CHAPTER
1
Learning, Teaching, and
Assessment: A Human
Constructivist Perspective
|OSEPH D, NOVAK
CoriuU Unwftstty
|OEL | MINTZES
Uiiivirsi(u o| Nortft Carolimi iinJ Nor(ii Cnri'liiia SIJIi UnivirsilM
|AMES H. WANDERSEE
Lomiiana State üiímnity
T H E ROLE OF ASSESSMENT
In 1973, joseph Schwab argued that every educative episode involves four
commonplaces. (I) the learner. (2) the teacher. (31 the subject matter or knowledge, and (4) the social milieu, We see value in these basic elements suggested by Schwab, but would add a fifth element |5) assessment (Novak,
1998) Whetherin school, work, orrecreation, so muchofwhatweachieveas
learners is controlled in good measure by how our performance is
appraised, evaluated, or rewarded. While we believe the primary motivation
for learning should be the satisfaction that comes with achieving competence, we need assessment to gauge the degree to which we approach or
attain high competence High-quality assessment can facilitate high-quality
learning, but unfortunately, poor assessment can deler or prevent highquality learning and may reward performance tlutt is deleterious to the
learnor in the long run Much has been written to show that too much
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|oseph 0. Novak, |oel I Minlzes, and lames H Wandersce
school testing can play this deleterious role, and some of the authors in this
book will address this problem. Our objective, however, is less to castigate
poorschool evaluation practices than to provide promisingalternatives.
We agree with Schwab (1973) that each of the commonplaces or elements
of education interacts with all of the other elements, and therefore no element
can be considered in isolation from the others, as is too often the practice in
books on testing or evaluatioiv Therefore, we begin by considering each of the
first four elements before proceeding to our focus on assessment.
T H E LEARNER
In the last quarter century, much progress has been made in our understanding of how humans learn and of the factors that influence their learning There is general agreement on the idea that, except for the neonate, all
learners come to a learning task with some relevant knowledge, feelings,
and skills By school age, children have already attained several thousand
concepts and language labels for these concepts. We see concepls as playing
a primary role in our theory of learning and our theory of knowledge and
hence we wish to define concepts very explicitly: Concepts are perceWcd regularities in events or oi>jecls, or records of events or objects, designated hy a lai>ei
Our evolutionary history has conferred on every normal child the capacityto recognize regularities in events orobjectsand to use language to label
these regularities. Thus children learn to recognize and correctly label
moms. dads, raining, running, and other such regularities. The language
they use to label these regularities depends on the social milieu in which
they are raised, but the capacity is universal. Of course, there are genetic
variations in the capacities to perceive specific kinds of regularities, and
some children see color, sounds, personal characteristics, and myriads of
other events or objects with greater acumen than others. This has led people to propose many "faces of intellect" (Guilford. 1959) or, more recently,
"multiple intelligences" (Gardner. 1983); but such classifications may do
more to obfuscate the fundamental capacity of humans to perceive regularities of various kinds and to label and use concepts than to illuminate the
process by which this basic form of learning occurs.
Learners do not store concepts as isolated bits: instead, they form relationships or connections between concepts to form propositions. Propositions
are statements about how some aspect of the universe is perceived or functions. Thus "sky is blue," "doggies have four legs." and "cells are units that
make up living things" are propositions about how some things are perceived, whereas "parlies are fun." "ice cools drinks." and "electrons move in
conductors are propositions about how some things function. Propositions
are unils of meaning, whereas concepts are the "atoms" that make up these
units. The idea that all knowledge Is constructed from concepts and rela-
t
Learning, Teaching, and Assessmenl
3
tionships between concepts represents our fundamental epistemológica!
beliefs, which are discussed further in the next section.
Learning may proceed in two different ways. RoIi learning occurs when the
learner makes no effort to relate new concepts and propositions to prior relevant knowledge he/she possesses. Meaningful learning occurs when the
learner seeks to relate new concepts and propositions to relevant existing
concepts and propositions in his/her cognitive structure. There is a continuum from rote learning to highly meaningful learning in that the degree of
the latter depends on the quantity of relevant knowledge the learner possesses, the quality of organization of relevant knowledge, and the degree of
effort made by the learner to integrate new with existing concepts and
propositions. These ideas can be illustrated using concept maps. Two concept
maps are shown in Figure !. Map (A) illustrates some of the missing concepts and misconceptions that are charactistic of rote learners, whereas
map (B) shows the organized knowledge of an "expert" meaningful learner
Another distinction in learning Is the contrast between surface and deep
learning (Marton 5- Saljo, 1976). Surface learning can be related to near rote
or very low levels of meaningful learning, whereas deep learning would be
characterized by relatively highly levels of meaningful learning.
Perhaps the best-known classification scheme is Blooms (1956) TdWiiomtj Bloom described 6 taxonomic levels for evaluation of learning ranging
from level 10. "recall ofspecifics." to level 5, "synthesis." and level 6, "evaluation Studies of classroom testing have shown that most test items do
not require more than level 1 performance. The consequence is that learning by rote can in some ways best achieve high performance on such test
items When the curriculum presents almost innumerable "factoids" or bits
of information to be recalled, it is almost impossible for most students to
consider how each of these "factoids" relates to what they already know or
to integrate the changed meanings that result as this information is assimilated The "overstuffed" curriculum in many science courses is one of the
reasons students resort to rote learning
Another reason students resort to rote learning is that they often possess
many invalid notions or misconceptions in virtually every domain of knowledge. Unless students have the time. encouragement, and the inclination to
reconstruct their faulty conceptual frameworks, they can do better on tests
in most content domains if they simply memorize the "correct" information,
procedure, oralgorithm Furthermore, teachers and textbooks can have idiosyncratic descriptions for specific concepts and propositions, and role
learning may be the most efficient strategy when verbatim recall of this
information is required. Other pitfalls of typical classroom testing will be
discussed in this book
in the course of meaningful learning, the learners knowledge structure,
or cognitive structure, becomes more complex and better organized
According to Ausubel (1963. 1968, 1978) this occurs as a result of four
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characteristic of meaningful learners
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6
|oseph D Novak, |oel I Minlics. and )ames H Wandcrsee
processes, siii'sumplioti. progressive differenUation. integrative nvoiidlwlioii. and
si<;'iror(/iiiiiii' learning First and most common is the process of sui'simiplioii,
wherein new concepts and/or propositions are subsumed under and related
to more inclusive concepts and propositions. For example, a young child
perceives a variety of dogs and acquires the concept of do^. Subsequently
the child learns that some dogs are called terriers, some are collies, and so
on. These latter concepts are subsumed under the child's concept of dog
and give greater clarity, complexity, and meaning to his/her dog concept. For
the domain of knowledge dogs, the child has achieved what Ausubel calls
progressive differentiation. His/her dog concept may now include the ideas that
terriers have short hair and collies have long hair. A young child may see a
cow or horse at a distance and call these doggies also, but the child soon
learns that these animals have features that are designated by different concept labels. Thus the child's cognitive structure undergoes further progressive differentiation and also integnnive reconciiialions: that is. things that were
first confused as dogs are now recognized as similar but also as different in
significant ways—and designated by different concept labels. This sorting
oul and refining of meanings that at first appear confusing or contradictory
is achieved through integrative reconciliation, which in turn leads Io further
progressive differentiation of cognitive slructure.
Cognitive structure development usually proceeds in an "up and down"
manner. First, a learner may acquire a concept of average generality and
inclusiveness He/she then proceeds from this Io distinguish concepls with
greater and greater detail or specificity and Io gain some concepts of greater
generality and inclusiveness Thus, in our example, dog or doggies may be
the initial concept developed, followed by concepls of terrier or collie, and
perhaps concepts of canine or mammal In due course, a more complex,
well-integrated knowledge structure emerges. The challenge we face in evaluation is Io assess the degree to which learners are developing lheir conceptual framework by which they can achieve both greater precision and
specificity of conceptual understanding, as well as mastery of more powerful, more general, more inclusive relevant concepts.
Recognizing that distant things appcar\o be smaller (cows look like dogs]
is also part of cognitive development, v/hereby concepts of scale and context are being developed and refined. The importance of the context in
which events and objects are embedded is one aspect of constructing va!id
meanings that all learners come to recognize with lesser or greater sophistication Some researchers have also found this to be important in what
they describe as "situated cognition" (Brown. Collins, & Duquid. 1989)
One threat Io assessment validity is thal information learned in one context may not be transferred and utilized in a different context. Test items
that require use of knowledge only in the same context jn which it was
learned do not assess higher levels of meaningful learning. When learners
achieve a high degree of differentiation and integration of knowledge in a
7
1 Leaming.Teaching.andAssessmem
particular subject matter domain, they are capable of transferring or applying that knowledge in a wide variety of new contexts We return to this issue
in lalerchapters.
The fourth process of meaningful learning described by Ausubel is superordinale learning. Early in a child's cognitive development, the most general,
most inclusive concepts lhe child acquires are relatively limited in the scope
of events and/or objects they reier to. Mommies, daddies, and doggies serve
as some of these fundamental concepls that subsume other more specific
concepts However, as cognitive development proceeds, the child acquires
more general, more inclusive superordinate concepts. For the preschool
youngster, these may include concepts such as people, mammals, energy,
and time In later years superordinate concepts such as religion, the Dark
Ages, evolution, and entropy may be acquired. Meaningful learning of
superordinate concepts confers new meaning Io relevant subordinate concepts and propositions and may also facilitate integrative reconciliation of
concepts. Thus the acquisition of powerful superordinate concepts should
be a primary goal of effective science teaching (Novak. 1977: Mintzes. Wandersee. & Novak, 1998). Unfortunately, for much science teaching, students
and teachers are preoccupied with the acquisition (usually by rote learning)
of numerous facts, problem-solving algorithms, and information classification schemes with little underlying conceptual coherence. The result is thal
students fail to acquire well-organized conceptual frameworks includins;
powerful superordinate concepts
One of the challenges we address in this book is how to design assessment strategies that encourage high levels of meaningful learning, including
the development of well-integrated superordinate concepts. We focus on
this commitment in each of the following chapters, albeit within a variety of
perspectives.
T H E TEACHER
Given what we have said about learning and the learner, it is evident thal
teachers have a very challenging role to play In the educative process. First,
they must seek to understand the major superordinate and subordinate
concepts of their field and Io integrate these into a complex, integrated,
hierarchical structure. This is no small task. So many preservice science
courses in colleges and universities are little more than a deluge of information or problem-solving algorithms to be memorized and reproduced on
tests Both the pedagogy and the assessment practices in these courses
often do little to foster development of the kind of knowledge frameworks
thal are needed for effective science teaching. So prospective science teachers must seek on their own initiative to build this kind of understanding oi
their field
8
loscph D. Novak, |oel |. Mintzes. and )ames H. Wandersco
Second, the context in which teachers learn most of lheir science is
divorced from the real world To create an appropriate context for their own
teaching, teachers must seek other experiences, such as field courses and
laboratory research opporlunilies. and they must work to integrate the
"book learning" wilh the knowledge, skills, and attitudes acquired through
these experiences.
Third, teachers must learn ways to plan lheir own curriculum, they musl
be able to sequence topics in such a way lhat new knowledge Is more easily
buill on previous learning, and lhey must master a set of strategies that aim
at helping learners restructure their scientific understandings. In the past 25
years we have come to recognize lhat helping learners change the way they
lhink about natural objects and events is far more difficult than we used Io
believe and that often this process extends well beyond the lime constraints
of the typical school year. Finding appropriate contexts for meaningful
learning within the constraints of school structures is a major challenge that
we have not even begun to seriously address.
Finally, teachers must plan and implement assessment strategies that
support meaningful learning and help to achieve the kind of conceptual
understandings, feelings, and actions that empower students to be more
effective in whatever future work they pursue
We have offered many ideas on how to achieve these goals in Teaclnng Science for Uiirfmlaiiiiim?. and we shall not repeat them here. Nevertheless, we
shall attempt to be consistent with the suggestions in that book as we focus
on new ideas for assessment in this book
KNOWLEDGE A N D KNOWLEDGE CREATION
There is the age-old question. Whal Is knowledge? Humans have pondered
the question for millennia. There have been significant advances in the past
3 decades in our understanding of the nature of knowledge, and also In our
understanding of the process of knowledge creation. Perhaps the most
important idea is that knowledge is not "discovered" as are diamonds or
archeological artifacts, but rather it is "created" by human beings. Knowledge
is a fiumiiii coiisliwlimi lhat is a natural outgrowth oj lhe capacitij oj iiiiitimi beings |or
fiitliiltTWso/mrtiniMijA(/fOTniififl(Novak. 1977; 1993; I998;Minlzes.Wandersee.
& Novak. 1998). |ust as the building blocks for learning and acquisition of
knowledge by an individual are concepts and propositions, lhese are also
lhe building blocks of knowledge. Understanding the process of meaningful
learning is fundamental Io understanding the process of knowledge creation
With the explosive growth of information on the Internet, anyone who
"surfs the net" soon recognizes the overwhelming amount of information
available. But is information knowledge? From our perspective, knowledge
I Learning, Teaching, and Assessment
0
has organization and potential for application in problem solving. The difficulty
with all of the information on the Internet is that much of il is not available
in a form that allows easy organization and application. There are search
engines and "crawlers" that seek oul and organize some of the information
available, but these are usually for special-purpose searches. Unless we
design special-purpose search engines or crawlers for our own needs, information taken from the Internet can be overwhelming chaos. There is a bright
future on the horizon, with new special-purpose search tools appearing, but
al this writing, gaining information lhat can be easily structured to our specific needs can be a daunting challenge.
Another characteristic of knowledge stored in the human brain is that
every piece of knowledge is associated to some degree with feelings or
affect. Thus the successful application of knowledge depends not only on
how much knowledge we have and how we organize it, but also on lhe feelings we associate with our knowledge. This is discussed in Keller's biography (1983), A FfriiMi) for the Organism. The life and Worij of Barbara McCli;iiod' In
a more prosaic manner. Herrigel (1973) presented some of the same ideas in
his ZfM in (AiArI ofAnheru Biographies ofgeniuses almost always emphasize
not the amount of these information that people possess but rather their
dogged perseverance and their feelings regarding the best questions or
approaches Io pursue. This is as true in the arls and humanities as It Is In
the sciences, or perhaps even more so.
In so much of school assessment, emotion plays lillle or no role; strong
feelings may even prove a liability. While we tend to see more emphasis on
expressing emotions in the arts and humanities, too often an individual's
freedom Io express emotions is suppressed in these disciplines as well.
Emotions or feelings motivate. We seek to do those things lhat make us feel
good, and we avoid those things that make us feel bad. If one of our goals is
Io make students more creative, more motivated to do something positive
with their lives, then we face the challenge of using evaluation strategies
that reward high levels of meaningful learning.
Poor testing practices can reward the wrong kind of learning. One way to
increase the distribution or "spread" of scores on a test is Io require recall of
relatively minute details or bits of insignificant information. Such practices
lend to discourage learners from looking for the "big ideas" in a domain of
study and seeking to organize knowledge hierarchically, with the "big ideas"
playing a dominant role. The development ofstrong positive feelings toward
elegant" organizations of knowledge and the wide span of relevant applications of powerful ideas is also discouraged. These are some of the issues we
shall address in this book.
The process of knowledge creation involves the interplay of at least 12
elements We have found it helpful Io represent the process using the vee
heurislicdeveloped by Gowin (1981; Novak & Gowin, 1984), Figure 2 shows
how these epistemological elements can be defined and related Elements
Ioscph D Novak, loel 1. Mintíe*. and )amcs H Wsndersee
THE KNOWLEDGE VEE
METHODOLOGICAL
(Doing)
CONCEPTUALA'HEORETICAL
(Thinkinf;)
WORLDVIEWt
FOCUS QUESTIONS
Questions that scrvc
to focus lhe inquir>
about events and/or
objects sludied
The general bclicfand
knowledge sysleni
motivaüng and guiding
the inquiry
PHILOSOPHY/
EPISTEMOLOGY:
The beliers alxiul the nature
of knowledge and knowing
guiding thc iiu)iiir>.
VALUECLAIMS:
Sutcnicnts based on
knowledge claims that
declare the worth or
value of tbe inquiry.
KNOWLEDGE CLAINK:
Sutemenu (hat answer thc
focus question(s) and ate
reasonable interpretations
of the records and transformed records (or data)
obtained.
THEORY:
The general principles guiding lhe inquiry that explain
why events or ohjecw exhibit
what is observed.
PRINClPLHS:
Statements of relationships
between concepts that explain
ho>v events or objectj can bc
expected Io appear or behave.
TRANSKORMATIONS:
Tab)cs. graphs, concept
maps, s(a(istics. or oüicr
forms of organization of
records made.
CONSTRUCTS:
Ideas showing specific relationships between conccpU,
'Althcuji direct origin in events
or objects
RECORDS:
The observations made
and recorded from thc
events/objects studied.
CONCEPTS:
Perceived regularity in events
or objects (or records of events
or object?! designated by a label
EVENTS AND/OR OBJECTS:
Description of thc cvcnl(s)
and/or object(s) to bc
studied in order to answer
the focus question.
FIGURE2
The knowledge vee for the 12 elements thal are involved in creating or
understanding knowledge in any domain. The elements on the left side of
the vee are used by the learner to select events and focus questions and Io
perform the actions on the right side of the vee thal lead to learning and
lhe creation of knowledge AlI elements interact wilh each other
on lhe left side represent the conceptual/theoretical elements These are
the knowledge structure and values lhat guide the inquiry On the right side
of lhe vee are the methodological or procedural elements that are involved
in the creation of new knowledge and value claims. Selecting the right"
focus question and the "right" events and/or objects to observe depends on
I Learning. Teaching, and Assessment
Il
the knowledge, feelings, and values the creator brings to the process It is
evident from the elements shown in the vee lhal the process of knowledge
creation is In some ways simple—only 12 elements are involved—and in
other ways enormously complex. There are almost an infinite number of
questions that may be asked and almost an infinite number of events or
objects Io be observed in any domain of knowledge. How do students learn
to ask lhe right questions, observe the appropriate objects and events, make
the important records, perform the best transformations, and construct the
most powerful knowledge and value claims? There are no simple answers to
these questions. The best we can hope to do Is to help the learner develop
the most powerful knowledge structures possible and help to impart a deep
respect for and drive to create new knowledge. We shall attempt to show
how improved assessment practices can help to achieve these goals. The
use of the vee heuristic as an assessment tool is discussed in Chapter 4.
THE SOCIAL MlLIEU
Education takes place in a social context. As societies change, new
demands are placed on schools. After the USSR launched Sputnik in 1957,
there was a public outcry for improving science and mathematics education
in our schools. One response was to increase funding for science education
at the National Science Foundation (NSF). The primary goal ofthese programs was to devise new textbooks and support for teacher education programs. Despite the expenditure of several billion dollars by federal agencies
and school districts Io improve science and mathematics education, there is
little evidence that we have made significant progress, as indicated by international comparisons of student achievement in the United States and
other developed democracies (see Chapter 12). There are. of course, many
reasons for this, but at least one important factor is that little was done to
improve assessment practices in past "reform" movements. As long as the
predominant mode of assessment stressed recall of facts and problem-solving algorithms, students continued to engage In rote learning practices.
While there were attempts to produce laboratory study guides with more
emphasis on enquiry approaches to learning, these were often taught in a
way that reduced the labs to little more than "cookbook" verification exercises. Additionally, most schools did not adopt the new NSF-sponsored curricula, for a variety of social, political, and economic reasons.
Currently the dominant factor influencing change in science and mathematics education comes from the recent effort to establish standards." The
two most prominent efforts in this have been the workof the American Association forAdvancement ofScience (AAAS), BenchmarksforSdence Literacy—Project 2061 (1993). and the National Academy of Sciences (NAS), National
Research Council. National Science Education Standards (19961 Both of these pub-
12
|oseph D Novak. Ioei I MinUes, and Iamcs H Wandersee
licalions were developed with counsel from scientists, outstanding teachers,
and science educators. The participants in lhe process of creating the standards were obviously well-recognized experts, but as is so often the case,
there were other experts whose ideas were not solicited or not included. For
example, the views of those experts who do not feel that inquiry approaches
are lhe best method of instruction for all science content were not included in
the NAS committees. This, in fact, is a principal problem in the way science
curricula are currently organized, taught, and evaluated
Although the AAAS Benchmarks give more recognition to the variety of
views on teaching approaches and grade level appropriateness ol certain
science topics, lhey are nevertheless very conservative in what they suggest
can be taught in the lower grades. This, in ourview, is a serious limitation.
Some concepts, such as the particulate nature of matter, are so fundamental to understanding most of science that postponing instruction on these
concepts postpones the chance for developing understanding of most basic
science phenomena. As Novak and Musonda (19911 showed in their 12-year
longitudinal study of children's science concept development, instruction in
the particulate nature of maller in grades 1 and 2 can influence children's
science learning throughout their schooling.
Another area that is largely ignored by the Stíiiuitirds and Benchmarks is the
important role thal metacognitive instruction can play when it is an integral
part of the curriculum for grades K-12. To ignore this is to ignore research
that suggests enormous gains in learning when metacognitive tools and
ideas are properly taught and utilized (Mintzes et al., 1998; Novak, 1998).
The net result of most current curriculum efforts is that there is still an
emphasis on what is essentially a "laundry list" of topics Io be taught
Although most curriculum groups expound the idea thal "more Is less." the
lists of topics Io be taught in the Siamiiir<fs, Benchmarks, and other curriculum
proposals remain overwhelming. AlI are a far cry from the guidelines proposed in 1964 by the National Science Teachers Association Curriculum
Committee suggesting seven major conceptual schemes and five characteristics of the process of science (Novak. 1964, 1966) as the basis for the
design of K-12 science curricula.
With growing public and political pressure on accountability in schools,
we are witnessing loday a renewed emphasis on testing in science and other
areas of the curriculum. While we support the need for accountability, much
of the testing done in school, state, and national programs falls far short of
evaluation thal assesses understanding of science concepts and methodologies. The net result may be inadvertently Io encourage classroom activities
thai support rote ratherthan meaningful learning. We recognize the central
role of traditional assessment practices as one of the most significant deterents Io meaningful learning, and this recognition has led us to develop and
evaluate several powerful new alternative assessment strategies that are
described in this book.
13
I Learning, Teaching, and Assessment
A FOREWORD
In lhe chapters that follow, we expand on the nature of science learning
and constuctivisl views thal underlie lhe alternative assessment practices
we recommend. Each of the well-known contributors to this volume has
had experience in applying the ideas presented, and each draws on lhis
experience Io suggest ways of improving teaching and assessment in
science With this brief introduction Io four of the five commonplaces of education, we invite you now to consider the fifth: new approaches to assessing
science i(mlm(amiitu)
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