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Examining examples and non-examples can help students understand definitions. While a square may be defined as a quadrilateral with four equal sides and one right angle, seeing concrete examples of squares of various sizes, as well as considering rectangular non-examples, can help children clarify the notion of square. When we teach linear algebra and introduce the concept of subspace, we often provide examples and non-examples for students. We may point out that the polynomials of degree less than or equal to two form a subspace of the space of all polynomials, whereas the polynomials of degree two do not. Is the provision of such examples always desirable? Would it perhaps be better to ask undergraduate students to provide their own examples and non-examples? Would they be able to? Given a false conjecture, would students be able to come up with counterexamples? Several studies shed light on these questions.
To answer this question, Randall P. Dahlberg
and David L. Housman of Allegheny College
conducted an in-depth study of eleven
undergraduate students - ten
seniors and one junior. All but one, who was
in computer science, were math majors. The
students had successfully completed introductory
real analysis and algebra, as well as courses in
linear algebra and foundations and a seminar covering
set theory and the foundations of analysis. In
individually conducted audio-taped interviews,
the authors presented the students with a written
definition of a "fine function," which they had
made up to see how the students would deal with
a formally defined concept. A function was called
fine if it had a root (zero) at each integer.
When interviewed, students were first
asked to study this definition for five to ten
minutes, saying or writing as much as possible of
what they were thinking, after which they were
asked to generate examples and non-examples of
"fine functions." Subsequently, they were given
functions, such as
Four basic learning strategies were used by the
students on being presented with this new
definition - example generation, reformulation,
decomposition and synthesis, and memorization.
Examples generated included the constant zero
function and a sinusoidal graph with integer
x-intercepts. Reformulations included
Of these four strategies, example generation
(together with reflection) elicited the most
powerful "learning events," i.e., instances
where the authors thought students made real
progress in understanding the newly introduced
concept. Students who initially employed
example generation as their learning strategy
came up with a variety of discontinuous, periodic
continuous, and non-periodic continuous examples
and were able to use these in their explanations.
Those who employed memorization or decomposition
and synthesis as their learning strategies often
misinterpreted the definition, e.g., interpreting
the phrase "root at each integer" to mean a fine
function must vanish at each integer in its domain,
but that need not include all integers. Students
who employed reformulation as their learning
strategy developed algorithms to decide whether
functions given them were fine, but had difficulty
providing counterexamples to false conjectures.
[Cf. "Facilitating Learning Events Through Example
Generation," Educ. Studies in Math. 33,
283-299, 1997.]
Finally, Dahlberg and Housman note the relative
ineffectualness of their attempted interventions.
One student agreed, after a question and answer
period with the interviewer, that the zero
function was indeed a fine function, but
immediately switched her attention to other
ideas, not returning until much later when,
through self-discovery, she actually realized
the zero function was a fine function. Dahlberg
and Housman suggest it might be beneficial to
introduce students to new concepts by having
them generate their own examples or having them
decide whether teacher-provided candidates are
examples or non-examples, before providing students
examples and explanations. However, some of
their students were reluctant to engage in
either example generation or usage -- a not
uncommon phenomenon in such circumstances.
The students used a variety of approaches to
generate examples, beginning with trial and error,
e.g., some simply picked a number at random and checked
whether it was divisible by 9. Others picked a number
N, and upon dividing by 17 and getting a
remainder of 2, would use N-2 for their next trial.
Students often found constructing examples and making
the necessary choices difficult, e.g., they inquired
of the interviewers whether the elements of the sample
space were to be numbers, letters, or other objects.
Some students designed their own algorithms for
generating functions, e.g., one focused on y =
ax + b, plugged in (3, -2) to get
-2 = a*3 + b, chose a = 2 and
solved for b = -8, finally declaring her
function to be y = 2x - 8.
Interestingly, very few students produced "trivial
examples," such as 170,000 for a 6-digit number
divisible by 17 or y = -2 as their function.
Hazzan and Zazkis conjecture that these examples
might not be seen as prototypical - a function is
expected to involve x and a 6-digit number
is seen as having a wider variety of digits. There
was also a strong tendency to (directly) check the
correctness of examples, e.g., some students who
had created a number divisible by 17 by choosing
a multiplier and performing the multiplication,
verified the correctness of their example by
division. Quite a number of students had difficulty
dealing with "degrees of freedom," e.g., in order to
find a number divisible by 9, one student who knew
the sum of the digits needed to be divisible by 9,
first chose 18, noted that 8 and 2 make 10, then
broke 8 into the sum of 4, 3, and 1, and declared
that 82431 should be divisible by 9. When asked for
another strategy, she suggested something very
similar -- making the initial sum 27, instead of 18.
Constructing examples proved to be more difficult
for these students than checking the divisibility
of a number, calculating the value of a function,
or finding the probability of an event. They were often
uncertain how to proceed and were especially troubled
by having to make choices in mathematics. The authors
suggest that teachers at all levels assign more "give
an example" problems. [Cf. "Constructing Knowledge
by Constructing Examples for Mathematical Concepts,"
Proceedings of the 21st Conference of the International
Group for the Psychology of Mathematics Education,
Vol. 4, 299-306, 1997]
Furthermore, when students are allowed to discuss
mathematical ideas and propose conjectures in class,
teachers need to be able to evaluate
student-generated examples, as well as to be able to
propose counterexamples for their students' consideration.
Students quite often fail to see a single counterexample
as disproving a conjecture. This can happen when a
counterexample is perceived as "the only" one that exists,
rather than being seen as generic, e.g., sometimes the
square root of 2 is considered the only irrational or
|x| is perceived as the only continuous,
nondifferentiable function.
Two groups participated in the study -- 38 inservice
teachers, most of whom had more than five years of
teaching experience and a B.Sc. in mathematics and
45 third year student-teachers who had completed
several advanced undergraduate mathematics courses.
For the first conjecture (Task 1), 97% of the inservice
teachers gave adequate counterexamples, i.e., ones
that refuted the claim, but only 53% of the
student-teachers did so. For the second conjecture
(Task 2), 76% of the teachers and 42% of the
student-teachers gave adequate counterexamples.
The counterexamples were analyzed for their
explanatory power as specific, semi-general,
and general. A specific counterexample is one
which contradicts the claim, but gives no indication
as to how one might construct similar or related
counterexamples. For example, for Task 1 one
subject carefully drew two rectangles of different
dimensions, but with congruent diagonals. A
counterexample was called semi-general if it
provided some idea how one might generate similar
or related counterexamples, but did not tell
"the whole story" or did not cover "the whole
space" of counterexamples. For instance, on Task 1,
one subject drew two rectangles with congruent
diagonals, but the angle between the two diagonals
of second rectangle was indicated as twice that of
the first rectangle. (Here it should be noted that,
while some conjectures might not lend themselves to
the generation of numerous counterexamples, i.e.,
they might be correct except for a small number of
special "pathological" cases, these two conjectures
were chosen to be far from "almost correct.") A
general counterexample provides insight as to why a
conjecture is false and suggests a way to generate
an entire counterexample space. In response to
Task 1, one subject specified that the angle between the
diagonals could be arbitrary, rather than merely double
that of the first rectangle.
Both teachers and student-teachers produced
counterexamples of all the above types, but the
former produced more semi-general and general
counterexamples (92% vs. 38% on Task 1, and 61% vs.
33% on Task 2). Both of these types were labeled
explanatory by the authors. The difficulty in
suggesting only a specific counterexample lies
in its potential for misleading students, whereas
the pedagogical value of explanatory counterexamples
lies in their ability to provide insight into why
a conjecture fails. The authors suggest that both
prospective and in-service mathematics teachers
could benefit from an analysis and discussion of
the pedagogical aspects of counterexamples.
[Cf. "Counter-Examples That (Only) Prove and
Counter-Examples That (Also) Explain," Focus on
Learning Problems in Mathematics 19 (3),
49-61, 1997.]
Not only does such circularity play a role in students'
failure to construct examples, so does their limited
knowledge of concepts involved in a formal
definition. When Zaslavsky and Peled asked 67 preservice
and 36 inservice secondary teachers to provide examples of
binary operations which were commutative and nonassociative,
their subjects had great difficulty. Only 33% of
the experienced teachers and 4% of the third-year
undergraduate students came up with complete, correct,
and well-justified examples. Just 56% of the experienced
teachers and 31% of the student teachers were able to
provide any kind of example (correct or incorrect).
Upon investigating why this might be so, the authors
found their subjects' underlying mathematical knowledge
was deficient. For example, one subject defined
a * b = | a + b | and
claimed this was nonassociative because
| a + b | + | c | does not equal
| a | + | b + c |. Another
proposed the operation of subtraction
claiming it was commutative
because -2 - 3 = -3 - 2, rather than 3 - (-2).
Yet another proposed the unary operation
Dahlberg and Housman also noted that their
undergraduate subjects had trouble with the
underlying concepts, e.g., function and root,
making it hard to generate examples and non-examples
of "fine functions." One student identified "root"
with "continuity," three others initially thought
the graph of the zero function was a point, and one
did not believe the zero function was periodic.
In addition, most students' initially thought in
terms of functions which were nonconstant polynomials
or continuous.
Successful Math Majors
Generate Their Own Examples
In upper-division courses like abstract algebra
and real analysis, students often encounter a
host of formal definitions, many new to them.
After presenting a few examples and non-examples
along with a few proofs of theorems, we hope
they will use these definitions to tackle problems,
examine conjectures, and construct their own proofs.
Is this the best way to proceed? How do such
students deal with new definitions?
Being Asked For
Examples Can Be Disconcerting
Coming up with examples requires different
cognitive skills from carrying out algorithms -
one needs to look at mathematical objects in
terms of their properties. To be asked for an
example, whether of a "fine function" or something
else, can be disconcerting. Students have no
prelearned algorithms to show the "correct way."
This is what Orit Hazzan and Rina Zazkis, of the
Technion - Israel Institute of Technology, found
when they asked three groups of preservice elementary
teachers to provide examples of (1) a 6-digit number
divisible first by 9, then by 17, (2) a function
whose value at x = 3 is -2, and (3) a sample
space and an event that has probability 2/7 in that
space. In addition, they asked the students to explain
how they generated their examples and to provide five
additional examples.
Generating
Counterexamples That Are Explanatory
Perhaps not surprisingly, experienced secondary
mathematics teachers are better at generating
explanatory counterexamples than preservice teachers.
Irit Peled, University of Haifa, and Orit Zaslavsky,
the Technion, asked some of each to generate at
least one counterexample for each of the two following
unfamiliar, false geometry statements supposedly given
by a secondary student. (1) Two rectangles, having
congruent diagonals, are congruent. (2) Two
parallelograms, having one congruent side and one
congruent diagonal, are congruent. They were also
asked to explain how they came up with their
counterexamples. None generated more than
one counterexample for each task.
"If I Don't Know What It
Says, How Can I Find an Example of It?"
This hypothetical quote, illustrates the
chicken-and-egg quandary some students might typically
face when encountering a formal definition, whether
of "fine function" or quotient group. A definition
asserts the existence of something having certain
properties. However, the student has often never
seen or considered such a thing. To give an example
or non-example, he/she would need at least some
understanding of the concept. But how can he/she
obtain such understanding? A good, and possibly the
best, way seems to be through an examination of examples.
Thus, the student is faced with an epistemological dilemma:
Mathematical definitions, by themselves, supply few
(psychological) meanings. Meanings derive from
properties. Properties, in turn, depend on definitions.
[This is a paraphrase from Richard Noss' plenary address
to the September 1996 Research in Collegiate Mathematics
Education Conference, as reported in Focus 17(1),
1&3, February 1997.] For mathematicians, this does not
seem to be a dilemma. We suspect they view
definitions differently than students - this allows
them to search for examples in order to gain understandings
of formal definitions.
Coda
Since success in mathematics, especially at
the advanced undergraduate and graduate levels
appears to be associated with the ability to
generate examples and counterexamples,
what is the best way to develop this ability?
One suggestion, given above, is to ask students
at all levels to "give me an example of . . . ".
Granted the inherent epistemological difficulties
of finding examples for oneself, are we, in a
well-intentioned attempt to help students understand
newly defined concepts, ultimately hobbling them, by
providing them with predigested examples of our own?
Are we inadvertently denying students the opportunity
to learn to generate examples for themselves?
Difficulties with the strikingly simple idea of
"fine function" suggest some students may be excessively
dependent upon explicit instruction. Another in-between
suggestion, given above, is to provide students with a
list of potential examples (or counterexamples) and ask
them to decide whether they are indeed examples (or
counterexamples) and why. Are there other ways we
might help students become example generators?
Finally, a tendency to generate examples is not
the same as an ability to do so -- it would be
interesting to know how each of these relates to
understanding and doing mathematics.
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Copyright ©1998 The Mathematical Association of America