Category Archives: UNL / OODA

The OODA Loop and Creativity, Try 2

Afer heavily revising my original work tying together the OODA loop to creativity, it has become clear that the project will involve much more than a few references in another paper. So I’m removing it from my current draft, but (for posterity) here were my final thoughts on Creativity in the context of OODA, at least before my work on the taxonomies of creativity changed my perspective.


The OODA loop was originally described to assist in understanding the nature of creativity (Coram, 2002). Creative thoughts, according to Boyd (1992), “permit us to rematch our mental/physical orientation [with the outside world] and grow” in the world (24). Before individuals can be creative, they must be experts. This requires reorientation. However, reorientation that leads to creativity is difficult because expertise requires considerable practice outside of an educational setting. Fortunately, educational psychology’s initial work on dual processing presents a way forward.
Modern research views creativity as a subset of expertise. This formulation is expanded on at length in Herbert Simon’s exploration of creativity in the arts and sciences . Expertise is defined by strong problem solving ability in a particular field, meaning quick scanning of a problem space for any of a large number of remembered patterns (Simon, 2001). Expertise tends to require more than ten years to develop, and a narrowness of focus that can involve both personal and intellectual sacrifices including slowed or reduced growth in other fields that are not focused on or practiced (Simonton, 2003).
The importance of reorientation in creativity is stressed by a recent overview of the growing literature on cognitive load. For instance, van Merrienboer & Sweller (2005) write that “expertise comes from knowledge stored in [long term memory] schemata, not from an ability to engage in reasoning with many elements that have not been organized in long-term memory. Human working memory simply is not able to process many elements” (149-150). Similarly, Sweller (2004) describes how random variations in ideas are necessary for creative products to be new, and not mere memories. The product of such thinking is “change via novelty” (20). Likewise, cognitive load describes originality is seen as random variations in the expression of long-term memory, and original ideas are kept or lost depending on their fitness in the landscape of thought (Sweller, 2004; van Merrienboer & Sweller, 2005). Yet as randomness in thought is assumed to be constant among all individuals, what makes those new ideas more likely to be useful is whether they are grounded in an orientation rich in relevant long term memory.
The scale of the difficult in encouraging creativity is gleaned from a recent discussion on minimal guidance instruction (Kirschner, Sweller, & Clark, 2006). Directly addressing the question of discovery-based styles of instruction, Kirschner and colleagues distinguish expert from novice operating styles. Summarizing research on the expert/novice divide, the authors conclude that attempting to become an expert by replicating the style of experts is not a productive strategy. Yet in an increasingly complex world where many learners will go on to perform tasks that do not currently exist, some form of discovery-based learning will be necessary for the development of expertise in these fields of the future. The task of the educator is not enviable.
Fortunately, educational psychology’s early approaches to dual processing show the way forward. Motivation and good attitude, focused on by Sinatra (2005) and Gregorie (2005), provide an approach that will encourage learners to continue their own reorientation long after they leave the classroom. To put it simply, motivation leads to more practice, more practice loads to more expertise, and more expertise leads to more creativity. In creativity as with other fields of educational psychology, dual processing and OODA do not overturn what we already know. Rather, the Observe-Orient-Decide-Act dual-processing cycle enrich what educational psychology has already discovered about providing the best education possible to our learners.

Boyd, J.R. (1992). The conceptual spiral. Retrieved October 1, 2007, from Belisarius. Web site: http://www.d-n-i.net/boyd/pdf/intro.pdf.
Coram, R. (2002). Boyd: The fighter pilot who changed the art of war. New York: Back Bay Books.
Gregorie, M. (2003). Is it a challenge or a threat? A dual-process model of teachers’ cognition and appraisal process during conceptual change. Educational Psychology Review, 15(2), 147-179.
Kirschner, P.A., Sweller, J., Clark, R.E. (2006). Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discovery, problem-based, experiential, and inquiry-based teaching. Educational Psychologist, 41(2), 75-86.
Simon, H.A. (2001). Creativity in the arts and sciences. In Cultures of creativity: The centennial celebrations of the Nobel Prizes. Kenyon Review, Spring, 23(2), 203-220.
Simonton, D.K. Expertise, competence, and creativity ability: The perplexing complexities. (2003). In The Psychology of Abilities, Competencies, and Expertise (R.J. Sternberg & E. Grigorenko, Eds.) New York: Cambridge University Press.
Sinatra, G.M. (2005). The “warming trend” in conceptual change research: The legacy of Paul R. Pintrich. Educational Psychologist, 40(2), 107-115.
Sweller, J. (2004). Instructional Design Consequences of an Analogy between Evolution by Natural Selection and Human Cognitive Architecture. Instructional Science, 32(1/2), 9-31.
van Merrienboer, J.J.G. & Sweller, J. (2005). Cognitive load theory and complex learning: Recent developments and future directions. Educational Psychology Review, 17(2), 147-177.

A History of the OODA Loop

This post was written as part of the roundtable on Frans Osinga’s Science, Strategy, and War. Contributions have already been made by Chet Richards and Wilf Owen.

“To a certain extent the argument is valid that Boyd offered merely a synthesis of existing theories, a contemporary one, important and timely regarding the context of the 1970s and 1980s, but only a synthesis.”
Osinga, 2007, pg 29

John Boyd’s OODA Loop divides cognition into four processes, perception (called Observation), unconscious or implicit thought (called Orientation), conscious of explicit though (called Decision), and behavior (called Action). Frans Osinga’s “Science, Strategy, and War: The Strategic Theory of John Boyd” does an excellent job describing the origins of Boyd’s learning theory in the writings of Skinner, Piaget, and the cognitivists. However, Osinga’s text excludes ongoing research into theories of learning related to OODA, as his text is focused on the development of the OODA model in particular rather than contemporary adaption. Fortunately, a recent review article by Jonathan St. B.T. Evans serves helps complete the picture, though the OODA loop is not mentioned there by name. Osinga’s book is well worth purchasing, and can be thought of as as prolegomena to all future OODA work.


The OODA Loop

The “OODA loop,” or “Boyd Cycle” (Osinga, page 2) is a dual-processing model of thought. That is, it supposes the existence of two seperate central executives inside each human mind. The first of these, “Orientation,” is activated immediately by perception (called Observation by Boyd) and is capable of directly controlling behavior (likewise, called Action). Orientation is closely associated with long term memory. As Osinga writes on pages 236 to 237:

In order to avoid predictability and ensuring adaptability to a variety of challenges, it is essential to have a repertoire of orientation patterns and the ability to select the correct one according to the situation at hand while denying the opponent the latter capability. Moreover, Boyd emphasizes the capability to validate the schemata before and during operations and the capability to devise and incorporate new ones, if one is to survive in a rapidly changing environment…. verifying existing beliefs and expectations, and if necessary modifying these in a timely matter, is crucial. The way to play the game of interaction and isolation is to spontaneously generate new mental images that match up with an unfolding work of uncertainty and change, Boyd asserted…”

The second central executive, Decision, analogous to conscious thought, or what attention is spent on. As Osinga writes, “Decision is the component in which actors decide among actions alternatives that are generated in the orientation phase.” Unlike orientation, decision faces limits in how much it can handle, and therefore relies on orientation to present it which simplified and categorized chunks in which to work.

John Boyd’s model was purposefully designed as an cognitive and learning theory based on mainstream work within psychology. As Osinga writes on page 53:

On 15 October 1972 he wrote from his base in Thailand to his wife that ‘I may be on the trail of a theory of learning quite different and – it appears now more powerful than methods or theories currently in use’. Learning for him was synonymous for the process of creativity

In particular, Boyd’s theory was based on the work of Jean Piaget, B.F. Skinner, and the earlier cognitivists. Boyd combined each of these traditions, though revised some elements. From Piaget he both took the concept of mental structures, as well as suspicion of the power of logical analysis alone as a proper epistemological tool. To again quote Osinga (page 68)

Boyd also came across another source of uncertainty. As Jean Piaget asserted in the book Boyd read for his essay, ‘In 1931 Kurt Gödel made a discovery which created a tremendous stir, because it undermined the then prevailing formalism, according to which mathematics was reducible to logic and logic could be exhaustively formalized. Gödel established definitely that the formalist program cannot be executed’.

As Osinga describes in Chapter 3, “Science,” Boyd drew from both Skinner and the cognitivists the power of environmental feedback. Consider the relatively trivial cognitive or cybernetic proposition on page 72 that:

“A feedback loop is a circular arrangement of casually connected elements, in which an initial cause propagates around the links of the loop, so that each element has an effect on the next, until the last ‘feeds back’ into the first element of the cycle. The consequence is that the first link (‘input’) is affected by the last (‘output’), which results in self-regulation fo the entire system.

Osinga then proceeds to discuss the OODA loop as Boyd applied it, touching only briefly on Chapter 7 of some applications of Boydian thought to areas of military operations. However, Osinga does not emphasize the areas in which the OODA loop itself is still unique, but only compares it to either incorrect renditions of the OODA model (such as the “simplified” rendition Osinga shows on page 2) or to theories that preceded OODA (such as a cybernetic model without feedback and “(Reflex)” instead of orientation or System 2, on page 75).

Consider, for instance, two other models, one by Jon St. Evans published in 2006 and the other by Richard Moreno, published in 1990. Using different terms, the Evans model describes the role of Orientation (called by him System 1) and Decision (called by him System 2). Orientation or System 1 initially activates, and it may either lead to conceptual change or else inform further System 2 deliberation. However, Evans’ model lacks the cybernetic or cognitive function of feedback, and does not describe how the last function would inform the first. Boyd’s OODA loop, by attaching both Action and Observation to the environment, therefore may be described as a completed Evans model.


Information Processing

Likewise, the OODA loop completes the Moreno model. Moreno’s description of learning focuses on the transformation of information in the external world to long term memory. In particular, Moreno’s ongoing research focuses on the limited ability of explicit though to handle all information that should be learned. However, Moreno does not view long term memory as much other than an end-state for information (rather than the abode of Boyd’s Orientation or Evans’ System 1). Additionally, like Evans, Moreno does not connect the last stage of his model with his first.


Dual Processing

Just as Osinga does not compare the OODA loop with other contemporary models, he does not describe contemporary research that further describes the difference between Orientation and Decision. The research on the subject is now well established, and Table 2 in Evans’ 2008 paper “Dual-Processing Accounts of Reasoning, Judgment, and Social Cognition,” in the 2008 edition fo the Annual Review of Psychology, provides a synopsis of the distinction between Orientation (System 1) and Decision (System 2)

System 1 System 2
Cluster 1 (Consciousness)
Unconscious (preconscious) Conscious
Implicit Explicit
Automatic Controlled
Low effort High effort
Rapid Slow
High capacity Low capacity
Default process Inhibitory
Holistic, perceptual Analytic, reflective
Cluster 2 (Evolution)
Evolutionarily old Evolutionarily recent
Evolutionary rationality Individual rationality
Shared with animals Uniquely human
Non-verbal Linked to language
Modular cognition Fluid intelligence
Cluster 3 (Functional characteristics)
Associative Rule-based
Domain-specific Domain-general
Contextualised Abstract
Pragmatic Logical
Parallel Sequential
Stereotypical Egalitarian
Cluster 4 (Individual differences)
Universal Heritable
Independent of general intelligence Linked to general intelligence
Independent of working memory Limited by working memory capacity

Frans Osinga’s Science, Strategy, and War is a groundbreaking book on the OODA loop, describing in excellent detail how it originated. Buy it. What is needed now is an comparison of the OODA loop to contemporary theories of learning and an application of OODA in light of the newest research.

References
Evans, J. St. B. (2006). The heuristic-analytic theory of reasoning: Extension and evaluation. Psychonomic Bulletin & Review, 13(3), 378-395.
Evans, J. St. B. (2008). Dual-processing accounts of reasoning, judgment and social cognition. Annual Review of Psychology, 59, doi:10.1146/annurev.psych.59.103006.093629.
Mayer, R.E. (1996). Learners as information processors: Legacies and limitations of Educational Psychology’s second metaphor. Educational Psychologist, 31(3/4), 151-161.
Osinga, F.P.B. (2007). Science, strategy, and war: The strategic theory of John Boyd. New York: Routledge.

Survey closed (Now for some words on Creativity and the OODA loop)

Thanks to all who participated in the recent study on creativity and blogging.

The pseudo-experiment was part of my larger study of the OODA loop applied to education, in this case to creativity.

I have only started to analyze the data. Before I launched this survey, I assumed that affective “gut” attitudes would be a better predictor than cognitive “thoughtful” attitudes, with respect to blogging. I also assumed that behaviors that signify purposeful practice on blogging would be directly related to recognition as a blogger, as measured through Technorati rank. Both these findings appear to be supported by the data.

As part of my dissertation proposal, I will suggest a second, larger test (using a different sample pool), to provide further support.

Over the next few days and weeks, I will post more description and analysis of the data. Eventually what I write here will find its way into my dissertation proposal (hopefully!). But for now,

Thank you.

You made this possible.

Automaticity (Automation of Schemata)

Curtis was kind enough to except some of my thoughts on automaticity over at Dreaming 5GW. The section he highlighted was from OODA Alpha, which is an early draft of an academic paper I am writing on John Boyd’s OODA (Observe-Orient-Decide-Act) loop, applied to educational psychology. Since then, much of the paper has been rewritten. Below are the paragraphs from the current draft that reference automaticity. While the the rest of this post is assembled from different sections of my OODA paper, they serve to put my current thoughts on automaticity, with respect to the latest research. So without further ado, some words on automaticity, or the automation of mental structures:

Within the OODA model, two aspects of decision are most apparent. First, it is slower. While orientation can directly guide action, decision making represents an additional step to this process. However, just as harmful is the dampening of the power of orientation and its related automaticity. Decision can be the distracting result of environmental conditions that make exploiting one’s prior knowledge impossible. A fuller discussion on this phenomenon of disorientation is included below.

One of the sub-processes of orientation is analysis / synthesis, so it is no surprise that System 1 and System 2 activities together lead to a change of orientation. An example of this dual-system approach to learning can be seen in Leahy & Sweller’s investigation into cognitive load theory (Leahy & Sweller, 2005). After defining learning as the creation and automation of the appropriate schemata, the authors conduct two experiments into this reorientation. Their finding is that in processing complex information, directing experienced learners to imagine a correct answer produces better learning than directing them to study the appropriate material. That is, deciding to rely on orientation produces a good reorientation.

The ultimate result of reorientation is automated, effortless, orientation-level control over tasks. This result, and how to get it, is aptly described by Topping, Samuels, & Paul (2007). In experiments focused on improving reading comprehension, both the quantity and quality of practice is shown to matter. Again the interaction between orientation and decision in reorientation is revealed. With each new quality practice, the mental schemata related to a task are reinforced, requiring less decision to execute them. At the beginning of learning, large-scale decisive control over action is required. At the end, decision does not impact the result as actions are implicitly guided and controlled from orientation.


Cognitive overload, leading to disorientation, can be useful in disrupting automaticity. The positive benefits of automaticity are described above as they are the product of orientation, but automaticity also degrades performance in some areas. One negative aspect is that experts have a reduced ability to change automated behavior, precisely because the behavior is automated and not under conscious control (Wheatley & Wegner, 2001). More subtly, the expertise reversal effect may cause experts to perform more poorly than notices in some instructional situations. Specifically, expertise may act as a form of redundancy, forcing a learner to handle both a schema for already learned information as well as another scheme for nearly identical information being processed (Kalyuga, 2007).

Automaticity is often focused on academic knowledge. However, the same process of decisive analysis and synthesis leading to a new orientation occur in social information processing, as well. Gable and Van Acker (2004) describe this perspective at length in their look at the origin and treatment of socially poor behavior. A broader look at the benefits of disorienting social behavior is below, in the section on peer interaction.

The central finding of both the practical and arbitrary programs of experimentation is that orientation level processes are critical components for learning. Effortful decision may be useful in certain classroom tasks, especially at it relates to building automaticity, but learning fundamentally involves building schemata in orientation. To the extent that manipulation on the learner’s orientation achieve educational outcomes better than conscious-level decision making, orientation and not decision is the proper focus of instruction.

As described in the section on disorientation, social learning is similar to academic learning in that it involves the creation and automation of schemata. Access and use of these mental structures becomes increasingly fast and effortless over time, becoming difficult to change. In the context of cheating, harmful cooperative patterns of behavior are learned by students and, the more often executed, the easier to repeat.


Bibliography:

Gable, R.A. & Van Acker, R. (2004). Sometimes, practice makes imperfect: Overcoming the aromaticity of challenging behavior by linking intervention to thoughts, feelings, and actions. Education and Treatment of Children, 27(4), 476-489.

Kalyuga, S. (2007). Expertise reversal effect and its implications for learner-tailored instructions. Educational Psychology Review, 19, 509-539.

Leahy, W. & Sweller, J. (2005). Interactions among the imagination, expertise reversal, and interactivity effects. Journal of Experimental Psychology: Applied, 11(4), 266-276.

Topping, K.J., Samuels, J., & Paul, T. (2007). Does practice make perfect? Independent reading quantity, quality, and student achievement. Learning and Instruction, 17(3), 253-264.

Wheatley, T., & Wegner, D. M. (2001). Automaticity of action, Psychology of. In N. J. Smelser & P. B. Baltes (Eds.), International encyclopedia of the social and behavioral sciences, (pp. 991-993). Oxford, UK: Elsevier Science Limited.

OODA Alpha, Part XIII: Conclusion

The Observe-Orient-Decide-Act, or OODA, loop is a model of human cognition. The OODA model is a dual processing theory that has two main circuits: Observe-Orient-Decide which is analogous to Level 1 processing, and Observe-Orient-Decide-Act which is a form of Level 2 processing. Within an educational context, one central insight of the OODA model is that an educator does not have to focus on decision, or conscious processing, to change actions. Two broad methods, reorientation and disorientation, are presented that operate by modifying or disrupting mental cognitive structures.

Three broad educational contexts are described. Instruction, or educating to some specific end, academics, or learner interaction supervised by an educator, and creativity, or the process of an educator preparing a learner to create new and useful products. For instruction and creativity, educators must focus on building the correct orientations within learners so they can learn. For academics, educators should use disorientation where appropriate in order to interrupt the natural behavior of learners to manipulate peer interaction. For creativity, educators should reorient learners so they possess the proper intrinsic motivation to be both well adjusted and successful.


OODA Alpha, a tdaxp series
1. Abstract
2. Dual Processing Systems
3. The OODA Loop
4. Decision
5. Orientation
6. A Theory of Mind
7. Reorientation
8. Disorientation
9. Education
10. Instruction
11. Student Interaction
12. Creativity
13. Conclusion
14. Bibliography

OODA Alpha, Part XII: Creativity

Science advances. While a literature on creativity exists in the OODA program of research (Boyd, 1976b), it draws on the conception of creativity as a fundamentally different form of thinking (Osinga, 2007). Modern research is converging on the realization that whatever creativity is, it is not the result of processes that are different than other forms of thinking (Kalyuga, Chandler, & Sweller, 1998; Kalyuga, et al., 2003; Kalyuga & Sweller, 2005; van Merrienboer & Sweller, 2005; Weisberg 1986, 1993, 2006;). Therefore, the antiquated sources of the original OODA paradigm (Osinga, 2007, 79) are set aside and modern research on creativity is examined in light of the observation-orientation-decision-action learning cycle.

Creativity is an understudied field within educational psychology (Plucker, Beghetto, & Dow, 2004). Creativity is defined as production that is “novel and interesting and valuable” (Simon, 2001) and is essentially an unstructured social process between individuals and already acknowledged experts in a field (Csikszentmihalyi, 1996). That is, creativity is not seen merely as divergent thinking , which may well be part of a special potential for creativity, (Torrance, 1968; 1993; Plucker, 1999) or only useful for studying the past (Simonton, 1984) which is certainly part of creativity, but rather the production of the novel, the interesting, the valuable whenever and wherever it occurs as long as it is recognized by an appropriate audience.


Creativity is also studied under the term expertise (Feldon, 2007a). When researchers speak of expertise as something that is either present or not, conclusions are made such as that it requires ten years of purposeful practice (Ericcson, Krampe, & Tesch-Romer, 1993). Another way of viewing expertise, as something that can exist in greater or lesser quantity, involves a recognition that more creative or expert people work more effortless (Kalyuga & Sweller, 2005) and efficiently (Ericsson & Lehmann, 1996) in a task.

Expertise is largely a matter of superior memorization (Anderson, 1980). Studies of chess grand masters revealed that chess grand masters had better memory for valid chess moves than novices (De Groot, 1965) but similar memory for nonsensical chess positions (Chase & Simon, 1973) it supports the contention that differences in long term memory alone may be the cause of exceptional skill (Sweller, 2004a). van Merrienboer & Sweller (2005) describe this view succinctly when they write that “expertise comes from knowledge stored in [long term memory] schemata, not from an ability to engage in reasoning with many elements that have not been organized in long-term memory. Human working memory simply is not able to process many elements (149-150).

While the contention that learners should develop mostly on their own (Bruner, 1961) has been criticized in recent years (Kirschner, Sweller, & Clark, 2006), young adults building expertise in the real world have no choice but to engage in this constructivist behavior. Therefore, creative and expertise individuals must be able to compensate for their poor self-constructed learning environment to be able to build up the schemata necessary for high-level performance.

An OODA perspective on creativity would encourage educators to reorient learners so that they develop mastery, acquire expertise and produce creative products, over a long period time on their own. In other words, motivational orientation is the key outcome Educators who wish their students to become creative and expert later in life should internalize the proper attitudes in them in a way that minimizes the role of decided-upon ends.


OODA Alpha, a tdaxp series
1. Abstract
2. Dual Processing Systems
3. The OODA Loop
4. Decision
5. Orientation
6. A Theory of Mind
7. Reorientation
8. Disorientation
9. Education
10. Instruction
11. Student Interaction
12. Creativity
13. Conclusion
14. Bibliography

OODA Alpha, Part XI: Student Interaction

Human nature makes no sense except in the context of social interaction (Vygotsky, 1978; Boyd, 1986; Tooby & Cosmides, 1992; 2005; Bjorklund & Pellegrini, 2002; Alford & Hibbing, 2004). This allows the academic system to function. Whether learners are engaged in construction rationality through multiple perspectives and reflection (Piaget, 1932/1965, 1985, 2001; Moshman, 1995, 2005) or peer tutoring (Topping & Bryce, 2004), academics cooperation is used in a variety of contexts (Das & Das, 2004; Ping & Swe, 2004; Carter & Hughes, 2005; Nambissan, 2005).

However, while cooperation may come naturally and easily from learner’s orientation, it may not be the form of cooperation that educators wish. Various forms of fairness driven cooperation needs to be suppressed by teachers such as cheating (Lin & Wen, 2007) and classroom disruption (Paulsel & Chory-Assad, 2005). An approach to modify cooperation among learners is needed, so that it can be disrupted where it hurts and encouraged where it helps.


In order to make cooperation work, however, an environment must be created where cooperation makes more sense than non-cooperation. One such way to do this is by individuals encoring common standards of decency on each other (Boyd, et al., 2003; Orbell, et al., 2004). Teachers often encourage peer-on-peer sanctioning, whether directly (Mann, 2006) or indirectly (Ronen & Langley, 2004). This works because enough learners often both willing to help others but averse to being unfairly used (Hibbing & Alford, 2004; Smith, 2006), caring about fairness and procedural justice (Gold, et al., 1984; Hibbing & Theiss-Morse, 2001; Alford & Hibbing, 2004). The concern for fairness even manifests itself in the brain (Singer, et al., 2006) and heritable (Wallace, et al., 2007) though of course is mediated by the broader culture (Henrich, et al., 2001). In other words, it’s part of orientation.

Four options present themselves for altering behavior when orientation does not produce the desired actions. First, reorientation might be used. Yet as mentioned above, there are a host of positive forms of cooperation that may be impacted by such manipulation of minds.. Second, students can be removed from even social activities by computer systems that mimic experts (Lehman, Bruning, & Horn, 2003) or peers (Kim & Baylor, 2006). However, the feasibility of cyber- and robotic learning companions is not yet determined. Thirdly, the academic environment can be made more resilient if such manipulation of the social environment is unfeasible (Doll, Song, & Siemers, 2003; Doll, Zucker, & Brehm, 2004). To the extent that altering the nature of social contacts is not realistic, altering the context in which those contacts happen is the wise course.

Another approach is to use disorientation to interrupt the natural behavior of learners. Disorientating stimulus might vary by task or situation, so environments that are likely to produce beneficial forms of cooperation may lack it while situations that may lead to harmful forms of cooperation would be purposefully disorienting.


OODA Alpha, a tdaxp series
1. Abstract
2. Dual Processing Systems
3. The OODA Loop
4. Decision
5. Orientation
6. A Theory of Mind
7. Reorientation
8. Disorientation
9. Education
10. Instruction
11. Student Interaction
12. Creativity
13. Bibliography

OODA Alpha, Part X: Instruction

In the context of conflict, Boyd (1986) instructs the reader to “get inside the adversary observation-orientation-decision-action loops (at all levels by being more subtle, more indistinct, more irregular, and quicker – yet appear to be otherwise.” The requirement for deception is because operations on the other’s orientation take place in confusing, disordered, and menacing environment (Boyd, 1986, 5). Yet whatever the attrition educators face (Smith & Ingersoll, 2004), students are not a force to be taken-down but one to be built-up. Therefore, the proper application of OODA theory would be to get inside the learners’ OODA loops, to manipulate their orientation bypass their decision making in order to change their implicit knowledge (Osinga, 2007). An instructor knowledgeable informed by OODA theory seeks to reorient learners.

In learning new words, to use as an example that teaches useful information, instructors wish to present an example of a new word in use, display what the word symbolizes, and explicitly define the word (Stahl, 1986) though too much information impedes performance (Igo, Kiewra, & Bruning, 2004; Igo, et al., 2007). That is, instruction is harmed by disorientation, even when the information that’s impeded cognition would by itself be useful (Kalyuga, Chandler, & Sweller, 2000, McCrudden, et al, 2004). Likewise, techniques that avoid disorientation by emphasizing materials for learners improve instruction (Kiewra, 1985; Titsworth, 2004; Titsworth & Kiewra, 2004 Neef, McCord, & Ferreri, 2006), beecause cues requires learners to make less decisions.


Laboratory instruction that does not attempt to teach useful information also finds the value of reorientation. One such arbitrary task is the Dunker radiation problem, which requires learners to discover that two separate lines of radiation are needed to kill a tumor (Dunker, 1926; Leech, Mareschal, & Cooper, 2007). Instruction in this program has focused on giving a one implicit or explicit clue, which still does not produce majority-correct performance (Gick & Holyoak, 1980), to repeated implicit practice, which does produce majority-correct answers (Thomas & Lleras, 2007). This result has been confirmed using other arbitrary tests (Schmidt, et al., 2007).

The central finding of both the practical and arbitrary instructional experiments is that learners, in the context of instruction, are best seen as passive. Or, more precisely, the conscious decision-making minds of learners should be recognized as passive. Orientation, and not decision, is the proper focus of instruction and therefore reorientation is the instructor’s trusty tool.


OODA Alpha, a tdaxp series
1. Abstract
2. Dual Processing Systems
3. The OODA Loop
4. Decision
5. Orientation
6. A Theory of Mind
7. Reorientation
8. Disorientation
9. Education
10. Instruction
11. Student Interaction
12. Creativity
13. Conclusion
14. Bibliography

OODA Alpha, Part IX: Education

Twice, Boyd (1986) includes headings that read “? Raises Nagging Question ?” (27, 71). These headings are used to draw attention to a problem drawn by above statements. In the same way, the discussions above on orientation and decision, and the meta-cognitive processes of reorientation and disorientation, raises the nagging question how to apply the OODA loop to education. Clearly, some aspects of the OODA loops of a student population are beyond control. Managed heterosis in order to improve genetic heritage would may only a slight improvement in performance (Mingroni, 2007) at a socially unacceptable cost (Graves, 2001), while informed social engineering (Skinner, 1976) has produced only mixed results (Kinkade, 1973; Kuhlmann, 2005). Similarly, learners come from a whole range of prior experiences (). In the next section, therefore, applications of the OODA loop are considered which speak to var only new information. Indeed, the presentation of new information intended to influence learning is the definition of teaching (Eisner, 1964).

The next three sections are organized in order of decreasing educator control. First, the instructional environment, where an educator interacts directly with a student, is examined. Second, the academic environment, where learners interact with each other under rules devised by the educator, is explored. Finally, the creative environment, where the only educators are those of the field in a domain that a learner chooses to engage, is discussed. The focus also shifts from the need to implicitly alter orientation on the spot, to the requirement to selectively disorient, and finally the need for long-term improvement in learner orientation. Therefore, the following section can be viewed as the journey from reorientation to disorientation, and back again.


OODA Alpha, a tdaxp series
1. Abstract
2. Dual Processing Systems
3. The OODA Loop
4. Decision
5. Orientation
6. A Theory of Mind
7. Reorientation
8. Disorientation
9. Education
10. Instruction
11. Student Interaction
12. Creativity
13. Conclusion
14. Bibliography