Concept maps and Vee diagrams: two metacognitive tools to facilitate meaningful learning

Instructional Science 19:29-52 (1990) 29 © Kluwer Academic Publishers, Dordrecht - Printed in the Netherlands

Concept maps and Vee diagrams: two metacognitive tools to facilitate meaningful learning

JOSEPH D. N O V A K Department of Education, Cornetl University, Ithaca, NY 14853, U.S.A.

Abstract. This paper describes two metacognilive tools, concept mapping and Vce diagramming, and reports on research utilizing these tools from grades one through university instruction. The psychological and epistemological foundations underlying these tools is presented briefly. The issues of the dominantly rote-mode nature of much school learning and the resistance of students (and teachers) to move to meaningful learning strategies fostered by concept mapping and Vet diagramming are dis- cussed. The data available to date from a variety of qualitative and quantitative research studies strongly support the value of these metacognifive tools both for cognitive and affective gains.

Introduction

In the past decade, there has been a rapid increase in instruction that helps students "learn how to learn". This activity derived in part from advances in cognitive learning psychology (see Mayer, 1981) and the increase in cognitive learning research in school settings. Flavell (1985) defines metacognition as "cognition about cognition" (p. 104). Metacognitive learning occurs whenever a person acquires some general strategy that facilitates learning or understanding of knowledge. Weinstein (1987) has described strategies that can be used for reading comprehension. Ideally, the most powerful metacognitive learning would be acquisition of strategies that apply at any grade level and to any subject matter. The intelligent construction and use of concept maps and Vee diagrams are two widely applicable metacognitive strategies we have developed at Cornell University, and world-wide use of these strategies is being reported increasingly in the literature since publication of Learning how to learn, (Novak and Gowin, 1984; 1988).

Concept maps as we have have developed them are a representation of meaning or ideational frameworks specific to a domain of knowledge, for a given con- text of meaning. We define concept as a perceived regularity in events or objects, or records of events or objects, designated by a label. Most of the labels we use are words, but signs such as +, -, E and so forth may also be used. Two or more concepts can be linked together with words to form propositions and we see propositions as the units of psychological meaning. The meaning of any concept for a person would be represented by all of the propositional linkages the person could construct that include that concept. Since individuals have unique sequences of experiences leading to unique total sets of propositions, all concept meanings are

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I' Figure 1. A concept map showing key concepLs and propositions involved in concept mapping. Linking words together with concepts forms propositions and these am shown in a hierarchical sl.t'uc~rc..

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to some extent idiosyncratic. However, in a given culture, there is sufficient commonality in experience that persons in that culture share sufficient common meanings for their concepts that they can communicate ideas to one another using language or other symbols. For most of us, we only have to look at a blackboard filled with mathematical relationships expressed in symbols to realize that this represents a "different world", a world for which we have no meanings. Figure I shows a concept map on concept maps.

Over the past dozen years, our graduate students and other colleagues have found that all domains of knowledge can be represented by concept maps (concept/propositional structures). Figure 2 shows representations of knowledge structures in basketball. There is no domain of knowledge (or "skills") for which concept maps cannot be used as a representational tool, in our experience.

Vee diagrams (see Figure 3) are a heuristic tool developed by my colleague, Bob Gowin, to represent the structure of knowledge and the epistemological elements that are involved in new knowledge construction. Epistemology is that branch of philosophy that deals with the nature and structure of knowledge. Epistemological elements are those units that together from the structure of some segment of knowledge and are required to construct a new piece of knowledge. The Vee heuristic is based on a constructivist epistemology, as contrasted to the empiricist or positivist epistemology that has characterized popular views of "knowledge discovery" in most elementary textbooks of science and social sci- ences. Kuhn (1962), Toulmin (1972), Brown (1979), Popper (1982) and others have shown the inadequacies of positivistic (truth-falsity proving) epistemologies and most leading contemporary philosophers concerned with the nature of knowledge and knowledge construction are agreed upon some form of constructivist

epistemology. Conslructivist epistemology sees production of new knowledge as a human construction, with all the power and weaknesses associated with the ideational frameworks, instrumentation used, and emotional vagaries of human beings. The Vee heuristic represents a constructivist view of knowledge and iUus- trates the dozen or so epistemological elements that interact in the process of new knowledge construction. The Vee heuristic can also be used to dissect an existing domain of knowledge and to see its structural elements. Figure 4 shows a representation of this for one area of biology.

My work and the work of my students has been based upon Ausubel's assimi- lation theory (1963, 1968) of cognitive learning for the past quarter century. In his epigraph to his 1968 book, Ausubel asserts: "If I had to reduce all of educa° tional psychology to just one principle, I would say this: The most important single factor influencing learning is what the learner already knows. Ascertain this and teach him accordingly." It is this fundamental principle that led our research group to search for better ways to represent "what the learner already knows" and to develop the tool of concept mapping in 1972. Although we developed this for

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research purposes to represent student's knowledge slructures before and after instruction, we soon learned that concept maps could be a useful tool to help students move from learning by rote to learning meaningfully. We now see meaningful learning as the fundamental process that underlies useful knowledge acquisition and also new knowledge construction. I have argued that meaningful learning is the foundation for human constructivism which is both a psychological and an epistemological phenomenon. Figure 5 shows a concept map representation of this union of psychological and epistemological meaning making (from Novak, 1987). This representation of meaning making draws upon and incorpo- rates ideas from many contemporary psychologists and philosophers including the work of Ausubel et al. (1978); Donaldson (1978); Flavell (1985); Gowin (1981); Johnson-Laird (1983); Kelley (1955); Kuhn (1962); Mathews (1980); Mayer (1981, 1983); MacNamara (1982); Piaget (numerous writings); Popper (1982); Steinberg (1985); Toulmin (1972); Vygotsky (1962) and many others.

Figure 2, Two concept maps prepared by a basketball player, one (above) early in training and the other (right) late in the season. Note the increased complexity and integration of concepts of team defense and communication, emphasized in coaching, which was accompanied by much-improved player performance. ('From Novak and Gowin. 1984, p. 44)

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CONCEPTUAl/THEORETICAL

(THINKING)

METHODOLOGICAL

(DOING)

World view: The general belief system motivating and guiding the inquiry.

Philosophy: The beliefs about the nature of knowledge and knowing guiding the inquiry.

Theory: The general principles guiding the inquiry that explain why events or objects exhbit what is observed.

FOCUS QUESTION(S):

Questions that serve to focus the inquiry about events and/or objects studied.

Value claims: Statements based on knowledge claims that declare the worth or value of the inquiry.

Knowledge claims: Statements that answer the focus questions and are reasonable interpretations of the records (or data) obtained.

Principles: Statements of relationships between concepts that explain how events or objects can be expected to appear or behave.

Concepts: Perceived regularity in events or objects (or records of events or objects) designated by a label.

Transformations: Tables, graphs, concept maps, statistics, or other forms of organization of records made.

Records The observations made and recorded from the events/objects studied.

Events and/or objects: Description of the event(s) and/or object(s)

to be studied in order to answer the focus questions.

Figure 3. Gowin's Vec hcurcstic invented to iUustratc the conceptual and methodological elements that interact in the process of knowledge construction or in thc analysis of lectures or dooamcnts presenting knowledge.

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FOCUS QUESTION: Can we design an experiment to study some aspect of orientation behavior in an organism-its response to a particular stimuli, the classificelien of that response, and the posebls adaptive benefit of that behavior?

rt.~orr: Orientation behavior- stimulus-reaponse. Adaptalion and evolution of behavior.

Principles: 1). Orientation behavior is the act of turning or moving in a predictable way with respect to an external stimulus. 2). Orient. behavior can be classified as a kinesis (the speed or turning rate changes with no orientation of the body with respect to the stimulus) or a taxis (the body is directly orientated toward, away from, or at an angle to the stimulus). 3). Orient. behavior can be named based on three things: a. positive or negative (attracted or repulsed by the stimulus), b. stimulus type (chemo-, photo-, thermo-, etc), c, response of body - kinesis (tuming is klino-, speed is ortho-), or taxis (receptors used, at fixed angle to, memory based, sic). 4). Experiments to study orientation behavior should control for variablos, include replicates, and provide quantifiable data.

Concepta Orientation behavior, taxis, kinasis, stimulus, response, receptor, adaptation, orthokinosis, klinokinosls, humidity, schooling behavior, bilateral sense receptor, circus movements.

I I I I I I I I J l I_1

I I Ve/ue ©/aine: I 1). Designing and conducting a study gives I students experience with sciantilic knowledge I constructkin. 2). This lab is valuable for providing

experience with orientation behaviors and their adaptive signifk~ nce.

Knawlmdge clakna: 1 ). Isepads exhibit a positive hygrokinesis and a negative phofotaxis, 2). Blowfly larvae usually show a negative phofokllnotaxis. 3). Daphnia usually have a negative phototaxis and a pasitlve geotaxls. 4). Fish species vary in the strength of their schooling behavior. Most tend to spend more time with conapecifios and with the larger group of conspeoifics. This behavior is considered Io be a telotaxis.

TranJformationo: Total, average and graph data_ Compare observed turning or movement rates and time spent with various stimuli to definition of kinesis and taxis in order to decide on classification ol observed behavior.

Record=: Measurement of times spent near various stlmuit. Counts of Lures or numbers of organisms at specific time intervals. Measurement of distance traveled and time evolved.

Obji~¢~: Isepeds, petri dish experimental apparatus, desiccant, paper Iowels, black paper, lights, marking pens, map measurer, blowfly larvae, Daphnia, graduated cylinders, ring stands, black plastic, several species of fish, lost fish lank, jars. Events: Design a study using one of the experimental organisms to determine the type of orientation behavior used in response to a particular stimulus. Gather data, transform data, and present results. Consider adaptive significance of the observed behavior.

Figure 4. A Vee diagram produced by a student for laboratory work in a study by Robertson-Taylor (1985). A PC software program was used for the construction.

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Figure 5. A concept map showing key concepts and propositions involved in "human constructivism", uniting meanings from psychology and epistemology.

Classroom research using concept maps and vee diagrams

As noted above, the development of concept mapping derived from our research program wherein we sought to represent science concept meanings possessed by students before and after instruction. We were engaged in a twelve-year study of concept development and needed a tool to show simply but also explicitly the concept meanings a student possessed as indicated in modified Piagetian clinical interviews (see Pines et al., 1978). Figures 6 and 7 shows a representation of the concept/propositional framework held by a student in grade two and later in grade twelve. These maps were drawn from clinical interviews (see Novak and Gowin, 1984 and notedly Chapter 7) with the student They show growth in the number and relationships of concept meanings for this student over the ten-year span of schooling.

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Our first use of concept maps to help students learn subject matter meaningfully were in the areas of mathematics and science at the college level. Cardemone (1975) found that preparation of a "master" concept map for the topic of "ratio and proportion" helped him to plan instruction on this topic. Copies of his map were distributed to students but only a minority of students reported in their questionnaire responses that Cardemone's concept maps were helpful to them for learning of this topic. Similarly, Bogden (1977) found that concept maps prepared by him and a professor for each lecture in a genetics course were reported to be of value in learning genetics by a small minority of students. Some students indicated they were confused by concept maps prepared for them. Concept maps proved useful, however, in designing and interpreting answers for course examinations. The concept maps used by Cardemone and Bogden did not have words on the linking lines between concepts.

From the Cardemone and Bogden studies, we learned that the primary benefit of concept maps accrues to the person who constructs the maps. It was of little value to distribute teacher-prepared concept maps to students when the latter were not involved in constructing their own concept maps. In more recent work, we have found concept maps prepared by a teacher to be helpful to students, but only after they had practice in constructing their own concept maps. Also, we find that it is very important to have "linking words" on the lines connecting concepts in order to form explicit propositional statements. As concept maps begin to appear more widely in textbooks, it will be unfortunate if students are not instructed in preparation of concept maps and required to prepare some of their own maps. It will be even more unfortunate if teachers require students to memorize and dupli- cate exactly concept maps prepared by others,

During the period 1975 to 1977, I tried teaching upper elementary and secondary school children concept mapping in classroom settings, In general, students from grades four onward were successful in constructing concept maps and both students and teachers were enthusiastic about the value of concept mapping. In 1980, David Symington (in Melbourne, Australia) and I began using concept maps with children in grades one through six, again with success and enthusiasm expressed by students and their teachers. These early efforts were directed toward tryout of concept mapping strategies with various classes and in various subject matter areas, primarily to assess student and teacher reactions to the technique and to work out techniques for introducing concept mapping in a variety a classroom settings. As strategies to introduce concept mapping to students were refined, most students at all grade levels demonstrated success in constructing concept maps. These strategies were later described in Learning how to learn (Novak and Gowin, 1984, chapter 2). These early efforts with concept mapping in school settings made no attempt to evaluate the influence of concept mapping on student achievement.

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Figure 6. A concept map prepared from a clinical interview with Paul, a second grade student, repre- senting his knowledge of the "particulate structure of ruatter".

39

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O.

Figure 7. A concept map prepared from a clinical interview with Paul in twelfth grade. Note the extent of additional new concepts and propositional meanings compared with his knowledge in grade two (Figure 6).

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A similar tryout of the Vee heuristic occurred during 1975 to 1977, although

we did not attempt to introduce this tool below grade four. Later work has shown

that the Vee can be used successfully with primary grade children.

Moreira (1977) used concept maps with university students in physics.

Concept maps were used together with topical reorganization in "experimental"

classes and traditional subject matter organization (Halliday and Resnick, 1966)

was used in control classes and no concept maps were used. Moreira found that

students in the experimental classes performed significantly better on tests requir-

ing graphical structuring of physics concepts; this difference increased over the

semester course of study (Table 1). No significant differences between the groups

was found on lraditional course exams or on word association tests. Although the

use o f concept maps was confounded with content sequence reorganization, stu-

dents were increasingly positive about the value of concept maps as the semester

progressed; this may have been a significant conlribution to gains in mean scores.

Another finding illustrated in Moreira's data is a pattern of achievement that

we have subsequently seen repeated often when instructional strategies are used

that require meaningful learning. For two to four weeks we generally see an aver-

age decline in performance on standard course exams and then score averages

move up, usually finishing significantly higher for students using tools like

concept mapping and learning more meaningfully. This is shown in data from

Table 1. Average concept map test scores and t values for experimental and control groups on three tests given during the semester, on the basis of thrce criteria (general. specific and intermediate concepts indicated).

Test One Test Two Test Three

N Mean t N Mean t N Mean t

CRITERION Identification of General Concepts

Experimental 37 1.11 35 2.11 35 2.46 Control 35 1.23 -1.23 34 1.53 4.41"* 33 1.48 7.15"*

CRITERION Identification of Intermediate Concepts

Experimental 37 1.03 35 1.60 35 1.89 Control 35 1.06 -.63 34 1.18 3.67** 33 1.30 4.18"*

CRITERION Identification of Most Specific Concepts

Experimental 37 1.11 35 1.83 35 1.97 Control 35 1.20 --95 34 1.44 2.53* 33 1.52 2.81"*

+ (Store range was 0 to 3) (From Moreira, 1977, pp. 110-112) * P < . 0 5 **P<.01

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Moreira's study in Table 1. Student attitudes also tend to shift from generally negative toward the meaningful learning required to positive and sometimes highly positive attitudes both toward the instructional approach and toward the subject studied. These patterns account for the commonly observed significantly lower

average performance among "experimental" students exposed to a new strategy for only two to four weeks and "no significant differences" in mean scores achieved over 10 or 12 weeks when compared over-all with students in "control" or traditional instruction that usually rewards rote-mode learning. In addition, of course, a study using metacognitive or other strategies to encourage meaningful learning is not likely to show significant advantages over "control" methods when the evaluation instruments do not require meaningful learning and transfer of knowledge to novel contexts, and rote learning can suffice to achieve high scores.

Our first comprehensive study utilizing concept maps and Vee diagrams was conducted with junior high school students (Novak et al., 1983). Our principal focus in that study was also on methodological issues related to implementation of these strategies in school settings, including the issue of whether or not seventh and eighth grade students, taught by their teachers, would be successful in acquir- ing skill in use of the strategies. This study led to the following major fmdings:

1. Concept mapping and Vee diagramming skills continued to improve over the span of a school year.

2. Seventh grade students outperformed eighth grade students in use of the strategies, probably as a result of more practice and experience.

3. There was little correlation between success in acquisition of skill in using concept mapping and ability or achievement test scores (see Table 2).

4. Students using the strategies outperformed their counterparts on a test of novel problem solving by a wide margin (see Novak et al., 1983, p. 643).

The study led to the following conclusions:

1. Classroom teachers motivated to use new metacognitive learning strategies can be successful in employing concept mapping and Vee diagramming tools with junior high school science students.

2. Skill in use of these tools takes time, perhaps one to two years if used only in a single course.

3. Conventional measures of student ability/achievement are poor indicators of success with use of these strategies.

Novel problem solving success is significantly correlated with success in concept mapping scores.

Junior high school students have become adapted to primarily rote-mode learning and it is not easy to move them to meaningful learning strategies. This is an inference arising out of the data, but it has been corroborated by other studies we have done.

.

.

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Concept mapping when used in conjunction with other educational strategies has led to superior achievement Basconas and Novak (1985) found that mean scores on problem solving test in high school physics were two to three standard deviations higher for students preparing concept maps and following a revised sequence of topics to enhance building new learning on prior learning, when compared with students following a traditional physics program and not using concept maps. The concept mapping group excelled at all ability levels (based on Raven's Progressive Matrices test) and there was no significant interaction between treatment and ability (See Table 3).

By 1981, when the above study was nearing completion, we were keenly aware of the difficulties of moving both teachers and learners away from rote- mode learning and toward meaningful mode learning. Published textbook/ worksheet/test packages used in most science classes push teachers in the direc- tion of "covering the material". These materials take essentially no account of the conceptual difficulty of the topics presented and treat all information similarly, presenting key vocabulary words (concept labels) or problem solving algorithms

Table 2. Correlation matrix for variables in a study with jtmior high school science students. Top number is the correlation coefficient; the middle number represents the significance lcvd; the bottom number (in parentheses) represents the fizz of the sample for analysis. "Winebottl¢" problem was a novel transfer of knowledge open response question.

Total scorn Identifying, Total number SAT - SAT - on concept defining and of correct reading math map examples of relationships - percentile percentile

the Vee "Wineboale'"

Identifying, defining and cxalTlples on

the Vee

0.36 0.0001 (149)

Total correct 0.40 0.09 relationships - 0.001 0.572 - "Wineboule" (43) (46)

SAT reading -0.02 0.30 0.43 percentile 0.815 0.0003 0.0001

(146) (147) (80)

SAT math 0.02 0.30 0.39 percentilc 0.784 0.0001 0.0003

(146) (147) (80)

Final course 0.02 0.24 0.31 examination 0.796 0.002 0.035 grade (156) (158) (46)

0.77 0.0001 (200)

0.74 0.70 0.0001 0.0001 (155) (155)

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at about the same rate with little regard for the pupil's understanding. Students memorize word definitions or formulas usually with little or no understanding of the concept meanings represented by the words or symbols and with little or no relationship to prior learning, or anticipation of future, related conceptual learning. Topical sequence is of little importance since new conceptual understanding is not being built on prior conceptual learning. Extended absences, or new students moving into the school are a minimum difficulty when rote learning of new topics is the predominant practice. On the other hand, when instruction is focused on meaningful learning, prior course work, absences, and/or the sequence of topics in a course becomes very important. We had grossly underestimated the logistic, curricular and pedagogical practices that needed to be modified if maximum benefit was to accrue from the use of metacognitive tools and a focus on meaningful learning. In about half of the cases, teachers reverted to traditional instructional practices within weeks, or a year or two after introduction of concept mapping and/or use of the Vee heuristic. Only those teachers who refused to accept predominantly rote learning and associated satisfactory short-term test performance as standard practice have persisted in the use of these tools. This has been true, in our experience, at all educational levels from primary grades through adult education programs.

We were not alone on our failure to recognize the pervasive, pernicious charac- ter of rote learning and associated pedagogical strategies; however, most reports on the use of metacognitive strategies make no mention of this as a potential or real problem. We now see this as a major (if not the major) concern to be addressed when moving to include metacognitive strategies into real school settings. Of course, for short-term, isolated efforts with metacognitive tools, Hawthorn and other novelty effects may continue to show positive results for almost any reasonable metacognitive approach.

Table 3. Analysis of variance in problem-solving test scores for concept mapping and traditional groups.

Mean Mean Source df Square F Probability

Method 1 6836.19 480.49 0.00

Ability group** 2 36.97 2.60 0.08

Method x Ability 3 15.11 1.06 0.35

Error 70 14.23

** Based on Raven test scores From Bascones and Novak (1985)

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Recognizing the problem of student adherence to rote-mode learning patterns, we turned some of our attention to research on how students think they learn. Edmondson (1985) attempted to instruct Cornell University freshman in strategies to "learn how to learn". Seventy-two f~eshman who were selected from a new program providing financial aid to promising students were invited by letters to participate in the program. Twenty-one attended an orientation/introduction meeting, but only one remained in the program through a series of tutorial ses- sions. Most of the others said they "didn't have time" for the program, and some recognized that strategies for meaningful learning were not consistent with the way they study nor what they believed was required to pass courses. Piqued by this rejection of free tutorial help to "learn how to learn", Edmondson interviewed fifteen students in a college psychology course and found that only three (20%) were clearly committed to learning for meaning, and this in general has been a pattern observed in our studies on how school/university students learn.

From 1975 to date, I have taught a course at Corner University on "Learning to Learn". Although this course (Education 312) carried a number that suggests sophomore, junior and senior enrolment, in fact the course enrols almost exclu- sively juniors and seniors. Occasional freshmen who have enrolled (with my blessing) have dropped out early in the semester. It seems that the sophomore year is often a year of reckoning for students at Corner University when many find that their straight "A" averages in high school have dropped to B's, C's, or worse as they enter more advanced courses. Students begin to recognize that either they are just poorly endowed with intelligence, or they must be doing something wrong in the way in which they study. Some turn to "how to study" courses to get new ideas on "time management" or "confidence building" etc., while others recognize that something more basic is wrong with their learning/ study approaches, Some of the latter enrol in "Learning to Learn", and the over- whelming majority of these discover that indeed they are not stupid; they simply have been using weak learning strategies; they have been engaged in rote rather than meaningful learning. Some of these students comment that they never knew there was another way to learn other than to memorize definitions or "facts" and review answers to old exam questions. They also recognize that, except for an occasional course or studies related to their hobbies, they have rarely been meaningful learners. It should be noted that Cornell University students are on average the "best" of our high school graduates with SAT scores averaging in the 600's or better for most fields of study.

My experiences with Ed 312, Edmondson's work, and research we were doing on metacognitive learning all led to the same conclusion: the predominantly rote- mode learning practices encouraged (or required) in so much of school/university learning had put "braces on the brains" of many students, especially female students who tend to play the "school game" more conscientiously than males, (see

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Best, 1983; Belenky et al., 1985), accounting perhaps for some of the underrepre- sentation of women in science, mathematics and engineering (Ridley and Novak, 1984). Could these patterns of learning be reversed? Experiences with Ed 312 students, math students, graduate students in our programs, anecdotal comments from students in our junior high school study, and other "success stories" suggested the answer was clearly yes. In a study with college students in introductory biology, Robertson-Taylor (1985) utilized concept maps and Vee diagrams in a study to see if students could be helped to acquire a meaningful understanding of biology laboratory work. Her earlier research (Taylor, 1984) showed that the large majority of students had little or no understanding of how or why the results they observed in laboratory work could be explained. Most students moved through laboratory work "procedurally", doing the things prescribed in the laboratory guide, but with little or no understanding of why they were doing what they were doing, or the meaning of the data or observations they were recording. Surely, most of the readers of this paper will recollect science laboratory experiences where this was also true. Taylor sought to make biology laboratory experience meaningful, rewarding, and emotionally satisfying. She taught two laboratory sections (N=30) where students were instructed briefly in concept mapping and Vee diagramming techniques, and Taylor required each student to prepare either concept maps or Vee diagrams prior to each laboratory session. She had no control over and no influence upon the lectures given in the course by the professor. These were conducted in the usual "here are the facts you need to learn" manner and course examinations were the usual machine-scored multiple- choice, "What is the right answer" type.

What Taylor found was that on the objective course examinations, her students scored somewhat better, as was also true in previous semesters. Where the truly significant differences occurred were in the students' feelings and attitudes regarding biology and biology laboratory studies. Typical of the student comments were these given by students before their first lab and after their last session (from Taylor, 1985, p. 108).

PRE - I really dislike biology lab and wish I didn't. I guess I don't see the purposes behind the labs or the studies do not really interest me.

POST - Better this semester than last; concept maps a definite help! I like it more because I 'm understanding more. Much more organized than last semester.

f

PRE - Unfortunately, after coming out of a terrible lab last semester, I am very wary of biology lab and its actual meaning, even though it was one of my favorite courses throughout my secondary schools.

POST - My attitude toward bio lab is really positive now, especially compared to last semester. I prepare for class, try to be more attentive, and like it a lot.

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P R E - Last semester it was a chore and I dreaded coming because it was usually boring.

P O S T - This semester my attitude toward lab has greatly improved - I even look forward to going to lab. It seems much more worthwhile and I enjoy it most of the time.

In our more recent research, we have been interviewing Cornell University students to ascertain their learning approaches. Overwhelmingly, we have found that our students are engaged in essentially rote-mode learning. They recognize that "memorizing notes" has little long-term value, but they also fred that this is the most expedient way to earn high grades. Many of them also recognize that this kind of learning has little lasting value and is one of the reasons why they have negative feelings about the subject matter. Typical of quotes from these students are those cited in Edmondson (1985, p. 72-73), in response to her question, "Can you describe a meaningful learning experience you have had?"

Male Student: Everyone was developing questions.., we participated. You know, what you put into it is what you get out of it. And then, it wasn't like the student talking to the professor, it wasn't like one on one, it was like everyone was talking among themselves, and I don't believe the professor - it was like the professor was participating, but he wasn't trying to keep discussion going by asking questions; a lot of the students would do that themselves, by "Well, if that's this, then what happens when it does that? You know? Things like that...

Investigator: Is that different from the other classes that you have had here?

Male Student: Yeah. Well, see, that happened only once. It wasn't a structured class. It stands out because usually you're just listening. You're just watching and listening.

Female Student: When I felt like I was really learning.,. Um, I 'm trying to think. I can think of so many examples when I wasn't learning... (laughs) It's far rarer when you fred that where you do.

Working with college chemistry students, Feldsine (1987) found a resistance on the part of the majority of his students to prepare concept maps for topics (text chapters) studied. However, as the course progressed and "reluctant mappers" began to see that difficult topics became conceptually clear using concept maps, ~11 members of his class moved toward preparation of good to excellent maps. Moreover, Feldsine found in case after case in his qualitative analysis that important misconceptions regarding chemistry were recognized by students and subsequently altered, with stable, valid conceptions resulting. Given the wide recognition (see Helm and Novak, 1983; Novak, 1987) of the intractability of student misconceptions to conventional instruction, Feldsine's findings have important implications for improved pedagogy.

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Most of the studies done by my students at Cornell University have focused in recent years on qualitative, rather than quantitative, analysis of cognitive development. In part, this qualitative emphasis has been necessary to search for better understanding of the interplay of cognitive and affective factors in facilitation of meaningful learning and pedagogical strategies effective in encouraging students to move toward meaningful learning practices, Unfortunately, qualitative studies producing qualitative data are not easily reported in the form of short journal arti- cles. Fortunately, other researchers have begun to report quantitative studies on the effect of concept mapping and Vee diagramming strategies.

Sherris and Kahle (1984) used concept maps with 282 high school biology students in a five-week unit of instruction, comparing achievement with 259 students receiving instruction in the same content but without utilization of concept maps. They also administered the Norvicki-Stricldand locus of control scale. Using three forms of a 25-item multiple choice test and 5 short answer items requiring application of concepts and principles, they found no significant differences on posttest scores, nor on 6-week retention test scores, between the two treatment groups. However, there was a difference (P<.01) favoring internal locus of control students and a significant interaction effect (P<.03) on the retention test between treatment and locus of control, with "external" students benefiting more from the concept map aided instruction. Their study shows a five-week study unit may have only minimal effect on student learning patterns and achievement scores, although there may be some benefit on affective dimensions (e.g., locus of control).

Lehman, Carter and Kahle (1985) used concept maps and Vee diagrams with 119 inner-city black students and text outlining with 124 students in an 8-week biology unit. They found no significant differences in achievement scores between the groups. The fact that text outlining was a familiar strategy to these students and that the concept mapping/Vee diagramming group had to learn new strategies was suggested by the authors as a reason why only small, non- significantly higher mean scores were observed for the mapping group. Moreover, teachers were previously unfamiliar with concept mapping and Vee diagramming strategies and experienced some difficulties using these strategies.

In a similar study with I03 ninth grade general science students, Pankratius and Keith (1987) compared concept mapping and text outlining and found 10 per- cent higher mean scores for the concept mapping group over an 18 week period. No tests of significance was reported for this group. For a group of 139 twelfth grade physics students, Pankratius and Keith reported significantly higher (P <.05) mean achievement scores for students who prepared concept maps prior to and after a unit of study, as compared with a group who prepared maps only after they studied the unit. Both groups had practice with concept mapping for four preceding physics topics. The authors also noted that test items requiring "higher order thinking" showed wider differences, with 19 out of 23 correct answers to one item given by the concept mappers.

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Working with college students in a course on human anatomy and physiology, Clibum (1987) found that students using concept maps during a three-week unit on the skeletal systems showed significantly higher (P <.03) performance on a retention posttest but not on an immediate posttest when other covariates were held constant. He also found that students using concept maps gave few verbatim textbook answers to essay questions in another unit of study.

Alvarez and Risko (1987) used Vee diagrams with 28 third grade students studying seed germination. They found all students were successful in constructing Vee diagrams. Scoring the Vee diagrams (interrater reliability r =.96) showed no significant mean differences between groups with high Stanford Achievement Test (SAT) scores and those with low scores, which raises the question of the SAT as an indicator of ability. In another study with 25 first grade students, Alvarez and Risko (1987) found that all were successful in preparing concept maps and Vee diagrams. No statistical comparisons were made, but anecdotal reports showed that students at all stanine levels on the SAT performed well in construction of maps and diagrams and in classroom discussions on four different topics.

In a recent study by Okebukola (in press, a), concept maps were used with 138 high school biology students in Lagos, Nigeria. He found that the concept mapping group (N = 63) scored significantly higher than a non-mapping group (N = 75) on a genetics unit. Mean scores were 28.12 for the mapping group and 17.23 for the non-mapping group, yielding a t value of 16.01 (P <.001). For a study unit on ecology, mean scores were 25.98 for the concept mapping group and 19.11 for the non-mappers, with t = 12.27 (P <.001).

In a related study, Okebukola (in press, b) administered the Fraser, Nash and Fisher (1983) Science Anxiety Scale to the same groups of students noted above. This instrument gives a measure of the student's anxiety toward the study of selected concepts in science. Two versions were administered, one dealing with genetics concepts and another with ecology concepts. On both of the scales, Okebukola found highly significant differences in mean anxiety scores (P <.001) favoring the concept mapping students. Both test results and anecdotal comments showed that when meaningful learning was facilitated using concept maps, student anxiety levels toward study of the subject decrease and attitudes toward the study of biology became increasingly positive.

Summary and conclusions

Concept maps and Vee diagrams can be useful heuristics for planning instruction and textbooks. Our first major effort in curriculum design using concept maps was in the area of waste management where we developed a 21-module program for instruction in land application of wastes (Loehr eta/., 1979). We have found

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concept mapping and Vee diagrams useful in redesign of laboratory work in college physics (Chen, 1980; Buchweitz, 1981; Lavendowski, 1981). Other colleagues are using concept mapping in planning earth science courses (Ault, 1985), microbiology (Barenholz and Tamir, 1987) and other fields. The BSCS group in Colorado Springs is employing concept mapping to plan new elementary school and high school science programs. Several publishers now include concept mapping as a learning tool. It is likely that the majority of science books published in the future will include concept mapping, and perhaps also Vee diagramming, as metacognitive tools to help teachers and learners. Hoz (1987) and his colleagues at Beer-Sheva University are using these tools in teacher education programs and in medical education. We axe exploring ways to use these tools in our new MAT program for science and mathematics teachers at Comer University.

It is likely that concept mapping, and perhaps Vee diagramming, will become widely used metacognitive tools for science and mathematics education, as well as for education in other fields of study. No educational tool is so robust, so infallible that it cannot be abused. What could be worse than instruction where students are required to memorize exactly the structure of complex concept maps in their syllabus or textbook? I would not be surprised to learn that this is already happening somewhere in the world. On balance, however, I believe the growing body of research evidence will point toward a wider and better utilization of these metacognitive tools. As Italian, Spanish and Thai versions of Learning how to

learn now in press become available, hopefully world-wide experimentation, research and critical appraisal of these tools will increase substantially.

Acknowledgements

The Novak et al., 1983 study was supported by NSF Grant (SED-78-116761).

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Concept maps and Vee diagrams: two metacognitive tools to facilitate meaningful learning