The learning process that characterizes the design studio can be examined in light of a number of different learning theories, learning styles, and their associated teaching approaches. While over fifty different learning theories have been catalogued at Greg Kearsley's Theory Into Practice database, the most well-known and widely subscribed to theories of learning can be divided into three areas: behaviorism, cognitivism, and constructivism. A matrix of learning theories with their associated instructional strategies can be found at Nada Dabbagh's Instructional Design Knowledge Base website at the Graduate School of Education at George Mason University.

Behaviorism

A behaviorist approach centers on learning behaviors through a process of stimulus and response (Pavlov's dog and Skinner's rats) or operant conditioning. Correct responses are rewarded, while incorrect responses are penalized. Knowledge and skills are sequenced through a series of small, logically-connected steps, and learning has been attained when a "correct" response is consistently given to a particular stimulus or input. This approach is grounded in an objectivist philosophy: the world around us is an objective, finite reality, and operates through a system of rules and laws (such as the laws of physics). Behaviorist learning objectives seek observable and measurable behaviors from the student.

Teaching strategies that are based on a behaviorist approach include drill and practice, recall of facts, and developing an ability to define, illustrate and explain concepts as they have been defined by others. Student performance is measured by "objective" tests in which there is a set of correct and incorrect answers. Behaviorism is the basis for the "programmed instruction" of the 1960's and 1970's, in which a student could learn through interaction with a computer. Branching logic in the program allows the learner's actions to determine what problems and choices are subsequently presented. "Expert systems" and video games are examples of behaviorism in a highly advanced, electronic form.

This approach to teaching is characteristic of primary and much of secondary education throughout the world, in which the student is regarded as an empty vessel to be filled with knowledge from a source (the teacher); it also continues to dominate much of post-secondary education. In an architectural curriculum, a student might experience a behaviorist approach to learning in many of the subjects taught in the traditional classroom (particularly large lecture courses), where students are expected to learn established facts, concepts and procedures. Students are evaluated against fixed grading criteria through the use of multiple choice, short-answer and essay examinations. In the age of beaux-arts design, a student would be expected to master the systems of proportioning and architectural details (established by the master architects of the past) to develop a "correct" solution to a problem.

Learning the more objective aspects of architecture relies heavily on behaviorist teaching approaches. A student is expected to acquire knowledge of technical constraints as well as an understanding of the symbolic, psychological and aesthetic impact of design decisions. An architect does not have complete freedom in design. For example, design standards and building codes dictate the maximum slope of a ramp or the height of a railing. Scientific formulas must be applied to determine the size that a beam must be to support a given load. Considerations of heat gain militate against having large expanses of clear glass on a south-facing wall. Some standards are more subjective: one must develop a "feel" for how wide a corridor must be to accommodate a certain amount of traffic, how the height of a ceiling or the size of a room affect one's sense of confinement or openness, or how the bulk and appearance of a building will complement or conflict with that of surrounding structures. In Kvan's terms, such assimilated knowledge governing one's behavior is "knowing in action." In the studio, "correct" behavior is reinforced through positive feedback from peers and the design instructor in desk crits, pinup sessions and formal reviews; "incorrect" behavior can be subject to sometimes humiliating critiques in front of one's peers.

Cognitivism

Cognitivism, like behaviorism, is predicated on an objectivist view of reality (Vrasidas, 2000, p. 2). However, it focuses not so much on behavior as on the mental processes. Learning is defined as a change in one's state of knowledge: the learner is an active participant in encoding, structuring, storing and processing information. Learning has occurred when the student is able to organize and retrieve information in a meaningful way. Students are encouraged to build upon prior knowledge to develop new associations. The instructor has an expanded role: the task is not only to deliver information, but also to assist learners in organizing it in a logical, meaningful way, developing an ability to see it from different perspectives and to draw associations or analyze it. An architectural theory class embodies a cognitive approach: students might be encouraged to consider how climate has affected indigenous building forms that the student initially learned about in an architectural history class that was presented along traditional lines in terms of historical eras and geographical areas.

Bloom's taxonomy of educational objectives, developed in the 1950's, is a widely accepted model of learning. This system of identifying educational objectives addresses three domains: the cognitive (thinking and problem-solving skills), the affective (attitudes and value systems), and the psychomotor. Bloom's cognitive domain, of most interest to educators, involves the following levels (Felder and Brent, 2004; Harb, Table 6, p. 31):

1. knowledge—the remembering of previously learned material
2. comprehension—the ability to grasp the meaning of material (lowest level of understanding)
3. application—the ability to use learned material in new and concrete situations (a higher level of understanding)
4. analysis—the ability to break down maetrial into its component parts so that its structure may be understood (requires understanding of both content and structural form)
5. synthesis—the ability to put parts together to form a new whole
6. evaluation—the ability to judge the value of material for a given purpose

Although such a hierarchical list only contains one dimension, the model is frequently illustrated as a triangle or pyramid, conveying the notion that one would climb through successively "higher" levels of understanding:

Bloom's Taxonomy: Cognitive Domain. (from Atherton, 2003)

Behaviorist techniques are considered adequate for achieving learning at the lower two or three levels at the higher. Engineering educators such as Felder and Harb associate various teaching and learning activities with the levels of Bloom's taxonomy and the quadrants of the Kolb experiential learning cycle (see Kolb-McCarthy Experiential Learning Cycle, infra):

Bloom's Taxonomy of Educational Objectives
Level	Description	Kolb quadrant
Knowledge	repeating verbatim	2
Comprehension	demonstrating understanding of terms and concepts
Application	applying learned information to solve a problem	3
Analysis	breaking things down into their elements formulating theoretical explanations designing mathematical or logical models for observed phenomena	2
Synthesis	creating something combining elements in novel ways	4
Evaluation	making and justifying value judgments or selections from among alternatives	1

Felder criticizes the fact that most engineering lectures and assignments focus almost exclusively on the application of learning, level 3 of Bloom's taxomony. Students are not presented with design problems in which they are called upon to synthesize their knowledge until the the end of a course or the conclusion of their studies in a "capstone" course. These engineering educators observe that without higher-level teaching, schools produce graduates who are ill-equipped to do "modeling, design, and critical and creative thinking" (Felder and Brent, p. 9). In contrast, architectural education, employing problem-based learning in all four or five years of the design studio, is designed to reach Bloom's "higher-order" cognitive skills—analysis, synthesis, evaluation.

The differences in the educational approach of these delated disciplines can help explain the difficulties encountered when architecture and engineering students are put together in collaborative design projects (a rare occurrence). In one such exercise at MIT, "the architecture students' view of designing was fundamentally different than the engineering student's view because they considered the design process not as a problem-solving activity but rather as an activity that required finding structure to an ill-defined and complex problem by problem-setting," while to the engineering student, design was about "problem-solving and optimization" (Yee, p. 94)

Constructivism

Constructivism, a learning theory that emerged in the early 1990's, rejects the objectivist view of reality and the idea that simply "communicating content to students will result in learning" (Jonassen, 1994, 1995), the "shovelware" approach reflected in some distance education courses. Constructivism would reject a linear, teacher-dominated instructional plan that defines learning objectives in advance in culminates in an objective assessment of observable behavior. Rather, it takes the view that each learner constructs his or her own subjective reality (i.e., creates meaning) through active engagement with the environment, the content, the teacher, and other learners. In Vygotsky's social constructivism, a community of learners, through their interactions and negotiations, may develop a largely-shared view of reality while recognizing the existence of a diversity of perspectives. Constructivism is focused on individual learning (meaning-making) rather than upon teaching; the instructor's role changes from being a conveyor of knowledge to one who facilitates (but does not completely control) an educational "transaction" promoting the development of the learner's thinking skills. Evaluation of learning is continuous, and is carried out by both the teacher and learner; learning how to evaluate one's own cognitive development (the highest of Bloom's "pyramid" of educational objectives) is an integral part of the learning process (Garrison, 1993; Vrasidas, 2000).

Constructivist teaching strategies carry with them labels such as "collaborative" or "cooperative" learning, "learning communities," "problem-based," "discovery," and "hands-on" learning, all of which can be used to describe the design studio. The type of learning that has characterized the studio from its inception is now beginning to become part of the educational mainstream. While constructive principles characterize the wide-ranging graduate seminar in humanities, it can also be found in science and engineering education, where it can be found in the laboratory, computer simulations, and groupeork, where students are encouraged to build their own concepts Wankat & Oreovicz, 285-288).

In the emerging field of instructional design, aAnalysis of the users and their needs is a critical step%mdash;one that has long been part of the architectural design process. An understanding of students' learning styles can help educators structure the educational transaction and adjust their teaching styles to address the needs of all students in a class (Felder & Brent, 2004). Conversely, a variety of teaching styles can be used to help students experience and become more adept at using more than one method of learning. Of more than 30 different models of learning styles, six appear to be most helpful to an analysis of learning styles (Felder, 1996; Montgomery & Groat, 1998):

• Information processing:: Gregorc's Mind Styles model, involving two measures: abstract vs. concrete and sequential vs. random, defining four categories
• Physiological:: Hermann Brain Dominance Instrument, involving two measures: left brain v. right brain and cerebral v. limbic, defining four categories
• Information processing: Kolb/McCarthy Experiential Learning Cycle, involving two measures: a perception axis ranging from concrete experience (CE) to abstract conceptualization (AC) and a processing axis ranging from reflective observation to active experimentation, defining four different learner types
• Personality type: Myers-Briggs Type Indicator&mdash, involving four different measures (orientation, perception, decision-making style, and attitude), resulting in 16 (2⁴) different personality types
• Information processing: Felder-Silverman learning styles, involving four different measures
• Social interaction: Grasha-Riechmann Learning and TeachingStyles, involving 6 different learning styles, coupled with their associated teaching styles
• Information processing: Gardner's theory of multiple intelligences, which identifies eight different types of learning: visual, auditory, tactile/kinesthetic, etc.

Gregorc Mind Styles Model

Phenomenolgist Anthony Gregorc's "mind styles" model (http://www.gregorc.com) is based on a person's ability to mediate "channels" in which information is received and expressed. This tool is based on two different measures:

• Perception: Abstract (A) versus Concrete (C)
• Ordering: Sequential (S) versus Random (R)

This model can be illustrated as a simple 2x2 matrix, representing four transactional channels based on the combinations of "perception" and "ordering." Abstract perception involves visualizing data through reason, while concrete perception involves the physical senses. Sequential ordering can be considered reasoning through a linear or step-by-step method, while random ordering represents non-linear thinking. Most people tend to think in concrete rather than abstract terms; the opposite is true of their professors. The distribution of students in a food science and nutrition course (Ouellette, 2000, p.4) are shown in the chart below:

Gregorc Mind Styles Model
Ordering		Sequential	Random
Perception	Abstract	AS 15%	AR 27%
	Concrete	CS 41%	CR 19%

Herrmann Brain Dominance Model

Artist, musician, and GE's manager of management education Ned Herrmann's Brain Dominance Instrument (http://www.hbdi.com/hbdi/hbdi_information.htm) measures personal thinking preferences. This model examines which hemispheres of the cerebral cortex (conscious thinking) and limbic system (sensing, feeling, motor) dominate one's mental activity (Herrmann 1988).

• Hemisphere: Left versus Right
• Cortex: Cerebral versus Limbic

Each of the four factors are measured independently and plotted in the form of a "radar" chart, where the shape of the figure connecting the subject's scores indicates their preferred learning style. A subject could score high in both right-hand and left-hand thinking. Like gregorc's, this model can be illustrated as a simple 2x2 matrix, in which we can place Felder's characterizations of engineering professors and students are from Felder (1996).

Hermann Brain Dominance: sample profile (characteristic of an engineer). Source: http://www.hbdi.com/hbdi/prof_pack/profile_sheet.htm

Herrmann Brain Dominance Model
	Left Brain (verbal)	Right Brain (visual)
Cerebral	Quadrant A: Logical (engineering professors and students) problem solver mathematical technical analyser logical Learning preferences: quantitative analysis, theorizing, locically-processing	Quadrant D: Imaginative (some engineering students) conceptualizer synthesizer imaginative holistic artistic Learning preferences: exploring, discovering, conceptualizing
Limbic	Quadrant B: Organized   planner controlled conservative organizational administrative Learning preferences: organizing, sequencing, evaluating, practicing	Quadrant C: Interpersonal (some engineering students) talker musical spiritual emotional interpersonal Learning preferences: sharing, internalizing, moving/feeling, emotional involvement

Kolb-McCarthy Experiential Learning Cycle

In the model developed by social psychologist David Kolb (http://www.learningfromexperience.com), learning styles are measured on two perpendicular axes, representing perception (ranging from a preference for passive, reflective observation to active experimentation) and processing (ranging from a preference for concrete experience to abstract conceptualization).

• Perception: Active Experimentation (AE) versus Reflective Observation (RO)
• Processing: Concrete Experience (CE) versus Abstract Conceptualization (AC)

These axes define four quadrants, each of which is associated with a learner type. Traditional classroom teaching and textbook learning is concentrated in quadrant 2, appealing to "assimilators" who prefer reflective observation and abstract conceptualization, and employ deductive reasoning. Kolb argues that all learning styles can be addressed by progressing through a repetitive cycle of reflective observation, abstract conceptualization, active experimentation, and concrete experience. Using this approach, the higher levels of Bloom's taxonomy of educational objectives can be reached.As in the Herrmann model, each of the four factors are measured independently and plotted in the form of a "radar" chart. This model can also be illustrated by a 2x2 matrix, annotated to indicate the characteristics of each style, and indicating the distribution of engineering professors and students from Harb:

Kolb Learning Style Inventory: sample profile (characteristic of an engineering student). Source: Sutliff and Balwin (2001)

Kolb/McCarthy Experiential Learning Cycle
	Perception axis CE Concrete Experience Feeling/sensing: immersion in new experience
Processing axis AE Active Experimentation	Quadrant 4    Accommodators 10% of engineering professors 20% of engineering students Ask "What if?" inductive reasoners (derive theory from its parts) active, creative natural leaders, performers flexible, adaptable Learning strategy: self discovery, adaptive environments Disciplines: Education		Quadrant 1    Divergent thinkers 10% of engineering professors 10% of engineering students Ask "Why do I need to learn this?" creative innovative individualistic highly personal intuitive Learning strategy: questions and class discussion Disciplines: Social sciences, humanities	Processing axis RO Reflective Observation
Doing: lab work, testing	Quadrant 3    Convergent thinkers 30% of engineering professors 30% of engineering students Ask "How?" pragmatic strategic practical problem-solvers methodical Learning strategy: skill building, labs, field work Disciplines: Engineering		Quadrant 2    Assimilators 50% of engineering professors 40% of engineering students Ask "What do I need to know?" deductive reasoners (start with overall theory, fit parts into it) strong conceptualizers work with detail Learning strategy: professor dominated lecture, textbooks Disciplines: Physical sciences	Watching: observing from different viewpoints
	Perception axis AC Abstract Conceptualization Thinking: logical and systematic organization

Wankat & Oreovicz (p. 292-297) detail how Bernice McCarthy (http://www.aboutlearning.com/) developed a corresponding system of teaching strategies that includes both left-brain and right-brain activities in all four quadrants, beginning with Quadrant 1 and "teaching through the cycle," providing every student with challenges and an "opportunity to shine when the learning activity is in her or his favorite quadrant." As can be expected, lectures and reading assignments are strategies appropriate for Quadrant 2. Design, simulations and open-ended problems—characteristic of the design studio—share Quadrant 4 with actual work experience. According to the authors, most college education oscillates between Quadrants 2 and 3, never making the full circle.

Sutliff and Baldwin (2001) describe the instructional activities that can support different quadrants of this learning cycle. Harb argues that engineering students should be given design problems in all four years of study (not just the last), in order to take them through all parts of the cycle and address the skills of analysis, synthesis and evaluation (the three higher levels of Bloom's taxonomy in the cognitive domain). He explains the prevalence of the transmissive, lecture-based format in engineering education: "It is a learning environment that is preferred by at least half of our engineering educators and one that is readily accepted (and preferred) by a large fraction of our students" (Harb, p. 7). He presents evidence that incorporating the entire cycle in teaching has remarkable success, promoting the goals of improved thinking, problem-solving, communication, and the development of self-motivated learners.

Myers-Briggs Type Indicator

The Myers-Briggs Type Indicator (Consulting Psychologists Press, http://www.cpp.com/products/mbti/index.asp) is a widely used instrument to assess personality type, having been administered to millions. Though not without its critics (people's personalities are not a direct measure of how they learn), it gives us a general picture of how architects' personalities—and their associated learning styles—compare to others in the population. If distance education methods are to be employed in architectural education, they must take into account the types of learners and their learning styles.

The Meyers-Briggs personality assessment tool is based on four different measures, with each pole designated by descriptive word and a corresponding letter:

• Orientation to life: Extravert (E) versus Introvert (I)
• Perception: Sensing (S) versus Intuitive (N)
• Decision-making: Thinking (T) versus Feeling (F)
• Attitude to outside world: Perceptive (P) versus Judgmental (J)

In MBTI terminology, a personality designated as ISFJ (the largest single group) is introverted, perceives by sensing, uses feeling rather than thinking to make decisions, and prefers tangible evidence (judgmental) to insight and opinion.

David Keirsey (http://keirsey.com/) has found that people tend to fall into four major divisions, the most significant distinction being between those whose manner of perception is sensing (S) or intuitive (N). Among the sensers, the major division is based on attitude: the judgers (SJ or "guardians," shown below in red) and the perceivers (SP or "artisans," shown below in green). Among intuitive types, however, the main point of distinction is based on how they make decisions: the feelers (NF or "idealists," shown below in yellow) and the thinkers (NT or "rationals," shown below in blue). Keirsey has assigned various labels to each of the 16 possible MBTI combinations to describe the "temperaments" of each personality type. The term used to decribe the category "INTP"—an introverted, intuititive, thinking, perceptive type of personality—is the "architect". Four dimensions are difficult to represent in a 2-dimensional table; in the 4x4 matrix below, colors are used to show Keirsey's major groupings. The percentages indicate the distribution of each personality type in the general population (Falt).

Myers-Briggs Type Indicator (with Keirsey "temperaments")
Attitude	J  Judgmental					Perceptive  P
Perception	S  Sensing			NJ    Intuitive    NP					Sensing  S
Decision-making	SJ Guardians—46.4%			NF Idealists—16.4%					SP Artisans—27%
F  Feeling	SFJ Conservators—26.1%			NFJ Mentors—3.9%		NFP Advocates—12.5%			SFP Players—16.1%
	E	ESFJ Provider—12.3%		E	ENFJ Teacher—2.4%	E	ENFP Champion—8.1%		E	ESFP Performer—8.5%
	I	ISFJ Protector—13.8%		I	INFJ Counselor—1.5%	I	INFP Healer—4.4%		I	ISFP Composer—8.8%
				NT Rationals—10.4%
T  Thinking	STJ Monitors—20.3%			NTJ Organizers—3.9%		NTP Engineers—6.5%			STP Operators—9.7%
	E	ISTJ Inspector—11.6%		E	INTJ Mastermind—2.1%	E	INTP Architect—3.3%		E	ISTP Crafter—5.4%
	I	ESTJ Supervisor—8.7%		I	ENTJ Field marshall—1.8%	I	ENTP Inventor—3.2%		I	ESTP Promoter—4.3%

By adjusting the size of the table cells, the relative size of each group can be better visualized:

MBTI categories (cells sized by prevalence)
ESFJ 12.3%	ENFJ 2.4%	ENFP 8.1%	ESFP 8.5%
ISFJ 13.8%			ISFP 8.8%
	INFJ 1.5%	INFP 4.4%
ISTJ 11.6%	INTJ 2.1%	INTP 3.3%	ISTP 5.4%
	ENTJ 1.8%	ENTP 3.2%
ESTJ 8.7%			ESTP 4.3%

To reduce the difficulty of visualizing this four-dimensional classification scheme, the extraverts and introverts can be combined, giving us an 8-cell (2³) table. This can be represented as a 3-dimensional object—a segmented cube or a segmented sphere—where each of the three perpendicular axes represents one of the dimensions of the MBTI system. The segments can be sized according to the size of the population they represent. One can visualize the introvert-extravert dimension as a function of distance from the center: introverts would be clustered toward the inside, and extraverts would be found nearer to the outside surface. In the illustrations below, the colors used correspond to the categories in the tables above:

MBTI categories in scale as cubic segments     MBTI categories in scale as spherical segments

As can be seen, the introverted INTP "architects" (a personality type comprising 3.3% of the population), along with the extraverted ENTP "inventors" (at 3.2%) occupy one of the smallest segments; furthermore, they are directly opposite in temperament to the largest segment of the population, the "SFJ" type that includes "providers" and "protectors."

The distribution of architects and engineers by personality type has been studied by Durling (1996) and by Felder (2002). Durling, in a comparison of architecture, art and mechanical engineering students with the general population, found that artists predominated in the NF (intuitive-feeling, or the yellow) categories; architects were concentrated in the IN (introverted-intuitive, or the inboard portions of yellow and blue) categories; while engineers were concentrated in the NJ (intuitive-judgmental, or the left-hand blue and yellow) categories. Viewed in 3 dimensions, we see that engineers and artist share as many personality characteristics as engineers and architects; we can also see how their personalities differ.

Felder's investigations support these figures as to engineering students. Those having INTJ personalities are more successful as engineering students: N's (intuitives) were far more likely to succeed than S's (sensing types), and J's (judgmentals) had a slight advantage over P's (peceivers). NJ's experienced a 76% pass rate, while their opposites—the SP sensing perceivers, or upper green area) only passed at a 31% rate. The two other combinations—NP's (intuitive perceivers, or the right-hand yellow and green) and SJ's (sensing judgers, or red area)—succeeded equally well at 43%. The highly analytical NTJ personality type also does well in other academic disciplines: Randall (1995) finds that INTJ's are also more successful as law students.

Artists: NF (Intuitive, Feeling)		Engineers: NJ (Intuitive, Judging)		Architects: IN (Introverts, Intuitive)
Artists, Engineers and Architects: Different types of MBTI Intuitives

According to Felder (2002, p. 3), the different MBTI personality types prefer different types of instruction. Traditional types of instruction, and those most often utilized in distance education programs, are clearly biased toward INTJ personality types, providing some explanation for their success in school:

MBTI Instructional Preferences
Introverts	opportunities for internal processing	Extraverts	activity and group work
iNtuitors	conceptual understanding abstractions: theories and mathematical models	Sensors	concrete learning experiences clearly defined expectations memorization of facts, rote substitutions in formulas, repetitive calculations
Thinkers	logically organized presentations of course materials feedback related to their work	Feelers	instructors who establish personal rapport feedback showing appreciation of their efforts
Judgers	well-structured instruction clearly defined assignments, goals and milestones	Perceivers	choice and flexibility in assignments

Felder Learning and Teaching Styles

North Carolina State University chemical engineering professor Richard Felder has developed his own model, which employs four dimensions of learning styles (Felder and Silverman, 1988). Like the MBTI construct, these four factors lead to 16 (2⁴) possible combinations.

• Perception: Sensing versus Intuitive (comparable to MBTI perception axis)
• Input: Visual versus Verbal (comparable to Herrmann left-right axis)
• Processing: Active versus Reflective (comparable to Kolb processing axis)
• Understanding: Sequential versus Global (comparable to Gregorc ordering axis)

Felder offers an online self-assessment tool for his Index of Learning Styles on his Learning Styles page at http://www.ncsu.edu/felder-public/Learning_Styles.html

Felder finds that engineers tend to be sensing, verbal, reflective, and sequential. When these measures are used to evaluate learning styles, the stereotypical architect seems almost the complete opposite (although on the MBTI perception axis, they are both intuitive):

Felder learning and teaching styles
ENGINEERS	ARCHITECTS (stereotype)
Perception
Sensing	Intuitive
concrete practical oriented toward facts and procedures	conceptual innovative oriented toward theories and meanings
Input
Verbal	Visual
prefer explanations that are written spoken	prefer visual representations: pictures diagrams flow charts
Processing
Reflective	Active
think things though work alone	try things out work with others
Understanding
Sequential	Global
linear orderly learn in small incremental steps	holistic systems thinkers learn in large leaps

Felder finds that most engineering instruction has been heavily biased toward the intuitive, a mismatch with engineering students who, like the general population, are mostly sensors (in this measure, Felder's data is inconsistent with that of Durling (1996)). Engineering instruction is also biased toward the verbal, whereas most people are visual learners, and toward the reflective and sequential learner. If we were to derive a profile of the "ideal" architecture student from the manner in which design is taught in the studio, it would be very close to the stereotype: someone who is more intuitive than the engineer, is decidely visual, is an active learner and a global thinker.

Many architecture and engineering students do not fall into these same categories, which can help explain why some have more difficulty in their courses than in others. Felder's research indicates that performance differences might be more attributable to the manner in which subjects are taught than instructors realize. Durling's study using MBTI categories showed that architecture students were distributed among all four categies of intuitive introverts, suggesting that a greater variety of teaching methods would have a positive effect. Additional research using Felder's instrument to assess populations of architecture and art students would be highly valuable in determining how closely they match the stereotype.

Felder's model shares some characteristics with the models previously reviewed. For instance, his reflective-active processing axis is the same as the Kolb RO-AC processing axis (and similar to the MBTI P-J (perceiving-judging attitude axis). Felder's sensing-intuitive perception axis is similar to the MBTI perception axis. His visual-verbal input axis can be compared directly to the Hermann right rain-left brain dichotomy. Finally, his sequential-global understanding axis can be compared to that of the Gregorc model.

The measures that Felder does not directly include in his model are the CE-AC (concrete-abstract) perception axis from the Kolb model (similar to the F-T (feeling-thinking) decision-making axis of the MBTI model), or the MBTI I-E (introvert-extravert) orientation axis. These characteristics are covered, at least in part, by his sensing-intuitive axis and his reflective-active axis. The measures in the Felder model that are not included in the MBTI model are his visual-verbal input axis and his sequential-global understanding axis.

Felder describes several instructional approaches that promote learning and retention: active learning, cooperative or team-based learning (with its subset collaborative learning), and problem-based learning that emphasizes inductive reasoning as opposed to the traditional deductive approach used by those who have already mastered a subject, which proceeds from the general (principles and theories) to the speific (applications). In the typical coursein science and engineering, the instructor will lecture on the general theories, and assign problems in which students apply those theories and principles.

Felder argues that most people learn through an inductive reasoning process. They confront a problem with limited knowledge and skills, gradually discover that they need more knowledge and skills; seek them out; apply them to the problem; observe and reflect on the outcome of each attempt. They learn more effectively "when they perceive a clear need to know it in order to solve a problem or meet a challenge" (Felder and Silverman, 1988, p. 5) The instructor only presents new material when students have reaced the point where they need it and can appreciate its value in solving the problem. This is very similar to what Schön describes as "reflection in action."

Felder also describes the more informal variant, project-based learning, in which most of the learning takes place in the context of a project, with few or no lectures. This approach is typically used in engineering lab courses and in the student's capstone project. The examples of problem-based learning that Felder and Brent (2004) describe are not dissimilar those given to architectural students in the design studio.

Grasha-Riechmann Learning and Teaching Styles

University of Cincinnati psychologist Anthony Grasha developed an integrated model of teaching and learning styles based on how students and instructors actually interact with each other (Grasha, 1996). Grasha and and Sheryl Hruska-Riechmann identified six styles relating to the way that learners interact with each other. Statistics showed that only two of the styles—participant and avoidant—were related to each other. Thus, an individual could be both "collaborative" and "competitive," or both "dependent" and "independent," at the same time:

Grasha-Riechmann Learning Styles
Competitive	compete with other students
	share ideas and talents		Collaborative
Dependent	need structure and support
	think for themselves, work alone		Independent
Participant	eager to take part in class activities	uninterested in or overwhelmed by what happens in class	Avoidant

Five teaching styles were identified in a study of 761 classrooms:

Grasha-Riechmann Teaching Styles
Expert	transmitter of information
Formal Authority	sets standards defines acceptable ways of doing things
Personal Model	teaches by illustration and direct example
Facilitator	guides and directs by asking questions, exploring options, and suggesting alternatives
Delegator	develops students' ability to function autonomously

Grasha found that students tend to adapt their learning styles to the teaching styles being used.In combination, the various teaching styles fall into clusters with associated learning styles, as indicated in the following table (instructors function as experts in all of the styles). Unlike Kolb, he did not find a relationship between learning styles and academic majors, although Groat has found distinct differences among architecture students based on sex, age/grade and ethnicity. Women architecture students are more collaborative and participatory and less competitive, while older students are more independent. Asians and African-American students are more dependent than Caucasian and Hispanic students (Montgomery & Groat, 1998, p. 5-6).:

Clustering of Grasha-Riechmann Teaching and Learning Styles
Expert	Formal Authority	Personal Model	Facilitator	Delegator
Expert	+ formal authority—38%
	learning styles: competitive, dependent, participant
	+ formal authority + personal model—22%
		+ personal model + facilitator—17%
		learning styles: collaborative, independent, participant
			+ facilitator + delegator—15%

Websites where teachers can assess their own teaching styles online include http://longleaf.net/teachingstyle.html and http://stoic.ftr.indstate.edu/fcrcweb/tstyles3.html. One of the many sites where students' learning styles can be assessed online is http://www.ltseries.com/LTS/sitepgs/GRSLSS/ls_invent.htm.

Gardner's Multiple Intelligences

Psychologist and Harvard education professor Howard Gardner developed a theory of "Multiple Intelligences" (http://www.pz.harvard.edu/Research/ResearchMI.htm), suggesting that individuals perceive the world in at least eight differentways:

Gardner Multiple Intelligences
Verbal/linguistic	reading, writing, and communicating with words
Logical/mathematical	looking for patterns, reasoning, and thinking logically
Musical/rhythmic	composing music, singing, and learning by using rhythm
Visual/spatial	thinking in pictures and visualizing results
Bodily/kinesthetic	using large and small motor skills to address problems
Interpersonal	using social skills and communication skills to empathize with and understand others
Intrapersonal	reflecting on and analyzing problems independently

These "intelligences" can be directly realted to many of the personality types and learning styles that have been reviewed above: for instance architects tend have a more highly developed visual intelligence than verbal. Gardner continues to gather evidence that there are additional forms of intelligence (Gardner, 2003). According to the Project Zero researchers, educational programs should seek to develop a wide range of competences.

The idea that learning can be reinforced by using multiple sensory channels is a widely-held belief. An article by University of Texas chemical engineering professor James Stice, Using Kolb's Learning Cycle To Improve Student Learning. Engineering Education 77: 291-296, is quoted by Felder as follows:

"A point no educational psychologist would dispute is that students learn more when information is presented in a variety of modes than when only a single mode is used. The point is supported by a research study carried out several decades ago, which concluded that students retain 10 percent of what they read, 26 percent of what they hear, 30 percent of what they see, 50 percent of what they see and hear, 70 percent of what they say, and 90 percent of what they say as they do something."

Somewhat different figures on retention have been attributed articles by University of Pittsburgh educational psychologist Robert Glaser: The Role of Knowledge, Technical Report No. PDS-6 (Pittsburg, PA: University of Pittsburgh, Learning Research and Development Center, June 1983; also published with the same title in 1984 in American Psychologist 39, p. 93-104.). People retain:

• 10 percent of what they read
• 20 percent of what they hear
• 30 percent of what they see
• 50 percent of what they see and hear
• 70 percent of what they say or discuss with others
• 80 percent of what they experience personally
• 90 percent of what they say and do
• 95 percent of what they teach to someone else

According to Thalheimer, these widely-repeated figures represent bogus reasearch that do not have an adequate scientific basis. Having found themselves into the literature, they have become legitimized without being adequately checked. They apparently originated in an obscure, unsupported 1967 article by D.G. Treichler in the magazine Film and Audio-Visual Communications, and have since acquired a life of their own. However, there is some scientific support for the idea of employing mutiple sensory channels to reinforce learning, such as the multiple coding theory advanced by widely-published University of California-Santa Barbara educational psychologist Richard Mayer (Mayer, 2001, p. 42).

Consolidating the theories

While no two theories focus on the same factors, there are many similarities. Taken together, these various learning theories define six key student learning factors that teaching approaches should address. These learning styles and the associated teaching styles highlight the differences between education in the classroom and the studio, and can provide insights into how distance education can address the types of learning that occur in the design studio:

Comparison of Learning Styles
Factor/dimension	Gregorc	Herrmann	Kolb	MBTI	Felder	Grasha	Gardner
Orientation to life (MBTI)				Extravert- Introvert		participant/ collaborative- independent/ avoidant	interpersonal- intrapersonal
Perception (Felder, MBTI) Cortex (Herrmann)		limbic- cerebral		Sensing- iNtuitive	sensing- intuitive
Perception (Gregorc, Kolb) Decision-making (MBTI)	concrete- abstract		Concrete Experience- Abstract Conceptual'n	Feeling- Thinking			bodily/ kinesthetic- logical/ mathematical
Processing (Kolb, Felder) Attitude to world (MBTI)			Reflective Observation- Active Experimentn	Judging- Perceiving	reflective- active	participant/ collaborative- independent/ avoidant
Input (Felder) Hemisphere (Herrmann)		left-right			verbal- visual		verbal/linguistic- visual/spatial
Understanding (Felder) Ordering (Gregorc)	sequential- random				sequentl- global	dependent- independent