Human Cognition: Embodied Views of Learning in Engineering and Technology Education

By Zanj K. Avery

Abstract

This paper explores the status of research pertaining to cognitive learning, as it relates to embodied cognition and its implications for engineering and technology education. The objective was to synthesize or unify concepts and principles involved in cognitive research with engineering and technology education as well as to present instructional strategies that enhance learning by considering how the mind, body and environment interact to form human perception. Moreover, the importance of making connections between abstract educational topics and real world events is discussed as it concerns providing relevant reference frames for learning.

Section I: Overview
Embodied Cognition in Engineering and Technology Education


Introduction

Engineering and technology educators seek to continuously enhance the educational experiences of their students. Modern day pedagogy strives to prepare a diverse population of technologically literate students while increasing accountability regarding the effectiveness of engineering and technology education programs. Because of the diverse populations involved in the engineering and technology-related educational programs, it is imperative that educators consider the way in which the mind, body and environment interact with each other in order to develop methods for teaching that enhance cognitive abilities and skills. Moreover, particular interest lies in preparing students to be productive in a culturally diverse world. Because we live in a world that is so diverse it should be of particular interest for educators to learn more about how an individual’s environment, and human biological system (mind and body) work together to form our perceptions of the natural universe.

The basic premise of embodied cognition addresses a multitude of diversity issues as it concerns how an individual best learns and helps one to understand the dynamic interchange between the mind, body and environment plus how these elements interact to facilitate the development of meticulous cognitive capacities (http://www.iep.utm.edu/). Fundamental to these efforts is a realization and aspiration to be more learner-centered in engineering and technology education practices. These practices should ensure that our educational practices identify the individuality of students (Turns, Atman, Adams, & Barker, 2005). Society, as a whole, is responding to this need with instructional principles and strategies that place importance on pedagogies that have been demonstrated to be diversely effective.

Purpose

This synthesis paper explores a range of concepts and principles related to cognitive research, especially as it relates to embodied cognition, with the objective of ultimately unifying these concepts and principles with engineering and technology education. Hence, this study explores several themes among a complex body of information (i.e., cognitive science) and attempts to develop an understanding of these themes as they relate to embodied cognition and its relevance to engineering and/or technology education. Furthermore, this line of research is conducive to discovering aspects of Engineering and Technology Education (ETE) that can be enhanced through embodied forms of meaning. In addition, this research will complement the ever increasing body of knowledge in the study of how to most effectively teach seemingly complex math and science concepts and principles that are inherent within engineering and technology education. These aspects will, in turn, illustrate the importance of embodied cognition in relation to engineering and technology education, while reflecting on ways to elucidate abstract concepts and principles.

The organization of this paper is as follows: Section II presents background literature and intellectual precursors regarding embodied views of cognition. In addition, Section II discusses fundamental ideas that are the theme of this paper including contemporary viewpoints regarding: a) the nature of knowing, b) the way of knowing and the impact on educational principles and strategies, plus c) the value of knowing, and a discussion of ideas regarding pedagogical approaches to enhancing the knowledge of engineering and technology students via the design process. Note: Each section presents an account on an analysis of these strategies, and exploits the results of the analysis to contemplate prospective research opportunities. In Section III, I conclude with a review and synopsis.

Section II: Background, intellectual antecedents, and pedagogy

The Nature of Knowing: Cognitive research (in general)

The mental process by which knowledge is obtained is called cognitive learning. Cognitive learning involves intellectual activities such as thinking, reasoning, remembering, imagining, or learning words. Cognitive science or the study of thinking and learning extend over across a wide variety of disciplines from developmental psychology to medicine. Engineering and technology education is no exception. Cognitive science, in relation to engineering and technology education, provides a foundation for understanding the nature of how the human mind interprets, analyzes and solves technical problems. Cognitive researchers attempt to discover if everything that humans know, such as, history, scientific knowledge, religious and political beliefs are shaped by humans through their language and vocabulary or, are there some aspects of thought that are universal (Notess, 2001). For example, 2+2=4 is a statement that is undistorted by emotion or personal bias and has the same connotation for everyone. Literature reveals that researchers in very diverse fields have embraced cognitive theories for developing instructional principles and strategies for teaching and learning. These theories can be quite informative to engineering and technology educators as they strive to augment the cognitive reasoning skills of their students, especially as it relates to the communication of abstract academic concepts and principles (e.g. math and science).

The Way of Knowing: Constructivism and Cognition

Per the constructivist view of learning, education is student-centered; students have to construct knowledge themselves; learning is an extensive progression of accumulating new information and adding it to what is already known. Moreover, the understanding of applied math and science concepts, in conjunction with engineering and technology related concepts, involves a multitude of mental processes, including aspects such as awareness, perception, reasoning, judgment and/or intuition. The development of these mental processes requires a system of learning/teaching that a) reminds students about what they already know, b) makes use of analogies and metaphors, c) makes distinctions between new and old information, d) establishes a purpose for what is to be learned, e) encourages students to generate thought provoking questions, and f) encourages teachers to design activities based on real world situations. These associations allow the learner to understand and value the workings of nature and the universe.

Intellectual Precursors: Classicist versus Embodied View

Those who promote constructivism concur that cognitive structures that influence adaptive behavior is the result of an individual’s perception of stimuli from his/her environment, rather than the actual stimuli (Huitt, 2003). This classicist view of cognition, neglects the role that the body plays in our perception of the world. Wherein the classicist view of cognition is mechanistic in nature and perceives the mind as a computer processor, embodied cognition identifies how our concepts are principally influenced by our physical form. In other words, the way we view the world is dependent on and is a function of our incarnation as human beings. Although the works of such philosophers as Piaget [who viewed children as active (versus passive) explorers who construct their own theories of knowledge], Vygotsky (who was influenced by the works of Piaget and regarded culture as a defining force in the development of cognitive abilities and skills), and Dewey (who believed that the totality of human knowledge was an aggregate of acts consisting of the interaction of human beings with one another complemented by natural occurrences in their environment including interactions with animals, plants and all types of other objects and phenomenon), helped plant the seed for this field of research, embodied cognition is deeply rooted in traditional anti-Cartesian approaches (Wikipedia, 2006). Roots of embodied cognition stem from ideals such as Immanuel Kant’s skepticism about having a knowledge that is restricted or apart from the body and bodily interactions with the environment (Wikipedia, 2006). Immanuel Kant, in his pre critical period, endorsed an embodied view of learning that concerned the mind-body problem that closely parallels the modern view of embodied cognition.

Kant’s Universal Natural History, published in 1755, explores the mind-body problem (the philosophical examination of the precise nature of the mind, mental events, mental functions, mental properties, and consciousness, and their interaction with the physical body), is an antecedent of our modern view of embodied cognition (Wikipedia, 2006). These views align with the paradigmatic orientation of : a) contextualism wherein emphasis is placed on the context in which an action or expression takes place and the focus on change entails exclusive, situated, personal events, and b) organicism which focuses on the dynamics of variation and change is a biological principle that accentuates the organization rather than the composition of organisms (Wikipedia, 2006).

Proponents of embodied cognition, such as George Lakoff and his various co-authors including Mark Johnson, Mark Turner, and Rafael E. Núñez, view the mind as being invested with bodily nature and form. According to Lakoff and Johnson (1999), the principal tools that gives us the capacity to discern or penetrate the true nature of a situation is metaphorical comprehension. Other philosophies such as conceptual blending and existentialism echo the sentiments of embodied cognition (Lakoff and Johnson, 1999). Although views vary within disciplines that support the embodied view of cognition, it does not endorse the mechanistic or stored description model of classical cognitivist but instead promotes the coupling metaphor of the mind as it relates to the interplay of the mind, body, and environment plus the governance of goal-directed action as it progresses in real time (The Internet Encyclopedia of Philosophy, 2006).

Understanding the theoretical framework of embodied cognition helps establish a basis for the integration of project-based/hands-on (employing the use of one’s sensorimotor and/or psychomotor abilities) activities that facilitate student’s comprehension of seemingly abstract concepts and principles. These types of activities are commonplace within engineering and technology-related curriculums. Notwithstanding the implications that embodied cognition has in relation to engineering and technology education, it is critical that such project-based activities (i. e., hands-on learning) provide a relevant reference frame for students to explore their individual interests. Embodied cognition cannot accomplish these objectives alone (Note: Just because an individual embodies knowledge does not necessarily imply that an event is relevant or, for that matter, interesting or meaningful). In order to institute and sustain successful engineering and technology education programs, an examination of the cognitive underpinnings that yield effective learning is exigent and at the same time, momentous.

Bruner’s Framework: Cognition in Engineering and Technology

Although Jerome Bruner is not regarded as a proponent of embodied cognition, his overall theoretical temperament lays a foundation for and, in effect, complements the ideals of embodied views of learning (especially as it concerns math and science education). Moreover, Bruner’s theories support and reinforce many of the pedagogical approaches adopted by engineering and technology educators. Bruner’s work is particularly popular amongst technology educators due to his general framework for instruction based upon the study of cognition. While technology educators seek identity and recognition amongst their peers in the domain of general education, Bruner’s work presents a strapping rationalization for the emphasis that technology education places on project-based (hands-on) activities.
Child development research laid much of the groundwork for the theory (especially Piaget, 1972). The ideas outlined by Bruner (1960) originated from a conference focused on science and math learning. Bruner’s theory is exemplified in the context of mathematics and social science programs for young children (Bruner, 1973). Bruner’s (1966) position is that instructional strategies concentrate on the following four major components: 1. Predisposition towards learning, 2. The ways in which a body of knowledge can be structured so that it can be most readily grasped by the learner, 3. The most effective sequences in which to present material, and 4. The nature and pacing of rewards and punishments. Good methods for structuring knowledge should result in simplifying, generating new propositions, and increasing the manipulation of information. Although these components address important aspects of learning, they do not mention the importance that culture and the environment play in the development of cognitive skills and abilities.

More recently, Bruner (1986, 1990) has extended his theoretical framework to include the social and cultural viewpoints of education per the following: 1. Instruction must be concerned with the experiences and contexts that make the student willing and able to learn (readiness), 2. Instruction must be structured so that it can be easily grasped by the student (spiral organization), 3. Instruction should be designed to facilitate extrapolation and or fill in the gaps (going beyond the information given), 4. Knowledge about one's own cognitive system; thinking about one's own thinking; essential skill for learning to learn, 5. Includes thoughts about (1) what we know or don't know and (2) regulating how we go about learning (Bruner, 1986, 1990). Note: From this standpoint, it appears that Bruner has crossed a significant threshold by recognizing the importance of contextual learning.

A major theme in the theoretical framework of Bruner is that learning is an active process in which learners construct new ideas or concepts based upon their current/past knowledge. The learner chooses and transforms information, forms hypotheses, and makes judgments, relying on a cognitive structure to do so. Cognitive structure, more specifically schemata, and mental models, provides significance and organization to experiences and allows the individual to "go beyond the information given".

Apparently, Bruner’s theories make no connection as to how the mind, body, and environment interact, however, the impact of his theories categorically lays a foundation for engineering and technology educators (especially as it pertains to math and science) to examine the implications of embodied cognition.

Embodied Cognition, the Design Process, and Engineering and Tech Ed

It is well known that engineering design and technological innovations are stimulated by natural (environmental) and/or social phenomenon (constructionist view of learning). For example, mechanical engineers may conduct a study concerning ergonomics in order to embody or better understand the comfort levels of human beings which, in turn, informs the design of more comfortable types of office chairs or computer keyboards. Another example is the way in which mechanical engineers may conduct a study to learn more about how small insects are able to navigate in flight. These opportunities help the designer to embody or better comprehend the control surfaces that allow small insects to fly which, in turn, informs the design of small (hand held) flying machines. From this perspective, we can see the usefulness of embodiment cognition as it relates to the engineering design process.

These same viewpoints should be considered and applied in the general educational field as it concerns knowing what students know (the phenomenon). This approach can assist in helping educators to design the most effective educational curricula (I.e. Experiences, assessment tools). In engineering and technology education, this line of thinking can also be employed to support design activities that assist students in situating meaning to complex topics while enhancing higher-order cognitive abilities and skills. Hence, educators should continue to take interest in research that illuminates what engineering and technology students know about their respective fields of study (Turns, Atman, Adams, Barker, 2005). Moreover, educators should consider methods that assist students in the embodiment of knowledge so that they are provided relevant reference frames for students to rehearse real world situations.

The Value of Knowing

Ideas concerning what engineering and technology students know, what facets of knowledge are crucial to engineering and technology, and methods for gaining insight into that knowledge are integral parts of the roles of engineering and technology educators (Turns, Atman, Adams, Barker, 2005). Bearing in mind the implications for embodied cognition in engineering and technological pedagogies, consider the following state of affairs:

· When a technology teacher in a fluid power class determines a suitable balance between theory and hands-on based learning in order to prepare students for real world situations that constructively discerns activities that mirrors an awareness of necessary knowledge and the level of knowledge students are likely to exhibit.
· When design engineering instructors invite practicing engineers into the classroom to discuss expected misunderstandings (e.g. skepticism about the significance of physics concepts in engineering design), they are utilizing their understanding of common disbeliefs to make intelligent teaching decisions.

. When industry and universities collaborate to develop curriculum that enhance students’ synthesis skills to counterpart their analytical skills, this reinforces the important types of knowledge (i.e., synthesis and analysis), in conjunction with the types of knowledge students need in order to make a successful transition from school to career.

The aforementioned examples lay a foundation for engaging in research related to embodied cognition in engineering and technology education. Moreover, research regarding existing student knowledge (including who knows what), and the context (framework) in which learning occurs. For example, the situations above are areas of teaching that echo semantic (declarative) knowledge, procedural knowledge, knowledge organization, and meta-cognition. These concepts are central to the erudition of knowing (Branford & Brown, 1999). Declarative knowledge (knowing what) refers to generalized knowledge that is for the most part universally accepted. In other words, it is knowledge that is commonly agreed upon. Its counterpart, procedural knowledge (knowing how) refers to the ability to act or knowledge used to control psychomotor skills. In contrast to declarative knowledge, procedural knowledge is acquired through experience and is discipline specific or not that generalized (Johnson, 2005). Both declarative and procedural knowledge denote groupings for describing general knowledge.

Conditionalized knowledge refers to knowing when to use it, deciding what to do and how to do it. It is related to meta-cognition, which refers to the concept of thinking about one's own thoughts. According to Douglas J. Hacker (1998) from the University of Memphis, “Those thoughts can be of what one knows (i.e., metacognitive knowledge), what one is currently doing (i.e., metacognitive skill), or what one's current cognitive or affective state is (i.e., metacognitive experience)”. It is necessary to reflect on the basis of metacognitive thoughts in order to segregate metacognition from other sorts of thinking: Metacognitive thoughts do not stem directly from a person's external reality; rather, their source is linked to the person's inner mental images of that reality, which can include what one knows about that internal image, how it operates, and how one feels about it (Hacker, 1998). The importance of knowledge integration and meta-cognition are manifested in the findings indicating that experts possess knowledge that is more strongly organized and deployed more effectively than novices (Chi, Glaser, & Farr, 1988). Research on expertise has indicated that experts exhibit attentiveness of their own knowledge including its limits and are able to make more informed decisions regarding the processes that they use (i.e., metacognition).

These ideas also mirror a perception of the discipline-specific knowledge that is conducive to becoming an engineer and/or a technologist or an engineering and technology educator. For instance, the aforementioned examples make reference to knowledge about fluid power, the role of physics in engineering and the ability to synthesize. The recognition of the critical components of technology-related knowledge is not a minor issue and has caused much dialogue among educators (Turns, Atman, Adams, Barker, 2005).

Mental models are pertinent for engineering and technology educators because they help to form mental images or representations of physical systems and objects (Johnson and Thomas, 1994). As research advances in this field, evidence is surmounting that indicates the mental models that influence decisions and behavior can vary depending on the situation, environment, and/or the context of learning. This, in turn, increases the difficulty of making generalizations regarding outcomes that transverse the differences between task and knowledge domains (Doyle, 1997). Central to the idea of acknowledging the individuality of students is identifying their cognitive abilities and processes used in learning.

The study of knowledge acquisition informs us as to how we gain knowledge. There is a reciprocal effect between the short and long term memory. To bring in new information, it is important to process new information and connect it with information contained in the long term memory bank. According to Harris (2005), the ultimate objective for both teacher and student is long-term memory:

Once information enters sensory memory and processes in short-term memory, it can enter and be organized in this unlimited and highly stable area in the student's mind. Learning has truly taken place when information can be recalled from the student's long-term memory. Using a computer as a metaphor for memory, the short-term phase is RAM (highly volatile and easily lost when something else is entered) while long-term memory is the hard drive or diskette (the information is there even after the machine is turned off). This metaphor is especially helpful because a computer knows the address of each bit of information because of the manner information is entered. It is essential that information placed into a student's long-term memory be linked in a way that the student can retrieve it later. The teacher who understands the relationship between memory and retrieval can gear a lesson plan to assist the student in the process which enhances learning.

A multitude of processes exist for the teacher in helping students to retain information over a long period of time (Long term memory). The key to higher retention is linking the information to something meaningful to the students. Harris (2005, para. 9) explains, “While rehearsal is important to short-term memory, it can also be used to transfer information to long-term if it is linked with something meaningful to the students.” A technology education teacher might, for example, connect sports with some aspect of physics. Repeating this connection multiple times will transfer it into long-term memory where it can be recovered because of the connection made with sports. For a sports fan this provides a relevant frame of reference for the particular physics concept(s) to be assimilated.

“Elaborating or making material memorable will also enhance the student's learning process” (Harris, 2005, para. 9). For instance, a demonstration showing a gyroscope in action will convey the concept of gyroscopic effects better than simply trying to explain it to the class. Instructional strategies, such as, demonstrations, can enhance a students ability to embody knowledge, make connections with real world events, plus help cultivate deeper interest by providing a reference frame that engages the learner through situated (interactive/hands-on) experiences. Over the years, a major concern for math and science educators is the poor performance of middle and high school students in comparison to other nations. (NSTA, 1999). Education can benefit greatly through the integration of more project based-learning and hands-on activities that helps students embody abstract concepts and principles while grounding theoretical assumptions in a manner that is socially constructive. Hence, the prominence of applied math and science as part of (pre-) engineering programs plus the emphasis that technology education places on interactive hands-on learning experiences can serve as a mechanism to promote higher order cognitive abilities and skills. In order for students to see the relevance of their learning, it is vital that students are afforded the opportunity to explore academic topics through embodied experiences. Hence, areas wherein math, science, engineering, and technology standards overlap should be capitalized on.

Section III: Summary and Coclusion

In sum, let us reconsider Bruner’s general framework for instruction based upon cognitive research as it relates to embodied views of learning. Bruner’s framework sheds light on a person’s predisposition towards learning, wherein the initial interest of the learner plays a major role in the education process. In other words, the learner has to be somewhat interested in what is being taught in order to develop his/her higher-order cognitive abilities. Otherwise, the learner loses interest quickly (Bruner, 1986, 1990). From this, educators must be concerned with the experiences and contexts that make the student willing to learn, as well as, structuring information so that it can be easily embodied by the student. Per the constructivist view of learning, students have to build knowledge themselves while accumulating new information and adding this new information to what is already known. Embodied cognition as it relates to engineering and technology education facilitates learning of abstract academic subjects plus imparts a relevant reference frame for student to better situate learning. This type of pedagogy also facilitates “deep thinking”, and, in turn, encourages students to generate questions, explanations, and summaries regarding a multitude of academic concepts and principles.

Conclusion
Although embodied views of learning provide a foundation for understanding the nature of how the human mind interprets, analyzes and solves technical problems, forming connections between thinking and behavior can be elusive and, at the very least, misleading. Apparently, this presents a major dilemma when taking into account an individual’s personal knowledge, intellectual skills, attitudes, etc (Doyle, 1997). Hence, variables, such as learning contexts, situational variables, emotions, and learning outcomes, are important factors in producing explicit, adaptive behavior. According to Doyle (1997), these variables (i.e., attitudes, mental models, scripts, and schemas) are obviously linked to behavior, but the association is often multifaceted and contrary to what common sense would have us believe. Keeping these issues in mind, we must recognize that there is much we do not understand about human cognition. But by acknowledging that our minds are embodied in a form that enables us to successfully interpret abstract ideas, interact with and endure the adverse forces of our natural environment (via the creation of technology), we have truly set the stage for greater understanding into the essence of human existence.

References

Adams, R.S., Atman, C. J., Barker, T., and Turns, J. (2005). Research on Engineering
Student Knowing: Trends and Opportunities. Journal of Engineering Education.

Bransford, J.D., Brown, A.L., and Cocking, R.R., (1999.), How People Learn: Brain
Mind, Experience, and School. Washington, D.C.: National Academy Press.

Brown, A. L. (1978). Knowing when, where, and how to remember: A problem of
metacognition. In R. Glaser (Ed.), Advances in instructional psychology (Vol. 1). Hillsdale, NJ: Erlbaum.

Bruner, J. (1960). The Process of Education. Cambridge, MA: Harvard University Press.

Bruner, J. (1966). Toward a Theory of Instruction. Cambridge, MA: Harvard University
Press.

Bruner, J. (1973). Going Beyond the Information Given. New York: Norton.

Bruner, J. (1983). Child's Talk: Learning to Use Language. New York: Norton.

Bruner, J. (1986). Actual Minds, Possible Worlds. Cambridge, MA: Harvard University
Press.

Bruner, J. (1990). Acts of Meaning. Cambridge, MA: Harvard University Press.

Chi, M.T.H., Glaser R., and Farr, M.J. (1988). The Nature of Expertise. Hillsdale, N.J.:
Lawrence Erlbaum Associates.

Doyle, J. K. (1997). The cognitive psychology of systems thinking. System Dynamics
Review, 13(3): 253-265.

Feil, Adam J. (2002). Talking Physics: How the Ability to Communicate
Physics Concepts Affects Learning. Retrieved November 21, 2005, from http://www.physics.uiuc.edu/research/PER/Adam/adam_thesis.pdf#search=

Hacker, Douglas J (1998) Metacognition: Definitions and Empirical Foundations
Retrieved December 1, 2005, from http://www.psyc.memphis.edu/trg/meta.htm

Harris, Doug. (1995). Cognitive Learning and Memory. Retrieved November 16, 2005,
from http://comp.uark.edu/~jdharris/cogmem.html

Huitt, W. (2003). Metacognition. Educational Psychology Interactive. Valdosta, GA:
Valdosta State University. Retrieved November 11, 2005, from
http://chiron.valdosta.edu/whuitt/col/cogsys/metacogn.html.

Internet Encyclopedia of Philosophy (2006). Embodied Cognition. Retrieved April
18, 2006 from http://www.iep.utm.edu/e/embodcog.htm

Johnson, Scott (2005 September 5). Knowledge Representation and Mental Models. Session presented for the National Center for Engineering and Technology Education: Cognition Course, online.

Johnson, Scott D., Thomas, Ruth, G. (1994). Implication of Cognitive Science for
Instructional Design in Technology Education. The Journal of Technology Studies, pg. 34.
George Lakoff and Mark Johnson. Philosophy In The Flesh: the Embodied Mind and its
Challenge to Western Thought. Basic Books, 1999.

McGee, Bruce G. (1997). Multimedia - Effectiveness in the Learning Environment:
A Review of Literature. Retrieved October 30, 2005, from,
Nash, Patrick L. (2005). A Message From The Chair. Retrieved November 15, 2005,
from, http://physics.utsa.edu/about%20us.htm.

Notess, Charles (2001). Glossary. Retrieved October 28, 2005, from
www.greeleynet.com/~cnotess/gloss.htm.

National Science Teachers Association (1999). Nation's Science Teachers Register
Concern over U.S. Science Education in New Survey. Retrieved December 6, 2005, from http://www.nsta.org/368/

Piaget, J. (1972). The psychology of the child. New York: Basic Books.
Hacker, Douglas J (1998) Metacognition: Definitions and Empirical Foundations
Retrieved December 1, 2005, from http://www.psyc.memphis.edu/trg/meta.htm

Lakoff and Johnson (1999). Philosophy in the flesh: The embodied mind and its
challenge to western thought. New York: Basic Books.

Wikipedia (2006). Embodied philosophy. Retrieved on April 28, 2006 from
http://en.wikipedia.org/wiki/Embodied_cognition

Wikipedia (2006). Contextualism. Retrieved on April 30, 2006 from
http://en.wikipedia.org/wiki/Contextualism#External_links.

Wikipedia (2006). Organicism. Retrieved on April 30, 2006 from
http://en.wikipedia.org/wiki/Contextualism#External_links)