JOURNAL OF RESEARCH IN SCIENCE TEACHING
VOL. 27, NO. 10, PP. 1033- 1052 (1990)
THE CONCEPT MAP AS A RESEARCH TOOL: EXPLORING
CONCEPTUAL CHANGE IN BIOLOGY
JOSEPHINE D. WALLACE
Department of Science Education, East Carolina University
JOEL J. MINTZES
Department of Biological Sciences, University of North Carolina at Wilmingron
Abstract
This study examined the concurrent validity of concept maps as vehicles for documenting
and exploring conceptual change in biology. Students (N = 91) who enrolled in an elementary
science methods course were randomly assigned to one of two treatment groups. Subjects in
both groups were administered a multiple-choicelfree-response inventory which assayed their
knowledge of “Life Zones in the Ocean,” and then were asked to construct a concept map on
the same topic. Those in the experimental group subsequently received 45 minutes of computerassisted instruction on marine life zones, while those in the control (“placebo”) group received
an equivalent exposure to an unrelated topic (‘‘Body Defenses”). Upon completing the instructional
sequence, subjects were again administered the “Life Zones” inventory and asked to develop a
postinstruction concept map on marine life zones. The data analysis employed a split plot
factorial design with repeated measures. Differences among treatment groups were documented
by analysis of variance and chi-square procedures. Subjects in the experimental group showed
evidence of significant and substantial changes in the complexity and propositional structure of
the knowledge base, as revealed in concept maps. No such changes were found in the control
group. Results suggest that concept mapping offers a valid and potentially useful technique for
documenting and exploring conceptual change in biology.
For the past decade we have focused our research efforts on issues of conceptual
development and cognitive processes in biology (Mintzes, Trowbridge, Arnaudin &
Wandersee, 1991). Several of these studies have employed cross-age designs in an
attempt to understand how childrens’ biological concepts change as they progress
through the school years ( b a u d i n & Mintzes, 1985; Trowbridge & Mintzes, 1985;
1988). Others have looked at the effects of brief interventions on student understandings
in biology (Amaudin, Mintzes, Dunn & Shafer, 1984). One ongoing study addresses
differences in the content, structure, and use of biological knowledge among “novices”
and “experts” (Maguire , 1990).
0 1990 by the National Association for Research in Science Teaching
CCC 0022-4308/90/101033-20$04.00
Published by John Wiley & Sons, Inc.
1034
WALLACE AND MINTZES
The common thread running through these studies is an interest in documenting
and exploring conceptual change in the life sciences. In attempting to do so we have
scoured the landscape of existing research tools and have used a wide variety of both
qualitative and quantitative techniques, including clinical interviews (Pines, Novak,
Posner & Vankirk, 1978), sorting tasks (Gobbo & Chi, 1986), open-ended and multiplechoice test items (Bloom, Hastings & Madaus, 1971). Likert-type (1932) scales,
student drawings (Quiggin, 1977; Porter, 1974) and concept maps (Novak & Gowin,
1984). Of the approaches we have used, the combination of clinical interviews and
concept maps has proven most versatile. But as researchers we have an obligation to
be cautious and circumspect about any new investigative technique.
What of the concept map itself? How well do concept maps represent what students
know and how they organize their knowledge? To what extent are changes in students’
cognitive structures reflected in the concept maps they draw?
This study examined the concurrent validity (American Psychological Association,
1974; Anastasi, 1968) of concept maps as vehicles for documenting and exploring
changes in cognitive structure. Specifically, it looks at the extent to which concept
maps reveal changes in cognitive structure that result from brief episodes of instructional
intervention. Should the concept map offer a valid mechanism for measuring conceptual
change, we might reasonably suggest that it holds promise as a research tool and
possibly as an adjunct or even an alternative to traditional evaluation methods.
Concept Maps in Research
A significant number of recent studies have examined the use of concept maps in
science learning (Abayomi, 1988; Bar-Lavie, 1988; Bodolus, 1987; Clibum, 1990;
Curry, 1986; Heinze-Fry, 1987; Kurzmyn, 1987; Lehman, Carter & Kahle, 1985;
Loncaric, 1986; Memll, 1987; Novak, Gowin & Johansen, 1983). Most of these
studies have focused on the use of concept mapping as a heuristic in promoting
meaningful learning in a variety of knowledge domains and instructional settings.
Others have employed the concept map as a metalearning strategy in an attempt to
help students “learn how to learn.” In general the results suggest that concept maps
hold great promise, particularly as a way of “empowering” students through knowledge
of their own learning.
Relatively few studies have investigated the use of concept maps as an approach
to documenting and exploring conceptual change (Amaudin et al., 1984; Bar-Lavie,
1988; Beyerbach, 1986; Stuart, 1985). This is especially surprising in light of Carey’s
(1986) suggestion that concept maps be used to investigate knowledge acquisition.
Says she, “By comparing successive concept maps, produced as the student gains
mastery of the domain, the researcher can see how knowledge is restructured in the
course of acquisition.”
Early studies by Novak et al. (1983) reported low correlations between concept
mapping scores and such conventional measures of learning as SAT scores and course
examination grades. However, to our knowledge, the issue of validiry of concept
mapping as an evaluation approach has not been fully explored in a carefully controlled
experimental environment. The present study sought to do just that, through random
assignment of subjects to treatment groups, use of computer-assisted instruction to
minimize variance attributable to instructional delivery, and careful documentation of
learning by conventional psychometric testing.
THE CONCEPT MAP AS A RESEARCH TOOL
I035
Method
Subjects
Subjects of this study were I I 1 elementary education majors who enrolled in five
sections of a science education methods course at East Carolina University, Greenville,
North Carolina. The course is normally taken during the junior year prior to student
teaching and requires, as prerequisites, a physical science and a life science course
for elementary school teachers.
Of the original 1 I I subjects, 20 were lost to absenteeism and normal class attrition.
As a result, complete data were available for 91 subjects (90 females and one male).
Procedure and Instrumentation
The entire experiment took place during six, 75-minute class sessions, and spanned
a period of three weeks. One session focused on each of the following activities:
training, practice, review, pretesting, instruction, and posttesting. Upon completion
of the experiment, a series of follow-up interviews were conducted.
Training. The first session was devoted to training subjects in the concept mapping
technique. In this period, subjects were introduced to operational definitions of terms
applied to concept maps: concepts, propositions, principles, theories, relationships,
hierarchy, cross-links, and general-to-specifc examples. Subjects were then presented
with examples of student-constructed concept maps, introduced to scoring criteria,
and given examples of scored maps.
Practice. During the second session, subjects were given an opportunity to
practice the concept mapping technique. Activities included a card-sorting exercise
for generating concept maps (Novak €2 Gowin, 1984), a review and discussion of
student-generated maps, and a homework assignment requiring subjects to develop
and submit a concept map based on their reading of a selected chapter in a middle
school science textbook.
Review. The third session was given over to review. The scored concept maps
were returned to the subjects, the scoring method was reexamined, and problematic
areas were discussed. Acetate transparencies of student-constructed maps served as
models for discussion.
Pretesting. The focus of the fourth session was pretesting. During this period,
subjects were administered a multiple-choicelfree-responseinventory which assayed
their knowledge of the experimental software package, “Life Zones in the Ocean.”
The purpose of this pretesting and subsequent posttesting procedure was to document
the extent of the learning that had occurred, using conventional psychometric methods.
The testing instrument was developed by the software publisher, Prentice-HalIlE4iunetics
(1986a, 1986b), and consists of a set of 40 knowledge, comprehension, and application
items. The alpha reliability was calculated at 0.76.
Following administration of the test, subjects were given a set of ten concept
labels and asked to develop a preinstruction concept map on the topic, “marine life
zones.” The following concept labels were supplied to assist the subjects with the task:
life zones in the ocean, abyssal zone, adapt, continental shey, intertidal zone, mineral,
neritic zone, photosynthetic zone, phytoplankton, and tide.
Instruction. The fifth session was devoted entirely to computer-assisted instruction
(CAI). Using a table of random numbers, subjects were assigned to experimental and
1036
WALLACE A N D MINTZES
control (“placebo”) treatment groups. Subjects (n = 42) in the experimental group
engaged in a CAI program which introduced basic concepts of “Life Zones in the
Ocean.” Those in the control group ( n = 49) received an equivalent exposure to an
unrelated topic: “Body Defenses.” The programs, which are commercially available
and widely used (Prentice-HaWEdunetics, 1986a, 1986b), were chosen because they
introduce domains of knowledge with which the subjects were judged to be relatively
unfamiliar. The mean completion time for both programs is approximately 45 minutes.
However, the subjects were encouraged to take as much time as they needed, to review
portions of the program where necessary, and to take notes if they so desired.
The experimental program, “Life Zones in the Ocean,” introduces students to
environmental conditions and life in the intertidal zone, variation of abiotic factors
(pressure, light, and temperature) within the neritic and open sea zones, and adaptations
of plants and animals within these zones. The control program, “Body Defenses,”
examines the body’s first, second, and third lines of defense against disease. Important
concepts include mechanical and chemical barriers to infection, the role of white blood
cells in fighting pathogens, and antigedantibody reactions.
Posttesting. The sixth and final session provided a time for posttesting. During
this period subjects were retested on their knowledge of “Life Zones in the Ocean”
and were asked to develop a postinstruction concept map on the topic “marine life
zones.” The posttesting instrument was identical to that used as a pretest. To the extent
possible, subjects in the experimental and control groups were treated identically in
all respects.
Post Hoc Interviews
One week after the completion of the experiment, ten subjects in the experimental
group were interviewed on their understanding of the program, “Life Zones in the
Ocean.” Five of these subjects had the lowest composite scores on the postinstruction
concept maps; the other five subjects had the highest composite scores.
Twenty-two line drawings taken from the software program served as visual stimuli
which helped to elicit propositional statements. The subjects were presented with each
stimulus and prompted to, “Tell me everything you can think of about this picture
from the unit ‘Life Zones in the Ocean’.”
The interviews were conducted in the privacy of a small room and responses were
audiotaped. Subsequently the tape recordings were transcribed verbatim and divided
into propositional statements.
Data Analysis
The data consisted of pre- and posttest scores on the “Life Zones” inventory, and
scores on the preinstruction and postinstruction concept maps. The analysis employed
a split plot factorial design with repeated measures (Campbell & Stanley, 1963; Pedhazur,
1982). Such a design enables the researcher to partial out variance attributable to
differences among subjects, thereby reducing the error variance.
A preliminary analysis of scores on the “Life Zones” inventory revealed, as
expected, small but significant differences [F (1, 89) = 5.47, p < .05] favoring the
experimental group (Table I). These differences, however, appear to be largely attributable
to pretest differentials, and the measurable effect of the experimental treatment on the
THE CONCEPT MAP AS A RESEARCH TOOL
1037
TABLE I
The Life Zones Invcntory: Means and Standard Deviations
Mranr
Group
Srdndard devlatlonr
PI
Pretest
Poatte\t
Prrte\t
Plibrle\r
Experimental
42
25 4
Control
49
23.6
28.6
46
26 2
65
4.0
4.1
posttest scores seems incremental at best. The analysis then shifted to the concept
maps. To what extent are these achievement differences reflected in the concept maps
that students draw? Two aspects of the concept maps were of interest: the concept
mapping scores and the number of critical concepts and propositions depicted.
Concept Mapping Scores. Concept mapping scores reveal the complexity of the
knowledge base and the structure of scientifically acceptable propositions embedded
in it. The scoring categories include the number of relationships, levels of hierarchy,
branchings, cross-links, and general-to-specific examples depicted in the concept map.
Several different scoring and weighting schemes have been used to quantify these
elements (Amaudin eta]., 1984; Novak, 1981; Novak & Gowin, 1984; Stuart, 1985).
For the purposes of this study, the following scoring method was used:
Relationships: one point for each valid proposition
Hierarchy: five points for each valid level of hierarchy
Branching: one point for each branching
Cross-Links:ten points for each valid cross link
General to Specific Examples: one point for each valid example.
CrificdConcepts and propositions. In an attempt to gauge the extent of bidogicaily
meaningful knowledge revealed in the concept maps, a panel composed of three outside
biology educators was asked to review the program “Life Zones in the Ocean” and to
develop their own concept maps. An analysis of these “template” maps produced a
set of “critical concepts and propositions,” that is, a set of concepts and propositions
which was deemed to be central to an understanding of the program.
Subsequently, each of the preinstruction and postinstruction maps was scored for
critical concepts and propositions. One point was given for each critical concept and
for each critical proposition or equivalent proposition judged to have the same semantic
meaning. The critical concepts are listed below. (Critical propositions are identified
in Figures 7, 8, and 9.)
Abyssal Zone
Adaptations
Bathyal Zone
Consumers
Environmental Conditions
Fish
Food Chain
Intertidal Zone
Light
Life Zones in Ocean
Neritic Zone
Open Sea Zone
Organisms (Other than Fish)
Photosynthesis
Photosynthetic Zone
Pressure
Producers
Solar Radiation
Temperature
Waves
WALLACE AND MINTZES
1038
Results and Discussion
Student Concept Maps
Figures 1 and 2 are examples of postinstruction concept maps drawn by students
in the control and experimental groups. These particular concept maps, like all others,
are idiosyncratic representations of domain-specific knowledge. Consequently, they
are neither “representative” nor “typical” of any group. Nevertheless, as examples,
the maps offer insight into some of the characteristics that are frequently seen in
students with differing levels of conceptual understanding.
On careful observation it is readily apparent that Barbara’s map depicts more valid
relationships than does Jennie’s. Furthermore, the hierarchical structure of Barbara’s
map is considerably more intricate, as is the branching pattern and the extent of crosslinkages, thus suggesting a substantially more differentiated and cohesive knowledge
base. Even a cursory, qualitative examination of Jennie’s map reveals a linear assemblage
LIFE ZONES IN
THE OCEAh‘
PHYTOPLANKTON
Fig. I .
Jennie’s concept map: an example from the control group.
THE CONCEPT MAP AS A RESEARCH M O L
I039
where occurs
where we fmd
Fig. 2. Barbara’s concept map: an example from the experimental group.
of linked concepts that are poorly integrated with related concepts, traits often seen
in concept maps of relative novices.
In addition to these traits, Jennie’s map lacks any valid general-to-specific eXaInpleS.
Interestingly, both she and Barbara depict “high’’ and “low” as examples of the concept
tide; however, both maps subordinate the latter concept to netitic zone, resulting in
an invalid propositional hierarchy.
The number of critical concepts and propositions in Barbara’s concept map is
somewhat greater than that in Jennie’s; however, an important difference is seen in
the number of alternative propositions or “misconceptions” in the two maps. As might
be expected, virtually all of Jennie’s propositions are scientifically unacceptable. And,
while Barbara does display an array of conceptual problems, a number of her propositions
are consistent with the explanations given in the software program.
A qualitative analysis of student concept maps such as these can offer rich and
detailed insights into the extent of meaningful learning resulting from classroom instruction. Such an analysis can also provide invaluable feedback for improving instruction.
I040
WALLACE AND MINTZES
For purposes of this study, however, the primary concern is the quantitative analysis
of differences in the complexity and propositional structure of the knowledge base as
depicted in student maps.
Concept Mapping Scores
Figure 3 summarizes the analysis of scores in the concept maps of students before
and after instruction. The analysis of variance revealed significant differences among
treatment groups in all five scoring categories.
The number of relationships in the concept maps of experimental subjects more
than doubled as a result of instruction, while no substantive changes were found in
the control group. These findings imply a significant shift in the degree of concept
differentiation and a change in the total number of scientifically acceptable propositions
encoded and stored in cognitive structure.
Additional evidence of progressive change in the knowledge structure is revealed
in the levels of hierarchy and the extent of branching depicted. The hierarchy scores
of the experimental group show an improvement of some 3096, in contrast to a slight
decline in the control group. Somewhat similar results are seen in the patterns of
branching where students in the control group actually improved by about 50% (possibly
a “practice effect”), while those in the experimental group jumped by over 120%.
The number of cross-links shown in the concept map is taken as a measure of
integration or cohesion in the knowledge base. Here we find a substantial amount of
variability from map to map, with some students depicting several such links and
others drawing none at all. Nevertheless, a comparison of pre- and postinstruction
scores reveals no change in the control group and a severalfold improvement in the
experimental group.
Finally, the number of general-to-specific examples depicted in the concept maps
was relatively small and the extent of variability was fairly high, with a slight decline
seen in both groups. Although significantdifferences were found favoring the experimental
group, it is uncertain in this case whether these differences can be meaningfully
interpreted.
Critical Cortceprs and Propositions
The mean number of critical concepts and propositions appearing in the concept
maps is summarized in Figure 4. The summary data suggest no change in the control
group but a substantial boost in the postinstruction maps of subjects in the experimental
group, where the number of critical concepts increased by over two-thirds and the
number of propositions jumped by nearly 150%. The analyses of variance confirm
these interpretations, indicating significant differences favoring the experimental group
in both critical concepts [F (1, 89) = 36.33, p < 0.011 and propositions [F (1, 89) =
50.24, p C 0.011.
A frequency analysis of student-generated critical concepts is given in Figures 5
and 6. These findings suggest substantial changes in the concept maps of subjects in
the experimental group with correspondingly little change in the control group. In
several instances (C1, C2, C7), the frequencies of critical concepts rose from 0 to
nearly 50%, in others (C4, C5, C9, C10) the improvement was less dramatic. In only
two instances (C3, C11) were no differences detected.
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POSTMAP = PO
PREMAP = PR
BEFORE AND AFTER INSTRUCTION
CONCEPT MAPPING SCORES
Fig. 3 . EffeLts of brief episodes of instructional intervention on concept mapping scores. [ F ( 1 . 89) = 30.3**
(relationships): 23.7** (hierarchy): 29.8** (branchings): I2.3** (cross-links): 4.3* (general-to-specific examples)].
CONCEPT MAPPING
SCORE
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Fig. 4.
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POST
CRITICAL CONCEPTS
PRE
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CRITICAL PROPOSITIONS"
RIE
Number of critical concepts and propositions in preinstruction and postinstruction concept maps.
NUMBER OF CRITICAL
CONCEPTSPROPS
MEAN AND (S.D.)
-
14
**P< .01
EXPERIMENTAL (N=42)
CONTROL (N=49)
CRJTICAL CONCEPTS AND PROPOSITIONS
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C 7 : LIGHT
C 5 : WAVES
C6* *
c7*
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CONTROL (N=49)
EXPERIMENTAL (N=42)
Fig. 5. Frequencies of critical concepts (C1 to C7) generated by students in pre- and postinstruction concept maps.
[ x 2 (3, N = 91) = 57.3** (Cl); 49.8** (C2); 3.4 (C3); 24.3** (C4); 27.9** (C5); 19.5** (C6); 45.4** (C7)].
c1* *
i
C4 : SOLAR RADIATION
C3 : ENVIRONMENTAL CONDITIONS
C2 ; BATHYALZONE
C1: OPEN SEAZONE
CRITICAL CONCEPTS
GENERATED BY STUDENTS
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C9 :FOOD CHAIN
C10 :PRODUCERS
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C8 :PRESSURE
*P< .05
CONTROL (N=49)
EXPERIMENTAL (N=42)
Fig. 6. Frequencies of critical concepts (C8to C14) generated by students in pre- and postinstruction concept maps.
[ x 2 (3, N = 91) = 41.8**(C8);16.4**(C9);10.0*(ClO);5.9 (C11);37.6**(C12);11.6**(C13);14.3**(C14)]
0
CRITICAL CONCEPTS
GENERATED BY STUDENTS
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THE CONCEPT MAP AS A RESEARCH TOOL
1045
In addition to these 14 critical concepts generated by the students themselves, 6
were supplied to the subjects to help them construct their maps. Except for one
(adaptations), these concepts appeared in 83%- 100% of the concept maps, with no
differences between treatment groups. Adaptations appeared in the postinsmction
maps of 49% and 90% of control and experimental subjects, respectively [ x 2 (3,N =
91) = 25.35,~< 0.011.
A similar but more complex pattern is seen in the frequencies of critical propositions
(Figures 7, 8, and 9). Here significant and, in several cases, substantial differences
were found in the frequencies of 17 out of 20 propositions. Except for one instance
(P4)where prior differences were found, virtually all of the changes in the concept
maps appear to be directly attributable to the brief instructional intervention.
For students in the experimental group, pre- to postmap improvement ranged from
17% (P15)to 50% (P6,P10). In the control group, differences ranged from a 14%
decline (P17)to a 17% improvement (Pl),with the frequencies of most propositions
showing essentially no change at all.
In some instances the frequency of a proposition can be explained, in part, by
the source and hierarchical locus of its constituent COnCeptS. Ibr example, the remarkably
high frequencies of the first two propositions (PI and P2) are instances where both
concept labels were supplied and where the concepts appear high in the knowledge
structure. On the other hand, as one progresses from “supplied” to “student generated”
concepts, and from higher to lower levels in the hierarchy (PI1 through P16), the
frequencies of propositions decline substantially.
Post Hoe Interviews
Figure 10 summarizes the mean number of critical concepts and propositions in
the interview transcripts of two groups of experimental subjects, those whose composite
postinstruction mapping scores were the five lowest and the five highest. The results
indicate that the highest exceed the lowest in critical concepts by about one-third ( 13.2
versus 10.0) and in critical propositions by almost 100% (58.8versus 29.8).
These differences suggest a potentially strong relationship between the complexity
of cognitive structure as revealed in concept maps and the extent of biologically
meaningful knowledge possessed by the learner. Although we find these results strongly
suggestive, the small sample size precludes further analysis. Additional studies which
combine the use of concept maps with clinical interview methods in this way would
be very helpful.
Conclusions and Implications
This study examined the concurrent validity of concept maps as vehicles for
documenting and exploring conceptual change in biology. The results suggest that
substantial and potentially important changes in both the complexity and propositional
structure of the knowledge base are revealed in concept maps after only 45 minutes
of computer-assisted instruction. Consequently, it appears that concept mapping offers
a valid and useful mechanism for looking at changes in cognitive structure.
The findings of this study, along with Some 10 years of practical experience in
using concept maps, have convinced US that many researchers might profit by adding
this approach to their personal repertoire of research methods. In using concept maps,
0
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0
20
40
60
80
94 100
140
P2
*
P3*
P4*
P5'
1
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P6*
[xz (3, N
= 91) =
P7- '
CONTROL (N=49)
EXPERIMENTAL (N=42)
CONCEFT LABEL SUPPLIED
STUDENT GENERATED CONCEPT
Fig. 7. Frequencies of critical propositions (P1 to P7) in pand postinstruction concept maps.
7.8 (Pl); 5.9 (P2); 27.8** (P3); 9.2* (P4); 33.7** (P5); 46.1** (w); 27.1** (P7)]
P P
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-7
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P5 ORGANISMS (0) OF INTERTIDAL(9... EXPOSED TO ENV. CONDITONS (0)
P4 INTERTIDAL
(m LIES BEWEEN HIGH & LOW TIDE LINES (0)
P3 LIFE ZONES IN OCEAN (9INCLUDE OPEN SEA (0)
P2 LIFE ZONES IN OCEAN (9) INCLUOE NERlTlC(9
P1 LIFE ZONES IN OCEAN (Q) INCLUDE INTERTIDAL (IT)
CRITICAL PROPOSITIONS 1
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60
R
-
-
-
YO 70
'O0
CONCEPT LABEL SUPPLIED
EXPERIMENTAL (N=42)
1
0 STUDEM GENERATU) CONCEPT
Fig. 8. Frequencies of critical propositions (P8 to P14)in pre- and postinstruction concept maps. [ x 2 (3.N = 91) =
41.0** (P8);53.5**(P9); 61.4**(PlO);37.4**(P11);37.4**(P12);27.1** (P13); 26.8** (P14)]
P14 FISH (0) ARE MOST ABUNDANT IN NERlTlC (9)
P12 LIGHT (0) IN OPEN SEA (0)...DECLINES WITH DEPTH
P13 TEMPERATURE (0) IN OPEN SEA (0)...DECLINES WITH DEPTH
P l 1 ATMOSPHERIC PRESSURE (0) IN OPEN SEA (0) INCREASESWITH DEPTH
P8 NERlTlC (m LIES BETWEEN LOW-TIDE LINE (9AND CONTINENTAL SHELF (9EDGE
P9 OPEN SEA (0) LIES BEYOND NERITIC (1)i
3 INCLUDESOPEN OCEAN
P10 OPEN SEA (0) INCLUDE PHOTOSHNTHETIC(9). BATHYAL (0) AND ABYSSAL ('c)
!
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PHYTOPLANKTON (0,ZOOPLANKTON (0) & FISH (0)
(m
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P19*
I
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CONCEPT LABEL SUPPLIED
[ x 2 (3, N
P20
=
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CONTROL (N=49)
EXPERIMENTAL (Nr42)
1
0
Fig. 9. Frequencies of critical propositions (P15 to P20) in pre- and postinstruction concept maps.
91) = 19.9** (P15); 31.6** (P16); 7.2 (P17); 33.9** (P18); 12.4** (P19); 34.3** (P20)]
P16* '
a
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p20 VARlATlONS (0) IN FISH ARE ADAPTATIONS (9) TO ENV. CONDITtONS(0)
P I 9 FISH (0)ABUNDANT IN NERlTlC (9) BECAUSE OF AVAIL. OF LIGHT (0) 8 MINERALS (9)
P I 8 NERlTlC (8) HAS SECOND FOOD CHAIN (0) OF SEAWEED (0).SHRIMP (0) 8 FISH (0)
PI7 NERlTlC
PI6 IN FOOD CHAIN (0).PRODUCERS (0) EATEN BY CONSUMERS (0)...EATEN BY LARGER CONSUMERS (0)
P15
-
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60
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CRITICAL PROPOSITIONS 15
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E
YEAN AND (SO)
CONCPrSlPROPS
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30
20
10
0
40-
-
50
d
0
N
v
h
09
CRITICAL
0
9
Y
U
a
-
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CRITICAL
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Low RVE
coNcEprs
PAOPOSmONS
Fig. 10. Number of critical concepts and propositions in interview transcripts.
NUMBER OF CRmCAL
-
1
60
70
CRITICAL CONCEPTS AND PROPOSITIONS
IN POST HOC INTERVIEWS
1
%
f
2m
1050
WALUCE AND MlNTZES
we have found that they complement, but usually do not duplicate, the work of other
techniques such as clinicaI interviews, soxting tasks, and conventionaltesting instruments.
The concept map is the only approach we have found that attends to both what students
know and how they organize their knowledge.
Of its many potential uses in research, we have found the concept map to be
especially valuable in documenting the "intelfectuaI journey" taken by students as they
restructure their understandings in individual courses and across the school years. In
our own work, for example, which explores the frequencies of "alternative conceptions"
in biology (Amaudin & Mintzes, 1985), we have enlisted the concept map in the
exploratory, inductive, or qualitative phase of the work. In subsequent phases we have
employed conventional psychometric approaches.
We should also add, from a purely practical standpoint, that concept mapping is
quickly taughr to experhental subjects, char it can be "administered" to large groups,
and that the product is readily interpreted. These are no small considerations when
one is attempting to probe understanding of complex, scientific concepts in young
minds.
In closing, we wish to suggest, as many natural scientists have, that good research
is theory driven but theory without method goes nowhere. Accordingly, we believe
that good research in science education must rest on a firm foundation of learning
theory; however, no matter how firm our theories are, understanding of complex
educational events depends on the development and application of powerful new tools.
We have found the concept map to be such a tool.
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We wish to thank Ms.Lisa Pike for her graphics expertise.
Manuscript accepted August 21, 1990.