H ow do we get students to think critically? How do we get them to take an interest in our disciplines,
to move beyond a concern with "just making the grade" or merely preparing for some standardized test that guards
the gates to graduate and professional schools? How do we arouse their curiosity? How can we make a sustained difference in
the way they think and act? How can we help students to become active intellects, human beings who are able to understand
important ideas, to analyze and evaluate the arguments and evidence that support those ideas, to collect and use evidence
in reaching their own conclusions, and logically and consistently to examine conflicting claims?
In short, what can we do to help and encourage more students to become like
the best ones, and how can technology help us accomplish that goal? Before we consider technology and its applications, however,
we must, first, determine how and why people learn?
At least a partial
answer might come from the investigators who have studied intrinsic motivations. Two fairly simple theories have emerged from
the research. First, human beings are naturally curious animals. Anyone who has spent much time with a five year old might
echo this claim. Second, human beings are both rational and emotional creatures. We must appeal to the whole person, the attitudes
and emotions as well as the ability to understand. In other words, people learn naturally while trying to solve problems that
concern them. They develop an intrinsic interest that guides their quest for knowledge, and an intrinsic interest--and here's
the rub--that can actually diminish in the face of extrinsic rewards that appear to manipulate that interest.
So what must we do as teachers? One big key may be very simple: We must pose
questions that intrigue and fascinate, fundamental questions, "big" questions, questions that lie at the heart of
our disciplines. Often scholars debate questions that are significant only because of some earlier question, which in turn,
is significant because of some still earlier question, which derived its own significance from some still earlier question,
and so forth. We often live our scholarly lives focused on questions that lie several layers beneath the surface of questions
that first intrigued us. In teaching, we must be willing to dig back toward the surface and to meet our students there, to
recapture the significance of our inquiries, and to help students understand why our current deliberations capture our attention.
We cannot simply call out from our position deep within the groud and ask our students to join our subterranean mining expeditions.
We must, instead, meet our students on the surface and help them understand the value and the location of the ores we pursue.
We must help them understand why anyone might want to solve this problem or answer this question. We must remind them of the
connection between today's smaller question and the larger issues.
We must also recognize that students are most likely to become intellectually excited and motivated to work if we appeal
to their emotions, if we show some concern for them and some faith in their ability to succeed, if we ask about their attitudes
and their values as well as about their ability to understand, if we act excited, and if we ask them both to understand abstract
concepts and to see the relevance of those concepts to people's lives. We must appeal directly to their curiosity.
Learning Specific Abstract Reasoning Abilities
Another part of the answer to our original question may come from the so-called critical
thinking movement. That crusade has argued, among other points, that we should help students develop and refine specific abstract
reasoning abilities. In other words, rather than thinking in terms of teaching history, biology, chemistry, or other topics,
we should think in terms of teaching students to understand, analyze, synthesize, evaluate
evidence, and so forth. While one cannot learn to reason without something to reason about, knowledge comes not through rote memorization, but from the ability to understand, analyze, synthesize, and evaluate evidence.
To learn is to acquire the ability to reason, that is, the ability to draw conclusions on the basis of reasons. Thus, to help
our students acquire knowledge (learn), we must deliberately help them acquire specific
abstract reasoning capacities. We must teach them the logics of our disciplines and not just dictate information
to them. We should spend our time teaching students how to learn (that is, how to read
the text actively and analytically and to think in the same manner) rather than using the classes to dictate information.
We should do less telling and more asking.
of this sounds simple enough, but we know it doesn't always work. What goes wrong? And how does this relate to computers?
Again, before we turn specifically to technology, we must find out more about human learning. Stick with me.
Overcoming Students' Preconceptions
The research on what happens when students listen to our explanations may
tell us a great deal. We often act as if students' minds are blank slates, waiting for our imprint. We want to think that
what we say to our students travels as a seamless entity from our mouths (or computer presentations) to the brains of students--as
if they are like computers. In fact, students bring models of knowledge with them to our classes, preconceptions that have
a profound influence on what they think they learn and how they react to what we tell them. As Mark Twain said, "It's
not what you don't know that hurts you. It's what you know that ain't so!"
In the mid 1980's two physicists at Arizona State University provided
dramatic evidence to support Twain's remark. They tried to determine whether a traditional lecture-based introductory
physics course really changed the way students thought about the way the physical universe operates. They suspected that even
the best students learned to plug in the numbers but continued to think in pre-Newtonian terms. The researchers, Ibrahim Abou
Halloun and David Hestenes, devised and validated an examination to determine how students think about motion. They administered
the test to the students of four different physics professors, all of whom received good marks on their teaching from both
peers and students. The students took the test both before and after taking either a calculus-based or non calculus-based
introductory physics course.
Did the course change
student thinking? The pre-test revealed that students entered the course with a common sense theory (a cross between
Aristotelian and 14th century impetus ideas) about the physical world, "which the student [used] to interpret" everything,
"including what" they heard in the physics course. They emerged with "comparatively small" changes in
the way they thought.
to All Learning Personalities
Part of the answer
to our question about what goes wrong may come from thinking about learning personalities. In general the brain loves diversity.
People like different kinds of input, not the same kind all of the time. Relatively few people have fixed styles of learning
in which they can learn from only one kind of experience, but many people do have learning personalities in which they often
express preference for one approach or another. Some people like visual information (pictures, diagrams, flow charts, time
lines, films, demonstration); others, auditory input (speech or visual symbols of auditory information--written words and
mathematical notations). Most people prefer to talk things out, to interact with other humans; some, to reflect independently.
A majority try to organize information inductively; a minority, deductively. Some like to learn sequentially, a piece at a
time; others, globally, suddenly gaining insights. Some like facts, data, and experimentation (sensors); others prefer to
work from principles and theories (intuitors). Sensors like solving problems by standard methods and dislike surprises; intuitors
like innovation and dislike repetition. Sensors show patience with details but hate complications; intuitors become bored
with details but welcome complications. Sensors are good at memorizing facts; intuitors are good at grasping new concepts.
Sensors are careful but may be slow (do not work well with timed tests); intuitors are quick but may be careless.
So what does all that mean about providing good learning environments. Just
keep in mind that the brain loves diversity. If we provide that diversity, we can speak to different personalities while encouraging
everyone to expand their preferences, and to consider the joys of learning in new ways.
Challenge versus Stress
Still another part of the answer
may come from research on learning and stress. Fear, worry, excessive anxiety and tension, all reduce the human capacity to
think. At the same time, a healthy challenge can motivate. We must help our students to feel comfortable, to believe in their
capacity to learn. But we must also promote a kind of uneasiness, the tension that stems from intellectual excitement, curiosity,
challenge, and intense concern with a particular question, the tension that emerges primarily from the questions that we ask,
the challenges that we issue, and the wonderful promises that we make about what students will be able to achieve if they
are willing to join us enthusiastically in our expedition "up the mountain in search of the truth."
Technology and Learning
Finally, we can ask how technology
can help us address these issues effectively? Let me suggest two important potential contributions.
I. Promoting Higher Order Intellectual
can use computers to help students learn the higher order cognitive skills of analysis, synthesis, and evaluation rather than
using technology (as we have often done in the past) to drill for memory or to shine light on a screen?
In his recent book on the teaching of physics, the late Arnold Arons, a longtime
University of Washington physicist, offered a specific example of how that might be done.
One outcome of research and observation over
a wide range of students and introductory courses is that many students do not break through a full command of a particular
concept or line of reasoning unless they can be reached in one-on-one Socratic dialogue. . . . [But] the necessary one-on-one
dialog with a single student can easily take as long as 20 to 30 minuets or more. . .. Personal computer[s] with graphic capability
[offer] the prospect of making one-on-one dialogues practicable in spite of numbers. The problem becomes one of writing effective
dialogues that pull students over the early, most severe obstacles, and help them on the way to further learning, with decreasing
dependence on Socratic assistance. . . .
Yet for a really effective computer dialogue, the most important (and most difficult) provisions an
author must make are the ones that lead a student to rectify incorrect responses. . . .Socratic rectification of
misconceptions and incorrect reasoning can be achieved only if the author has prior knowledge [of]. . . the actual incorrect
responses likely to be made. This is why authors must be well versed in the research results if they are to write good material.
Ideally, computers can help us foster the accomplishment of the highest learning objectives
we have for our students: the ability to think critically and creatively, to reason, to use our disciplinary approaches to
information, to learn and to want to learn independently of any informal instruction, and to work collaboratively in solving
the Brain a Good Diet of Visual Learning and Provocative Thought
My second suggestion involves a more traditional use of
computers in the classroom, but with some special qualifications. We know many people like visual learning as opposed to auditory
learning. They like to see pictures, diagrams, flow charts, time lines, films, demonstrations, and so forth. This does not
mean that such people must see everything they learn, or that they cannot learn abstract concepts. It means that we probably
can’t reach some people educationally unless we at least begin with visuals. It may also mean everyone may benefit from
such visual input.
But not just any visuals, and not just an endless stream of visuals.
Three important points here:
1. Visual representations of
auditory information (words and mathematical symbols written on a screen, for example) do not provide a rich diet of visuals.
We must provide pictures, diagrams, charts, and so forth. Computers can, of course, help us create pictorial representations
of things for which we have no pictures (future models, ancient sites, and tiny places, among others), can make items appear
to move, and can help us assemble and easily use visuals from a variety of sources.
used in long, seamless presentations make fewer contributions to learning than do visuals used in short pieces to stimulate
or contribute to a discussion, in preparation for laboratories, discussions, or in other interactive environments.
Indeed, studies that have looked at the results of students' performances after exposure to "visual lectures"
(with little or no interaction) and compared those outcomes with performances after exposure to conventional lectures have
found that such visual-based instruction makes little difference. One literature review that looked at 74 different studies
on the college level, for example, drew such conclusions. Moreover, when the same professor taught both types of classes in
the comparisons, the differences were especially small.
3. Use visuals to help students
learn, not to help you get through the material faster. I had a colleague who adopted Powerpoint in a math course because
he could put whole problems on the board with a click of the mouse, and, thereby, “cover” more material. He failed
to remember that while he was going faster, his students were grasping less. Don’t think about “covering the material.”
Think about uncovering it so your students can better understand it.
Opportunities with Technology
growing use of computers in instruction offers us one of those moments--as we move from one medium to another--when we can
most productively stop and reexamine our objectives and methods. Such reexamination will not take place automatically, however;
nor will it necessarily lead to the most productive use of our new technology.
Rather than asking ourselves how will we use this particular
technology, we should begin with questions about what we want our students to learn and whether certain technologies
can help them achieve that