LEARNING AND TEACHING STYLES
IN ENGINEERING EDUCATION
[Engr. Education, 78(7), 674–681 (1988)]

Author’s Preface — June 2002
by Richard M. Felder
When Linda Silverman and I wrote this paper in 1987, our goal was to offer some insights about
teaching and learning based on Dr. Silverman’s expertise in educational psychology and my
experience in engineering education that would be helpful to some of my fellow engineering
professors. When the paper was published early in 1988, the response was astonishing. Almost
immediately, reprint requests flooded in from all over the world. The paper started to be cited in
the engineering education literature, then in the general science education literature; it was the
first article cited in the premier issue of ERIC’s National Teaching and Learning Forum; and it
was the most frequently cited paper in articles published in the Journal of Engineering Education
over a 10-year period. A self-scoring web-based instrument called the Index of Learning Styles
that assesses preferences on four scales of the learning style model developed in the paper
currently gets about 100,000 hits a year and has been translated into half a dozen languages that I
know about and probably more that I don’t, even though it has not yet been validated. The 1988
paper is still cited more than any other paper I have written, including more recent papers on
learning styles.
A problem is that in recent years I have found reasons to make two significant changes in
the model: dropping the inductive/deductive dimension, and changing the visual/auditory
category to visual/verbal. (I will shortly explain both modifications.) When I set up my web
site, I deliberately left the 1988 paper out of it, preferring that readers consult more recent
articles on the subject that better reflected my current thinking. Since the paper seems to have
acquired a life of its own, however, I decided to add it to the web site with this preface included
to explain the changes. The paper is reproduced following the preface, unmodified from the
original version except for changes in layout I made for reasons that would be known to anyone
who has ever tried to scan a 3-column article with inserts and convert it into a Microsoft Word
document.
Deletion of the inductive/deductive dimension

I have come to believe that while induction and deduction are indeed different learning
preferences and different teaching approaches, the “best” method of teaching—at least below
the graduate school level—is induction, whether it be called problem-based learning, discovery
learning, inquiry learning, or some variation on those themes. On the other hand, the traditional
college teaching method is deduction, starting with "fundamentals" and proceeding to
applications.

The problem with inductive presentation is that it isn't concise and prescriptive—you
have to take a thorny problem or a collection of observations or data and try to make sense of it.
Many or most students would say that they prefer deductive presentation—“Just tell me exactly
what I need to know for the test, not one word more or less.” (My speculation in the paper that
more students would prefer induction was refuted by additional sampling.) I don't want


2

instructors to be able to determine somehow that their students prefer deductive presentation and
use that result to justify continuing to use the traditional but less effective lecture paradigm in
their courses and curricula. I have therefore omitted this dimension from the model.

Change of the visual/auditory dimension to the visual/verbal dimension

“Visual” information clearly includes pictures, diagrams, charts, plots, animations, etc.,
and “auditory” information clearly includes spoken words and other sounds. The one medium of
information transmission that is not clear is written prose. It is perceived visually and so
obviously cannot be categorized as auditory, but it is also a mistake to lump it into the visual
category as though it were equivalent to a picture in transmitting information. Cognitive
scientists have established that our brains generally convert written words into their spoken
equivalents and process them in the same way that they process spoken words. Written words
are therefore not equivalent to real visual information: to a visual learner, a picture is truly worth
a thousand words, whether they are spoken or written. Making the learning style pair visual and
verbal solves this problem by permitting spoken and written words to be included in the same
category (verbal). For more details about the cognition studies that led to this conclusion, see
R.M. Felder and E.R. Henriques, “Learning and Teaching Styles in Foreign and Second
Language Education,” Foreign Language Annals, 28 (1), 21–31 (1995).
.

The Index of Learning Styles

The Index of Learning Styles (ILS) is a self-scoring web-based instrument that assesses
preferences on the Sensing/Intuiting, Visual/Verbal, Active/Reflective, and Sequential/Global
dimensions. It is available free to individuals and instructors who wish to use it for teaching and
research on their own classes, and it is licensed to companies and individuals who plan to use it
for broader research studies or services to customers or clients. To access the ILS and
information about it, go to .

And now, the paper.







674

“Professors confronted by low test grades, unresponsive or hostile classes, poor attendance
and dropouts, know that something is wrong.” The authors explain what has happened and how
to make it right.




Learning and Teaching Styles
In Engineering Education

Richard M. Felder, North Carolina State University
Linda K. Silverman, Institute for the Study of
Advanced Development
[Engr. Education, 78(7), 674–681 (1988)]

Students learn in many ways— by
seeing and hearing; reflecting and
acting; reasoning logically and
intuitively; memorizing and
visualizing and drawing analogies
and building mathematical models;
steadily and in fits and starts.
Teaching methods also vary. Some
instructors lecture, others
demonstrate or discuss; some focus
on principles and others on applica-
tions; some emphasize memory and
others understanding. How much a
given student learns in a class is
governed in part by that student’s
native ability and prior preparation
but also by the compatibility of his
or her learning style and the
instructor’s teaching style.
Mismatches exist between com-
mon learning styles of engineering
students and traditional teaching
styles of engineering professors. In
consequence, students become
bored and inattentive in class, do
poorly on tests, get discouraged
about the courses, the curriculum,
and themselves, and in some cases
change to other curricula or drop
out of school. Professors,
confronted by low test grades,
unresponsive or hostile classes,
poor attendance and dropouts, know
something is not working; they may
become overly critical of their
students (making things even worse)
or begin to wonder if they are in the
right profession. Most seriously,
society loses potentially excellent
engineers.
In discussing this situation, we will
explore:
1) Which aspects of learning style
are particularly significant in engi-
neering education?
2) Which learning styles are pre-
ferred by most students and which are
favored by the teaching styles of most
professors?
3) What can be done to reach stu-
dents whose learning styles are not
addressed by standard methods of
engineering education?

Dimensions of Learning Style

Learning in a structured educa-
tional setting may be thought of as a
two-step process involving the recep-
tion and processing of information. In
the reception step, external in-
formation (observable through the
senses) and internal information
(arising introspectively) become
available to students, who select the
material they will process and ignore
the rest. The processing step may
involve simple memorization or in-
ductive or deductive reasoning, re-
flection or action, and introspection or
interaction with others. The outcome is
that the material is either “learned” in
one sense or another or not learned.
A learning-style model classifies
students according to where they fit on a
number of scales pertaining to the ways
they receive and process information. A
model intended to be particularly
applicable to engineering education is
proposed below. Also proposed is a
parallel teaching-style model, which
classifies instructional methods
according to how well they address the
proposed learning style components. The
learning and teaching style dimensions
that define the models are shown in the
box.
Most of the learning and teaching
style components parallel one another.*
A student who favors intuitive over
sensory perception, for example, would
respond well to an instructor who
emphasizes concepts (abstract content)
rather than facts (concrete content); a
student who favors visual perception
would be most comfortable with an
instructor who uses charts, pictures, and
films.


* The one exception is the active/
reflective learning style dimension and
the active/passive teaching style dimen-
sion, which do not exactly correspond.
The difference will later be explained.


675



The proposed learning style di-
mensions are neither original nor
comprehensive. For example, the first
dimension—sensing/intuition— is one
of four dimensions of a well-known
model based on Jung’s theory of
psychological types,1’2 and the fourth
dimension—active/reflective
processing—is a component of a
learning style model developed by
Kolb.3 Other dimensions of these two
models and dimensions of other mod-
els4’5 also play important roles in
determining how a student receives
and processes information. The hy-
pothesis, however, is that engineering
instructors who adapt their teaching
style to include both poles of each of
the given dimensions should come
close to providing an optimal learning
environment for most (if not all)
students in a class.
There are 32 (25) learning styles in
the proposed conceptual framework,
(one, for example, is the sensory/
auditory/deductive/active/sequential
style). Most instructors would be
intimidated by the prospect of trying
to accommodate 32 diverse styles in a
given class; fortunately, the task is not
as formidable as it might at first
appear. The usual methods of engi-
neering education adequately address
five categories (intuitive, auditory,
deductive, reflective, and sequential),
and effective teaching techniques
substantially overlap the remaining
categories. The addition of a relatively
small number of teaching techniques
to an instructor’s repertoire should
therefore suffice to accommodate the
learning styles of every student in the
class. Defining these techniques is the
principal objective of the remainder of
this paper.













A student’s learning style may be defined in large part by the answers to
five questions:
1) What type of information does the student preferentially perceive:
sensory (external)—sights, sounds, physical sensations, or intuitive (in-
ternal)—possibilities, insights, hunches?
2) Through which sensory channel is external information most effectively
perceived: visual—pictures, diagrams, graphs, demonstrations, or auditory—
words, sounds? (Other sensory channels—touch, taste, and smell—are
relatively unimportant in most educational environments and will not be
considered here.)
3) With which organization of information is the student most com-
fortable: inductive—facts and observations are given, underlying principles
are inferred, or deductive—principles are given, consequences and
applications are deduced?
4) How does the student prefer to process information: actively— through
engagement in physical activity or discussion, or reflectively— through
introspection?
5) How does the student progress toward understanding: sequentially—in
continual steps, or globally—in large jumps, holistically?

Teaching style may also be defined in terms of the answers to five
questions:
1) What type of information is emphasized by the instructor: concrete—
factual, or abstract—conceptual, theoretical?
2) What mode of presentation is stressed: visual—pictures, diagrams,
films, demonstrations, or verbal— lectures, readings, discussions?
3) How is the presentation organized: inductively—phenomena leading to
principles, or deductively— principles leading to phenomena?
4) What mode of student participation is facilitated by the presentation:
active—students talk, move, reflect, or passive—students watch and listen?
5) What type of perspective is provided on the information presented:
sequential—step-by-step progression (the trees), or global—context and
relevance (the forest)?

Dimensions of Learning and Teaching Styles
Preferred Learning Style Corresponding Teaching Style
sensory
perception
intuitive
concrete
content
abstract
visual
input
auditory
visual
presentation
verbal
inductive
organization
deductive
inductive
organization
deductive
active
processing
reflective
active student
participation
passive
sequential
understanding
global
sequential
perspective
global


Models of Learning &
Teaching Styles


676

Sensing and Intuitive Learners

In his theory of psychological types,
Carl Jung6 introduced sensing and
intuition as the two ways in which
people tend to perceive the world.
Sensing involves observing, gathering
data through the senses; intuition
involves indirect perception by way of
the unconscious—speculation, imagin-
ation, hunches. Everyone uses both
faculties, but most people tend to favor
one over the other.
In the 1940s Isabel Briggs Myers
developed the Myers-Briggs Type
Indicator (MBTI), an instrument that
measures, among other things, the
degree to which an individual prefers
sensing or intuition. In the succeeding
decades the MBTI has been given to
hundreds of thousands of people and
the resulting profiles have been
correlated with career preferences and
aptitudes, management styles, learning
styles, and various behavioral
tendencies. The characteristics of
intuitive and sensing types7 and the
different ways in which sensors and
intuitors approach learning1,2 have been
studied.
Sensors like facts, data, and ex-
perimentation; intuitors prefer prin-
ciples and theories. Sensors like solv-
ing problems by standard methods and
dislike “surprises”; intuitors like
innovation and dislike repetition.
Sensors are patient with detail but do
not like complications; intuitors are
bored by detail and welcome
complications. Sensors are good at
memorizing facts; intuitors are good at
grasping new concepts. Sensors are
careful but may be slow; intuitors are
quick but may be careless. These
characteristics are tendencies of the
two types, not invariable behavior
patterns: any individual—even a strong
sensor or intuitor—may manifest signs
of either type on any given occasion.
An important distinction is that
intuitors are more comfortable with
symbols than are sensors. Since words
are symbols, translating them into what
they represent comes naturally to
intuitors and is a struggle for sensors.
Sensors’ slowness in translating words
puts them at a disadvantage in timed
tests: since they may have to read
questions several times before
beginning to answer them, they
frequently run out of time. Intuitors
may also do poorly on timed tests but
for a different reason—their impa-
tience with details may induce them to
start answering questions before they
have read them thoroughly and to
make careless mistakes.
Most engineering courses other than
laboratories emphasize concepts rather
than facts and use primarily lectures
and readings (words, symbols) to
transmit information, and so favor
intuitive learners. Several studies show
that most professors are themselves
intuitors. On the other hand, the
majority of engineering students are
sensors,8-10 suggesting a serious
learning/teaching style mismatch in
most engineering courses. The
existence of the mismatch is
substantiated by Godleski,11,12 who
found that in both chemical and
electrical engineering courses intuitive
students almost invariably got higher
grades than sensing students. The one
exception was a senior course in
chemical process design and cost
estimation, which the author
characterizes as a “solid sensing
course” (i.e. one that involves facts
and repetitive calculations by well-
defined procedures as opposed to
many new ideas and abstract
concepts).
While sensors may not perform as
well as intuitors in school, both types
are capable of becoming fine engineers
and are essential to engineering
practice. Many engineering tasks
require the awareness of surroundings,
attentiveness to details, experimental
thoroughness, and practicality that are
the hallmarks of sensors; many other
tasks require the creativity, theoretical
ability, and talent at inspired
guesswork that characterize intuitors.
To be effective, engineering edu-
cation should reach both types, rather
than directing itself primarily to
intuitors. The material presented
should be a blend of concrete in-
formation (facts, data, observable
phenomena) and abstract concepts
(principles, theories, mathematical
models). The two teaching styles that
correspond to the sensing and intuitive
learning styles are therefore called
concrete and abstract.*
Specific teaching methods that
effectively address the educational

* Concrete experience and abstract
conceptualization are two poles of a
learning style dimension in Kolb’s ex-
periential learning model7 that are
closely related to sensing and intuition.
needs of sensors and intuitors are
listed in the summary.

Visual and Auditory Learners

The ways people receive informa-
tion may be divided into three cate-
gories, sometimes referred to as mo-
dalities: visual—sights, pictures,
diagrams, symbols; auditory— sounds,
words; kinesthetic—taste, touch, and
smell. An extensive body of research
has established that most people learn
most effectively with one of the three
modalities and tend to miss or ignore
information presented in either of the
other two.13-17 There are thus visual,
auditory, and kinesthetic learners.*
Visual learners remember best what
they see: pictures, diagrams, flow
charts, time lines, films, dem-
onstrations. If something is simply
said to them they will probably forget
it. Auditory learners remember much
of what they hear and more of what
they hear and then say. They get a lot
out of discussion, prefer verbal
explanation to visual demonstration,
and learn effectively by explaining
things to others.
Most people of college age and
older are visual13,18 while most college
teaching is verbal—the information
presented is predominantly auditory
(lecturing) or a visual representation of
auditory information (words and
mathematical symbols written in texts
and handouts, on transparencies, or on
a chalkboard). A second learning/
teaching style mismatch thus exists,

* Visual and auditory learning both
have to do with the component of the
learning process in which information
is perceived, while kinesthetic learning
involves both information perception
(touching, tasting, smelling) and in-
formation processing (moving,
relating, doing something active while
learning). As noted previously, the
perception-related aspects of
kinesthetic learning are at best
marginally relevant to engineering
education; accordingly, only visual
and auditory modalities are addressed
in this section. The processing compo-
nents of the kinesthetic modality are
included in the active/reflective learn-
ing style category.


677



this one between the preferred input
modality of most students and the pre-
ferred presentation mode of most
professors. Irrespective of the extent
of the mismatch, presentations that use
both visual and auditory modalities
reinforce learning for all stu-
dents.4,14,19,20 The point is made by a
study carried out by the Socony-Vac-
uum Oil Company that concludes 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.21
How to teach both visual and au-
ditory learners: Few engineering in-
structors would have to modify what
they usually do in order to present
information auditorily: lectures
accomplish this task. What must
generally be added to accommodate all
students is visual material—pictures,
diagrams, sketches. Process flow
charts, network diagrams, and logic or
information flow charts should be used
to illustrate complex processes or
algorithms; mathematical functions
should be illustrated by graphs; and
films or live demonstrations of
working processes should be presented
whenever possible.

Inductive and Deductive
Learners

Induction is a reasoning progression
that proceeds from particulars
(observations, measurements, data) to
generalities (governing rules, laws,
theories). Deduction proceeds in the
opposite direction. In induction one
infers principles; in deduction one
deduces consequences.
Induction is the natural human
learning style. Babies do not come
into life with a set of general princi-
ples but rather observe the world
around them and draw inferences: “If I
throw my bottle and scream loudly,
someone eventually shows up.” Most
of what we learn on our own (as
opposed to in class) originates in a real
situation or problem that needs to be
addressed and solved, not in a general
principle; deduction may be part of the
solution process but it is never the
entire process.
On the other hand, deduction is the
natural human teaching style, at least
for technical subjects at the college
level. Stating the governing prin-
ciples and working down to the
applications is an efficient and elegant
way to organize and present material
that is already understood.
Consequently, most engineering cur-
ricula are laid out along deductive
lines, beginning with “fundamentals”
for sophomores and arriving at design
and operations by the senior year. A
similar progression is normally used to
present material within individual
courses: principles first, applications
later (if ever).
Our informal surveys suggest that
most engineering students view
themselves as inductive learners. We
also asked a group of engineering
professors to identify their own
learning and teaching styles: half of
the 46 professors identified them-
selves as inductive and half as de-
ductive learners, but all agreed that
their teaching was almost purely de-
ductive. To the extent that these re-
sults can be generalized, in the or-
ganization of information along
inductive/deductive lines—as in the
other dimensions discussed so far—a
mismatch thus exists between the
learning styles of most engineering
students and the teaching style to
which they are almost invariably ex-
posed.
“Inductive learners need to see phenomena before they can understand underlying theory.”


678
One problem with deductive
presentation is that it gives a seriously
misleading impression. When students
see a perfectly ordered and concise
exposition of a relatively complex
derivation they tend to think that the
author/instructor originally came up
with the material in the same neat
fashion, which they (the students)
could never have done. They may then
conclude that the course and perhaps
the curriculum and the profession are
beyond their abilities. They are correct
in thinking that they could not have
come up with that result in that
manner; what they do not know is that
neither could the professor nor the
author the first time around. Un-
fortunately, students never get to see
the real process—the false starts and
blind alleys, the extensive trial-and-
error efforts that eventually lead to the
elegant presentation in the book or on
the board. An element of inductive
teaching is necessary for the instructor
to be able to diminish the students’
awe and increase their realistic
perceptions of problem-solving.
Much research supports the notion
that the inductive teaching approach
promotes effective learning. The
benefits claimed for this approach
include increased academic achieve-
ment and enhanced abstract reasoning
skills;22 longer retention of in-
formation;23’24 improved ability to
apply principles;25 confidence in
problem-solving abilities;26 and in-
creased capability for inventive
thought.27’28
Inductive learners need motivation
for learning. They do not feel
comfortable with the “Trust me—this
stuff will be useful to you some day”
approach: like sensors, they need to
see the phenomena before they can
understand and appreciate the
underlying theory.
How to teach both deductive and
inductive learners: An effective way
to reach both groups is to follow the
scientific method in classroom
presentations: first induction, then
deduction. The instructor precedes
presentations of theoretical material

Active learners do not learn
much in situations that require
them to be passive, and reflective
learners do not learn much in
situations that provide no
opportunity to think about the
information being presented.

with a statement of observable
phenomena that the theory will
explain or of a physical problem the
theory will be used to solve; infers the
governing rules or principles that ex-
plain the observed phenomena; and
deduces other implications and con-
sequences of the inferred principles.
Perhaps most important, some home-
work problems should be assigned that
present phenomena and ask for the
underlying rules. Such problems play
to the inductive learners strength and
they also help deductive learners
develop facility with their less-
preferred learning mode. Several such
exercises have been suggested for
different branches of engineering.29

Active and Reflective Learners

The complex mental processes by
which perceived information is con-
verted into knowledge can be conve-
niently grouped into two categories:
active experimentation and reflective
observation.3 Active experimentation
involves doing something in the
external world with the information—
discussing it or explaining it or testing
it in some way—and reflective
observation involves examining and
manipulating the information in-
trospectively. * An “active learner” is
someone who feels more comfortable
with, or is better at, active ex-
perimentation than reflective ob-
servation, and conversely for a reflec-


* The active learner and the reflec-
tive learner are closely related to the
extravert and introvert, respectively, of
the Jung-Myers-Briggs model.1 The
active learner also has much in
common with the kinesthetic learner
of the modality and neurolinguistic
programming literature.14,15
tive learner. There are indications that
engineers are more likely to be active
than reflective learners.20
Active learners do not learn much
in situations that require them to be
passive (such as most lectures), and
reflective learners do not learn much
in situations that provide no opportu-
nity to think about the information
being presented (such as most lec-
tures). Active learners work well in
groups; reflective learners work better
by themselves or with at most one
other person. Active learners tend to
be experimentalists; reflective learners
tend to be theoreticians.
At first glance there appears to be a
considerable overlap between active
learners and sensors, both of whom
are involved in the external world of
phenomena, and between reflective
learners and intuitors, both of whom
favor the internal world of abstraction.
The categories are independent,
however. The sensor preferentially
selects information available in the
external world but may process it
either actively or reflectively, in the
latter case by postulating explanations
or interpretations, drawing analogies,
or formulating models. Similarly, the
intuitor selects information generated
internally but may process it
reflectively or actively, in the latter
case by setting up an experiment to
test out the idea or trying it out on a
colleague.
In the list of teaching-style catego-
ries (table 1) the opposite of active is
passive, not reflective, with both terms
referring to the nature of student
participation in class. “Active”
signifies that students do something in
class beyond simply listening and
watching, e.g., discussing, question-
ing, arguing, brainstorming, or re-
flecting. Active student participation
thus encompasses the learning pro-
cesses of active experimentation and
reflective observation. A class in
which students are always passive is a
class in which neither the active
experimenter nor the reflective ob-
server can learn effectively. Unfortu-


679

nately, most engineering classes fall
into this category.
As is true of all the other learning-
style dimensions, both active and re-
flective learners are needed as engi-
neers. The reflective observers are the
theoreticians, the mathematical
modelers, the ones who can define the
problems and propose possible
solutions. The active experimenters are
the ones who evaluate the ideas, design
and carry out the experiments, and find
the solutions that work—the
organizers, the decision-makers. How
to teach both active and reflective
learners: Primarily, the instructor
should alternate lectures with
occasional pauses for thought
(reflective) and brief discussion or
problem-solving activities (active), and
should present material that
emphasizes both practical problem-
solving (active) and fundamental un-
derstanding (reflective). An excep-
tionally effective technique for
reaching active learners is to have
students organize themselves at their
seats in groups of three or four and
periodically come up with collective
answers to questions posed by the
instructor. The groups may be given
from 30 seconds to five minutes to do
so, after which the answers are shared
and discussed for as much or as little
time as the instructor wishes to spend
on the exercise. Besides forcing
thought about the course material, such
brainstorming exercises can indicate
material that students don’t
understand; provide a more congenial
classroom environment than can be
achieved with a formal lecture; and
involve even the most introverted
students, who would never participate
in a full class discussion. One such
exercise lasting no more than five
minutes in the middle of a lecture
period can make the entire period a
stimulating and rewarding educational
experience.31

Sequential and Global Learners

Most formal education involves the
presentation of material in a logically
ordered progression, with the pace of

Global learners should be given
the freedom to devise their own
methods of solving problems
rather than being forced to
adopt the professor’s strategy,
and they should be exposed
periodically to advanced
concepts before these concepts
would normally be introduced.

learning dictated by the clock and
the calendar. When a body of material
has been covered the students are
tested on their mastery and then move
to the next stage.
Some students are comfortable with
this system; they learn sequentially,
mastering the material more or less as
it is presented. Others, however,
cannot learn in this manner. They
learn in fits and starts: they may be
lost for days or weeks, unable to solve
even the simplest problems or show
the most rudimentary understanding,
until suddenly they “get it”—the light
bulb flashes, the jigsaw puzzle comes
together. They may then understand
the material well enough to they apply
it to problems that leave most of the
sequential learners baffled. These are
the global learners.32
Sequential learners follow linear
reasoning processes when solving
problems; global learners make intu-
itive leaps and may be unable to ex-
plain how they came up with solu-
tions. Sequential learners can work
with material when they understand it
partially or superficially, while global
learners may have great difficulty
doing so. Sequential learners may be
strong in convergent thinking and
analysis; global learners may be better
at divergent thinking and synthesis.
Sequential learners learn best when
material is presented in a steady
progression of complexity and
difficulty; global learners sometimes
do better by jumping directly to more
complex and difficult material. School
is often a difficult experience for
global learners. Since they do not learn
in a steady or predictable manner they
tend to feel out-of-step with their
fellow students and incapable of
meeting the expectations of their
teachers. They may feel stupid when
they are struggling to master material
with which most of their
contemporaries seem to have little
trouble. Some eventually become
discouraged with education and drop
out. However, global learners are the
last students who should be lost to
higher education and society. They are
the synthesizers, the multidisciplinary
researchers, the systems thinkers, the
ones who see the connections no one
else sees. They can be truly
outstanding engineers—if they survive
the educational process.
How to teach global learners: Ev-
erything required to meet the needs of
sequential learners is already being
done from first grade through graduate
school: curricula are sequential, course
syllabi are sequential, textbooks are
sequential, and most teachers teach
sequentially. To reach the global
learners in a class, the instructor
should provide the big picture or goal
of a lesson before presenting the steps,
doing as much as possible to establish
the context and relevance of the
subject matter and to relate it to the
students’ experience. Applications and
“what ifs” should be liberally
furnished. The students should be
given the freedom to devise their own
methods of solving problems rather
than being forced to adopt the
professor’s strategy, and they should
be exposed periodically to advanced
concepts before these concepts would
normally be introduced.
A particularly valuable way for in-
structors to serve the global learners in
their classes, as well as the sequential
learners, is to assign creativity
exercises—problems that involve
generating alternative solutions and
bringing in material from other
courses or disciplines—and to en-
courage students who show promise in
solving them.31’33 Another way to
support global learners is to explain


680


Teaching Techniques to Address
All Learning Styles
ï‚· Motivate learning. As much as possible, relate the material being
presented to what has come before and what is still to come in
the same course, to material in other courses, and particularly to
the students’ personal experience (inductive/global).
ï‚· Provide a balance of concrete information (facts, data, real or
hypothetical experiments and their results) (sensing) and abstract
concepts (principles, theories, mathematical models) (intuitive).
ï‚· Balance material that emphasizes practical problem-solving
methods (sensing/active) with material that emphasizes
fundamental understanding (intuitive/reflective).
ï‚· Provide explicit illustrations of intuitive patterns (logical
inference, pattern recognition, generalization) and sensing
patterns (observation of surroundings, empirical experimentation,
attention to detail), and encourage all students to exercise both
patterns (sensing/intuitive). Do not expect either group to be able
to exercise the other group’s processes immediately.
ï‚· Follow the scientific method in presenting theoretical material.
Provide concrete examples of the phenomena the theory
describes or predicts (sensing/ inductive); then develop the
theory or formulate the mod(intuitive/inductive/ sequential);
show how the theory or modcan be validated and deduce its
consequences (deductive/sequential); and present applications
(sensing/deductive/sequential).
ï‚· Use pictures, schematics, graphs, and simple sketches liberally
before, during, and after the presentation of verbal material
(sensing/visual). Show films (sensing/visual.) Provide
demonstrations (sensing/visual), hands-on, if possible (active).
 Use computer-assisted instruction—sensors respond very well to
it34 (sensing/active).
ï‚· Do not fill every minute of class time lecturing and writing on the
board. Provide intervals—however brief—for students to think
about what they have been told (reflective).
ï‚· Provide opportunities for students to do something active besides
transcribing notes. Small-group brainstorming activities that take
no more than five minutes are extremely effective for this
purpose (active).
ï‚· Assign some drill exercises to provide practice in the basic
methods being taught (sensing/active/sequential) but do not
overdo them (intuitive/reflective/ global). Also provide some
open-ended problems and exercises that call for analysis and
synthesis (intuitive/reflective/global).
ï‚· Give students the option of cooperating on homework assignments
to the greatest possible extent (active). Active learners generally
learn best when they interact with others; if they are denied the
opportunity to do so they are being deprived of their most
effective learning tool.
ï‚· Applaud creative solutions, even incorrect ones (intuitive/global).
ï‚· Talk to students about learning styles, both in advising and in
classes. Students are reassured to find their academic difficulties
may not all be due to personal inadequacies. Explaining to
struggling sensors or active or global learners how they learn
most efficiently may be an important step in helping them
reshape their learning experiences so that they can be successful
(all types).
their learning process to them. While
they are painfully aware of the draw-
backs of their learning style, it is
usually a revelation to them that they
also enjoy advantages—that their
creativity and breadth of vision can be
exceptionally valuable to future
employers and to society. If they can
be helped to understand how their
learning process works, they may
become more comfortable with it, less
critical of themselves for having it, and
more positive about education in
general. If they are given the
opportunity to display their unique
abilities and their efforts are
encouraged in school, the chances of
their developing and applying those
abilities later in life will be substan-
tially increased.

Conclusion

Learning styles of most engineering
students and teaching styles of most
engineering professors are in-
compatible in several dimensions.
Many or most engineering students are
visual, sensing, inductive, and active,
and some of the most creative students
are global; most engineering education
is auditory, abstract (intuitive),
deductive, passive, and sequential.
These mismatches lead to poor student
performance, professorial frustration,
and a loss to society of many
potentially excellent engineers.
Although the diverse styles with
which students learn are numerous, the
inclusion of a relatively small number
of techniques in an instructor’s
repertoire should be sufficient to meet
the needs of most or all of the students
in any class. The techniques and
suggestions given on this page should
serve this purpose.
Professors confronted with this list
might feel that it is impossible to do all
that in a course and still cover the
syllabus. Their concern is not entirely
unfounded: some of the recommended
approaches—particularly those that
involve the inductive organization of
information and opportunities for
student activity during class—may
indeed add to the time it takes to
present a given body of material.
The idea, however, is not to use all


681

A class in which students are
always passive is a class in which
neither the active experimenter
nor the reflective observer can
learn effectively. Unfortunately,
most engineering classes fall into
this category.

the techniques in every class but rather
to pick several that look feasible and
try them; keep the ones that work; drop
the others; and try a few more in the
next course. In this way a teaching
style that is both effective for students
and comfortable for the professor will
evolve naturally and relatively
painlessly, with a potentially dramatic
effect on the quality of learning that
subsequently occurs.

References

1. Lawrence, G., People Types and
Tiger Stripes: A Practical Guide to
Learning Styles, 2nd edit., Center for
Applications of Psychological Type,
Gainesville, Fla., 1982.
2. Lawrence, G., “A Synthesis of
Learning Style Research Involving the
MBTI,” J. Psychological Type 8, 2-15
(1984).
3. KoIb, D.A., Experiential Learn-
ing: Experience as the Source of
Learning and Development, Prentice-
Hall, Englewood Cliffs, N.J., 1984.
4. Dunn, R., T. DeBello, P Brennan,
J. Krimsky, and P. Murrain, “Learning
Style Researchers Define Differences
Differently,” Educational Leadership,
Feb. 1981, pp. 372-375.
5. Guild, P.B. and S. Garger,
Marching to Different Drummers,
ACSD, 1985.
6. Jung, C.G., Psychological Types,
Princeton University Press, Princeton,
N.J., 1971. (Originally published in
1921.)
7. Myers, lB. and Myers, PB., Gifts
Differing, Consulting Psychologists
Press. Palo Alto, Calif., 1980.
8. McCaulley, M.H., “Psychological
Types of Engineering Students—
Implications for Teaching,”
Engineering Education, vol. 66, no. 7,
Apr. 1976, pp. 729-736.
9. McCaulley, M.H., E.S. Godleski,
C.F. Yokomoto, L. Harrisberger, and
E.D. Sloan, “Applications of Psycho-
logical Type in Engineering Edu-
cation,” Engineering Education, vol.
73, no. 5, Feb. 1983, pp. 394-400.
10. Yokomoto, C.E and J.R. Ware,
“Improving Problem Solving Perfor-
mance Using the MBTI,” Proceedings,
ASEE Annual Conference, College
Station, Tex., 1982, pp. 163-167.
11. Godleski, E.S., “Learning Style
Compatibility of Engineering Students
and Faculty,” Proceedings, Annual
Frontiers in Education Conference,
ASEE/IEEE, Philadelphia, 1984, p.
362.
12. Godleski, E.S., “Faculty-Student
Compatibility,” Presented at the 1983
Summer National Meeting of the
American Institute of Chemical Engi-
neers, Denver, Aug. 1983.
13. Barbe, WB. and M.N. Milone,
“What We Know About Modality
Strengths,” Educational Leadership,
Feb. 1981, pp. 378-380.
14. Barbe, WB., R.H. Swassing and
M.N. Milone, Teaching Through Mo-
dality Strengths: Concepts and Prac-
tices, Zaner-Bloser, Columbus, Oh.,
1979.
15. Bandler, R. and J. Grinder,
Frogs into Princes, Real People Press,
Moab, Ut., 1979.
16. Dunn, R. and K. Dunn,
Teaching Students Through Their
Individual Learning Styles: A Prac-
tical Approach, Reston Publishing
Division of Prentice-Hall Publishers,
Reston, Va., 1978.
17. Waldheim, G.P, “Understanding
How Students Understand,” Engi-
neering Education, vol. 77, no. 5, Feb.
1987, pp. 306-308.
18. Richardson, J., Working With
People, Associate Management Inst.,
San Francisco, Calif., 1984.
19. Barbe, W.B. and M.N. Milone,
“Modality Strengths: A Reply to Dunn
and Carbo,” Educational Leadership,
Mar. 1981, p. 489.
20. Dunn, R. and M. Carbo,
“Modalities: An Open Letter to Walter
Barbe, Michael Milone, and Raymond
Swassing,” Educational Leadership,
Feb. 1981, pp. 381-382.
21. Stice, J.E., “Using KoIb’s
Learning Cycle to Improve Student
Learning,” Engineering Education,
vol. 77, no. 5, Feb. 1987, pp. 291-296.
22. Taba, H., Teaching Strategies
and Cognitive Functioning in Elemen-
tary School Children, U.S.O.E. Co-
operative Research Project No. 2404,
San Francisco State College, San Fran-
cisco, Calif., 1966.
23. McConnell, T.R., “Discovery
Versus Authoritative Identification in
the Learning of Children,” Studies in
Education, 2(5), 13-60 (1934).
24. Swenson, E.J., et al., “Organiza-
tion and Generalization as Factors in
Learning, Transfer, and Retroactive In-
hibition,” Learning Theory in School
Situations, University of Minnesota
Press, Minneapolis, Minn., 1949.
25. Lahti, A.M., “The Inductive-De-
ductive Method and the Physical Sci-
ence Laboratory,” Journal of Experi-
mental Education, vol. 24, 1956, pp.
149-163. Cited in MeKeachie, W. J.,
Teaching Tips (7th edit.), Heath, Lex-
ington, Mass., 1978, p. 33.
26. Kagan, J., “Impulsive and Re-
flective Children: The Significance of
Conceptual Tempo,” in J. Krumboltz,
Ed., Learning and the Educational
Process, Rand McNally, Chicago, Ill.
1965.
27. Chomsky, N., Language and
Mind, Harcourt, Brace and World,
New York, 1968.
28. Piaget, J., Science of Education
and the Psychology of the Child, Orion
Press, New York, 1970.
29. Felder, R.M. and L.K.
Silverman, “Learning Styles and
Teaching Styles in Engineering
Education,” Presented at the 1987
Annual Meeting of the American
Institute of Chemical Engineers, New
York, Nov. 1987.
30. Kolb, op. cit., ref. 3, p. 86.
31. Felder, R.M., “Creativity in En-
gineering Education,” Chemical Engi-
neering Education, 1988, in press.
32. Silverman, L.K., “Global Learn-
ers: Our Forgotten Gifted Children,”
Paper presented at the 7th World Con-
ference on Gifted and Talented Chil-
dren, Salt Lake City, Ut., Aug. 1987.
33. Felder, R.M., “On Creating Cre-
ative Engineers,” Engineering Educa-
tion, vol. 77, no. 4, Jan. 1987, pp. 222-
227.
34. Hoffman, J.L., K. Waters and M.
Berry, “Personality Types and Com-
puter Assisted Instruction in a Self-
Paced Technical Training Environ-
ment,” Research in Psychological Type
3, 81-85 (1981).