: A Guide to Better Ideas, 5th ed. (New York, New York, U.S.A: Basic Books, 2019).

7. For example: Koberg, D. and Bagnall, J. The Universal Traveler: A Soft-Systems Guide to Creativity, Problem-Solving, and the Process of Reaching Goals, 4th ed. (Menlo Park, California, U.S.A.: Crisp Learning, 2003).

8. Cross, N. Design Thinking: Understanding How Designers Think and Work (Oxford; New York, New York, U.S.A.: Berg, 2011).

9. Merriam-Webster.com Dictionary, s.v. “iteration,” accessed October 15, 2021, https://www.merriam-webster.com/dictionary/iteration.

10. John Chris Jones, Design Methods, 2nd ed. (New York, New York, U.S.A.: Van Nostrand Reinhold, 1992). Pgs. 63-64.

11. Lawson, B. How Designers Think, 2nd ed. (Oxford, U.K.: Butterworth-Heinemann, 1990). Pgs. 33-34.

12. Buchanan, R. Wicked Problems in Design Thinking,” in The Idea of Design, ed. Victor Margolin and Richard Buchanan (Cambridge, Massachusetts, U.S.A.: The MIT Press, 1995). P. 15.

13. Meredith Davis, Teaching Design: A Guide to Curriculum and Pedagogy for College Design Faculty and Teachers Who Use Design in Their Classrooms (New York, New York, U.S.A.: Allworth Press, 2017). P. 95.

14. Ambrose and Lovett, "Prior Knowledge is More Than Content: Skills and Beliefs Also Impact Learning." 10.

15. Feltovich, Ericsson, and Prietula, “Studies of Expertise From Psychological Perspectives.” P. 5.

16. Perkins, D.N. and Salomon, G. “Are Cognitive Skills Context-Bound?,” Educational Researcher 18, no. 1 (Jan.-Feb.) (1989). Online. Available at:https://www.jstor.org/stable/1176006. (Accessed May 22, 2022). P. 23.

17. Kober, N. Reaching Students: What Research Says About Effective Instruction in Undergraduate Science and Engineering (Washington, DC: The National Academies Press, 2015). P. 57. http://www.nap.edu/catalog.php?record_id=18687

18. Ambrose and Lovett, “Prior Knowledge is More Than Content: Skills and Beliefs Also Impact Learning.” P. 7.

19. Ambrose and Lovett, “Prior Knowledge is More Than Content: Skills and Beliefs Also Impact Learning.” P. 7.

20. Perkins and Salomon, “Are Cognitive Skills Context-Bound?.” P. 19.

21. Jones, Design Methods. 11. For Jones, the sketch “represents the form of the problem.”

22. Cross, Design Thinking: Understanding How Designers Think and Work. Pgs. 19-26.

23. Cross, Design Thinking: Understanding How Designers Think and Work. P. 19.

24. Koedinger, K.R., Corbett, A.T., & Perfetti, C. ”The Knowledge-Learning-Instruction Framework: Bridging the Science-Practice Chasm to Enhance Robust Student Learning," Cognitive Science 36 (2012).

25. Koedinger, Corbett, and Perfetti, “The Knowledge-Learning-Instruction Framework: Bridging the Science-Practice Chasm to Enhance Robust Student Learning.” P. 791.

26. Ambrose and Lovett, “Prior Knowledge is More Than Content: Skills and Beliefs Also Impact Learning.” P. 10.

27. Lee, C.H. and Kalyuga, S. “Expertise Reversal Effect and Its Instructional Implications,” ed. Victor Benassi, Catherine Overson, and Christopher Hakala, Applying Science of Learning in Education: Infusing Psychological Science into the Curriculum (Society for the Teaching of Psychology, 2014). Pgs. 37-38.

28. Koedinger, Corbett, and Perfetti, “The Knowledge-Learning-Instruction Framework: Bridging the Science-Practice Chasm to Enhance Robust Student Learning.” Pgs. 761-762.