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LEARNING SCIENCE: THE VERY IDEA
RUNNING HEAD: LEARNING SCIENCE: THE VERY IDEA
Learning Science: The Very Idea
Liam Rourke
Assistant Professor
Learning Science and Technology Academic Group
National Institute of Education
Nanyang Technological University
Singapore
[email protected]
(65) 6790-3349
Norm Friesen
Applied Communication Technology Lab
School of Communication
Simon Fraser University
Vancouver, BC
[email protected]
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Abstract
Attempts to frame the study of teaching and learning in explicitly scientific terms are
not new, but they have recently been growing in prominence. Societies, journals,
conferences, handbooks, and centers of learning science are appearing with
remarkable frequency. However, in most of these invocations of an educational
science, the term science is itself understood in exclusively progressivist, positivistic
terms. More recent theory, sociology, and everyday practice of science are ignored in
favour of appeals to idealized scientific rigour and efficiency. We begin this paper by
considering a number of examples of prominent scholarship undermining this
idealization (e.g., Popper, Kuhn, Latour, Woolgar). We then argue that learning and
education are inescapably interpretive activities that can only be configured
rhetorically rather than substantially as a science. We conclude by arguing for the
relevance of a broader and self-consciously rhetorical/metaphorical conception of
science, one that would include the possibility of an interpretive human science.
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Learning Science: The Very Idea
In 1781, Kant surveyed the advances of mathematicians and geometers, and he
compared their progress to the work of the philosophers with woe. He characterized all
of metaphysics to that point as random groping and longed for certain, progressive
knowledge (p. 17). In the late 1980s, a similar mood took hold among a group of
educational researchers. Those who had embraced cognitive science felt their approach
presented, as last, a way beyond the random groping of previous research on teaching and
learning. Its certain and progressive nature, moreover, would lead to robust
improvements to educational practice (Kolodner, 1991).
In its current state, this movement is called the learning sciences. The Journal of
the Learning Sciences (JLS) was established in 1991 as its principle forum, a handbook is
forthcoming (Sawyer, 2006), and a handful of learning science programs have popped up
in universities in the United States, Europe, and South East Asia. In this article we
critique the effort to reconstruct educational inquiry as learning science. In it, we address
four questions, 1) What is learning science in its current form 2) What is science,
generally considered? 3) Is science something to which all educational researchers should
aspire? And 4) What might we do instead? In addressing these questions, we argue 1)
current understandings and practices of science, as revealed by philosophers, historians,
and sociologists of science are quite different from the idealized version held by those
most committed to learning science; 2) relapsing into a positivistic approach to the study
of human action ignores major intellectual movements of the 20th century, and 3)
movements underway in this century, including phronetic (i.e., socially responsible)
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social science and hermeneutic psychology offer more promising ways to understand and
affect educational practice.
Science
To understand the current popularity of learning science we are forced to rehearse
a story that was told and retold frequently in the latter part of the 20th century. The story
typically begins by identifying the attributes that comprise an orthodox definition of
science and then follows the abandonment of each attribute as they were scrutinized by
philosophers of science and sociologists --and in many cases, by scientists themselves.
For Western chroniclers, the story of the scientific enterprise often begins in 15th
or 16th centuries, and its function is to help us distinguish the Middle (or Dark) Ages from
the Enlightenment (or the Age of Reason). In the former era, knowing and acting were
informed by recourse to sacred texts and the interpreters of these texts. In the latter era,
these endeavors came to be founded on increasingly formalized processes of observation
(theory-driven and replicable), abstract representations (models, theories, and ontologies),
and empirical verification. In this classical formulation, scientists had privileged access to
the natural world, a world that was objective or pre-existing. Employing an agreed upon
methodology, these trained practioners described and explained the phenomena that they
discovered, and this enabled them to predict and modify outcomes.
Learning science
To what extent do these principles reflect the understanding of science
propounded by learning scientists? As we await a canonical text and codified
terminology (e.g., a ‘handbook of learning science’), we will induce this understanding
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through a survey of their practice. Because science is often defined, at its root, in terms of
the scientific method, we look for this definition in the methods of the learning sciences.
Learning scientists employ several methods of inquiry, most of which have been
borrowed from other fields and adapted to educational interests. One method however, is
emerging within, and is unique to, the learning sciences. It is referred to variously as
design research (Collins, Joseph, & Bielaczyc, 2004; Kelly, 2004; Reeves, 2000; Wang
& Reeves, 2004), design experiments (Brown, 1992; Collins, 1992; diSessa & Cobb,
2004), design based research (Barab, & Squire, 2004; Dede, 2004) or developmental
research (van den Akker, 1999; Ritchie, 1996). Design based research (DBR)—the term
we settled on for this article—and learning science are reflections of each other, we
argue, or mutually constitutive in the way that ethnography is of cultural anthropology or
conversation analysis is of ethnomethodology.
As with science, it is difficult to locate a concise, consensual definition of DBR.
Separately, authors attend either to its goals, its epistemological commitments, or its
procedures. Where these discussions overlap, there are tensions. To move our discussion
forward, we offer our general and somewhat awkward definition: DBR is a method of
inquiry whose goal is to contribute equally to educational practice and learning theory
through formative case studies of interventions in naturalistic settings.
Formalization of the method began with publications in 1992 by Collins and
Brown, and much of our analyses will focus on Brown’s prescient article. Brown had
been trained as experimental psychologist in the 1960s and had engaged subsequently in
influential educational research programs. Moving across her career from behavioral to
cognitive concerns, her early research designs embodied the social sciences’
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interpretation of natural science: a) experimental and quasi-experimental designs, which
assured internal and external validity, b) laboratory studies, which allowed control and
manipulation of variables, c) formulation and testing of hypotheses deduced from
theories, which allowed advancement on prior work, and d) reliable and valid data
collection procedures analyzed statistically, which demonstrated the experimenter’s
detachment from the pre-existing reality under investigation.
Eventually, several problems gave rise to discontent with these strictures. First,
across their attempts to conduct a social science, many researchers realized that their
endeavors lacked many of the defining features of the scientific method. Brown (1992)
acknowledged that, unlike the natural sciences, much of educational research was not
progressive. For a short time and within a particular community, successive studies build
on previous ones, Brown maintained. However, after brief interludes of ‘progress,’ new
theoretical perspectives take over, accompanied by new questions, research designs, and
measurement instruments. These shifts derail the progressive sequence.
Similarly, Brown questioned the utility of a reductionist approach to educational
inquiry, which is also central to the scientific method. Reflecting on her studies of
educational practice, Brown painted a holistic, rather than reductionist, picture:
“Classroom life is synergistic,” she declared:
Aspects of it that are often treated independently, such as teacher training,
curriculum selection, testing, and so forth actually form part of a
systematic whole. Just as it is impossible to change one aspect of the
system without creating perturbations in others, so too it is difficult to
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study any one aspect independently from the whole operating system.
(Brown, 1992, p. 143)
Brown described further problems in imposing the methods of social science on
educational concerns. In her attempts to enhance learning theory and practice, she found
that the antiseptic and contrived environments of the laboratory were altering
fundamentally the phenomena she wished to study. In addition, the principles of teaching
and learning produced in these settings did not transfer to classrooms. Moreover, these
sites of educational practice were rife with conditions anathema to the researcher’s
devotion to rigour and objectivity. Using cognitivist research on memory as an
illustration, Brown reported, “These were issues of theory, attempts to unravel mysteries
of the memory system. The work had nothing to do with theories about how to make a
better learner. The players had absolutely no educational relevance in mind” (p. 145).
As a reflective practitioner with a genuine interest in the welfare of students and
teachers, Brown—and subsequently many educational researchers—found themselves
studying teaching and learning in ways that systematically violated the tenets of social
science research (cf. Campbell & Stanley, 1963). As Brown recalled, “My training was
that of a classic learning theorist prepared to work with subjects (rats, children,
sophomores), in strictly controlled laboratory settings. Those methods are not readily
transported to the research activities I currently oversee” (1992, p. 141). Contributors to
the recent JLS issue on DBR continue to grapple with the moral, epistemological, and
methodological issues that originally effected Brown over a decade ago.
Design based researchers traverse the line dividing two distinct orientations
toward research: post-positivism (eg., Cook & Campbell, 1979) and interpretivism (eg.
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Lincoln & Guba, 1985). Post-positivism maintains the values and processes of science
that we described previously, but recognizes that there will be some slippage in the
ability to realize these ideals when one studies human, agentive phenomenon rather than
natural phenomenon. Post-positivists admit that the judgment of the researcher plays a
role in interpreting of the results of experiments, and they have ritualized methods for
correcting this bias, subjectivity, or error (Malhotra, 1994). Interpretivists, on the other
hand, argue that this same interpretation on the part of the researcher is not an incidental
or undesirable process, but one that is both unavoidable as well as central and
foundational. Any study of human behaviour, they argue, is the active interpretation of
phenomena that are themselves intentional --consequently well beyond the realm of the
unproblematically “objective.”
The oscillation of practitioners of DBR between these two, very different
positions is widely evident in their writing. In the JLS special issue, readers encounter
characterizations of DBR as an interpretivist, constructivist endeavor, but they are
quickly referred to footnotes that return them to post-positivistic touchstones. Barab and
Squire (2004), for instance, offer the following description of DBR:
DBR focuses on understanding the messiness of real-world practice, with
context being a core part of the story and not an extraneous variable to be
trivialized. Further DBR involves flexible design revision, multiple
dependent variables, and capturing social interaction. In addition,
participants are not subjects assigned to treatments but instead treated as
co-participants in both the design and even the analysis. The focus is on
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characterizing situations as opposed to controlling variables. (Barab &
Squire, 2004, p. 5)
But hastily, they direct readers to this accompanying footnote:
It is important to note that this is not meant to deride the importance of
traditional psychological methods . . .. Design-based researchers should be
asking how their claims would benefit from more rigorous testing within
laboratory-based contexts. (Barab & Squire, 2004, p. 5)
Similar vacillations between programmatic declaration and countervailing qualification
appear throughout the special issue and elsewhere in related studies and discussions.
Such researchers put themselves in a double bind, a term invoking not only paradox, but
schizophrenic inconsistency (Bateson, Jackson, Haley & Weakland, 1956): Every move
they make toward a deeper understanding of local practices is a move away from reliable,
valid measurement and generalizable results. Conversely, assertions of the
generalizability, objectivity and scientific validity of their findings removes them from
their origin in situated, local and authentic practice.
In all but one article in the special issue (Dede, 2004), we sense a desire to retain
scientific terminology and the esteem, the hope of certainty, and the pursuant funding that
it entails while letting go of the scientific method and its epistemological,
methodological, and procedural commitments.
Critiques of Science by Philosophers and Historians of Science
Forty-three years after Kant offered his critique, Auguste Compte extended the
vision: “I believe that I shall succeed in having it recognized that there are laws as welldefined for the development of human species as for the fall of a stone” (Compte, 1974
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cited in Frankel & Wallen, 2000, p. 431). Two centuries after this proposal for a social
science put forward by the self-titled Pope of Positivism, efforts to formulate the
equivalent of the law of gravity for one area of human activity—teaching and learning—
have been elusive.
Prior to the pragmatic critiques of science offered by researchers such as Brown
(1992) who were interested human activities, foundational objections were being posed
by philosophers and historians of science, and later by sociologists.
One of these critics, philosopher Karl Popper (1959, 1963), took issue with the
assertion that empirical verification distinguished science from other modes of inquiry.
He argued that logically, no number of supportive experimental outcomes could confirm
a theory once and for all, and instead, proposed falsifiability as a more apt criterion for
scientific “truth.” Neatly summing up the difference, Einstein purportedly remarked, “No
amount of experimentation can prove me right, but a single experiment can prove me
wrong.” As this principle was ratified, Feyerabend (1975), a student of Popper’s (1959,
1963), pointed out that few theories are consistent with all experimental tests. Again,
Einstein colloquializes the issue for us: “If the facts don’t fit the theory; change the
facts.” Verification and falsification were categorical distinctions between scientific and
other types of inquiry. Their dismissal was consequential.
Even more consequential however were the challenges raised by another of
Popper’s (1959, 1963) successors, Thomas Kuhn (1996), who questioned the progressive
nature of scientific knowledge and its fundamental independence from its objects of
study. Kuhn argued that scientific knowledge is cumulative only in a mundane or even
accidental sense. Significant developments are revolutionary, he demonstrated, not
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evolutionary, and they reflect dramatic breaks that are incompatible with previous
research programs.
Kuhn’s (1996) analysis also presents a challenge for another central tenet of
science, that the natural phenomena it investigates are pre-existing, having a life apart
from scientists’ interest in them. Kuhn’s tack was to draw on a concept rooted in
structural linguistics, paradigm. Kuhn employed the term to reveal the arbitrary,
contextual, and consensual meaning that objects have for an interested community
pursuing a common goal. He then characterized these paradigms as having the tendency
to undergo a seismic “shift,” in which one consensual frame of reference replaces
another, and an area of scientific inquiry undergoes a sudden—rather than progressive or
cumulative—change.
Learning Science Paradigms: Shift Happens
A number of aspects of Popper’s and Kuhn’s understandings of scientific
paradigms can be readily illustrated by a cursory examination of two prominent attempts
to understand teaching and learning in scientific terms: behaviourism and cognitive
science. The first of these, behaviourism, had as its explicit goal to make psychology—a
discipline at the time associated with non-experimental introspective methods—into a
“real” science. It proposed to do so by emphasizing empirically and experimentally
verifiable evidence at the expense of any theories or impressions about the mind or
mental states. In this sense, behaviourism can be seen as taking Popper’s insistence on
falsifiability very literally and seriously: The only valid knowledge available to
psychological researchers, as the name behaviourism itself suggests, comes from
behaviour, and from the stimuli (positive or negative reinforcement). Claims about the
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role of the mind, about thought, or about free will cannot not be falsified, and are
therefore outside of the bounds of a scientific psychology. As a consequence, research
questions, problems and possible answers that this paradigm led researchers to were
about ways of most effectively shaping behaviour through conditioning and
reinforcement. Educational research itself was understood in terms of the observation of
persistent changes in behavior through conditioning. Teaching was conceptualized as the
provision of rewards for the successive approximation of target behaviors, and learning
came to be understood as an enduring behavioural change achieved through these
processes. The influence of this powerful paradigm lives on in our understandings of the
importance of “positive reinforcement” or “stimulating environments” in fostering
learning.
The ability of this paradigm to satisfy consensual pursuit of scientific psychology
met its limit quite abruptly in its attempt to account for language learning. In the late
1950’s linguist Noam Chomsky argued effectively that the ability of children to learn the
vocabularies and grammar of their native language without formal instruction could not
be explained through the laborious repetition of stimulus and response. As an alternative,
Chomsky posited the existence of inherent, generative mechanisms of the mind --a
conjecture expanded to become the founding hypothesis of the shifting psychological
paradigm (e.g. see Bechtel, Abrahamsen and Graham, 1998). This paradigm,
cognitivism, posits that computational structures, mechanisms and processes in the mind
can be known. They can be the subject of scientific investigation by being modeled
through the use of computer hardware and software. Cognitivism, in other words,
proceeds from “the conjecture that every aspect of learning or any other feature of
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intelligence can in principle be so precisely described that a machine can be made to
simulate it" (McCarthy, et al 1955). This powerful hypothesis served as the basis for new
and interdisciplinary orientations in linguistics (structural), computer science (Artificial
Intelligence), philosophy (of mind), and explicitly “cognitive” orientations in
neuroscience and education. Together, these were known as the “cognitive sciences” -constituting what has been called a “cognitive paradigm” (e.g. De Mey, 1992). This
paradigm, in clear ascendancy in educational research since the 1970’s, has its own way
of configuring educational research and practice. Learning is seen as changes in the way
information is processed, represented and structured in the mind, and teaching becomes
the effective support of these computational mental operations. Research, in turn, is
centred around the discovery of mechanisms and processes such as those identified by
Chomsky, and is also focused on computational modeling of such constructs as a kind of
“existence proof” for these ideas (Gardner, 1987, 40). Cognitive science has produced
ideas such as long- and short-term memory, or the educational value of advanced
organizers which remain with us today.
Recently, however, the cognitivist paradigm has itself shown signs of “shift:”
“post-cognitivist” and “anti-cognitivist” schools of research and clinical psychology (e.g.
Potter, 2000) have emerged over the last two decades. Within education itself,
constructivist and situated variations on this paradigm have gained popularity—variations
which are based on sociological, ethnographic and anthropological assumptions that
differ radically from the a-social, mechanistic orientation of cognitivism in its early
stages (e.g. Greeno, 1998; Salomon, 1998; Pea, 1994). It is in this context that the
“learning sciences” --as an eclectic amalgam of schools and approaches-- appear to be
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gradually taking the place of the more monolithic scientific paradigm provided by
cognitivism.
Critiques of Science by Sociologists
Although the recent emergence of the learning sciences can certainly be
understood as the latest in a procession of paradigms to gain prominence in educational
research, it can also be understood in slightly different terms. These terms are also
offered by the philosophy and sociology of science; specifically by more recent
developments in the analysis of science as an everyday affair engaged in by people
working in specific socio-historical contexts Whereas philosophers and historians of
science such as Popper (1959, 1963), and Feyerabend (1975) and others (eg. Quine,
1951; Lakatos, 1970, 1976) dealt with Science as an abstract concept, Kuhn’s work
precipitated an analysis of science specifically as sets of quotidian, situated and valueladen practices and contexts. This move was advanced by sociologists for whom the
contingent nature of scientific procedures and the interpretive character of scientific facts
were obvious.
Latour (1979, 1987, 1988, 1992, 1999, 2005) for instance, employed ethnographic
methods to study scientists at work. During prolonged engagements in the laboratories of
primatologists and neuroendocrinologists, he witnessed an approach to inquiry that was
very different from the disinterested, logical, and methodical reproduction of nature still
dominant in orthodox understandings of the scientific endeavour. Like Feyerabend
(1975) (and Lakatos, 1970, 1976), he dismissed the notion that theories stand and fall on
the outcome of a single experiment. Rarely does an experiment provide anything more
DRAFT: LEARNING SCIENCE: THE VERY IDEA 13
than inconclusive data, he observed. He was equally unconvinced that the acceptance or
rejection of scientific theories are decided entirely on evidence or reason.
Others, such as Knorr-Cetina (1981, 1999), Gilbert and Mulkay (1990), and
Woolgar (1988) supported Latour’s interpretations with similar types of studies. They
argued that the objects of scientific study are socially constructed (to use a term now
prominent in a number of educational and sociological research contexts) in the lab, and
have no existence outside of the instruments that measure them and the minds that
interpret them.
By the latter half of the 20th century, any idealized notions of science and the
scientific method as unquestionably privileged or impartial were in a troubled state. A
picture of the natural sciences as not always, not only, or simply not progressive,
objective, and explicitly logical prompted reflection among those interested in
understanding human action and learning. This group, as Brown (1992) describes so well,
were making major epistemological and pragmatic sacrifices in order to adhere to
scientific principles, but these principles seemed more and more illusory.
Lageman (2000) offers one possible rationale for this debilitative commitment.
She demonstrates that the commitment to validity, objectivity and other trappings of
natural science is a longstanding attempt by educational researchers to gain respectability
and legitimacy. Flyvbjerg (2003), unfortunately, is pessimistic about this ever
materializing, and he grounds his pessimism in a recounting of the recent science wars.
He reminds readers of physicist Alan Sokal’s successful attempt to have a bogus article
peer-reviewed and published in a leading social science journal. Of the many issues
raised by the hoax, Flyvberg focuses on how it revealed the disdainful and dismissive
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attitudes which many ‘hard’ scientists have for their ‘soft’ kin. He quotes from a Harvard
biologist who cautions, “In pretending to a kind of knowledge that it cannot achieve,
social science can only engender the scorn of natural scientists” (Lewonton, 1995, p. 28,
cited by Flyvberg, 2003, p. 1).
A further explanation for educational researchers’ detrimental commitment to the
scientific method is found in a tangible correlate of esteem and respect: funding. In 2003,
Burkhardt and Schoenfeld compared research funding in fields such as science,
engineering, and electronics—5%-15% of their budgets—with funding for educational
research—less than 0.01% of their budgets. Commenting on these figures, they note
wryly that this is considerably less than Pfifer spends on R&D in its pet food division.
Sroufe (1997) makes the connection between the perceived legitimacy of educational
research and funding by quoting from a section of the 1997 Presidents’ Committee of
Advisors on Science and Technology: “Education research is applied and anecdotal and
permits gleaning to support one’s perspective” (President’s Committee of Advisors on
Science and Technology [PCAST], 1997, p. 102; cited by Sroufe, 1997, p. 26).
Therefore, as Sroufe reports incredulously, PCAST suggested that an outside committee,
composed of unemployed graduates from science, math, and engineering programs, be
enlisted to conduct educational research.
Nonetheless, it is difficult to accept the argument that educational research needs
to be more scientific if it is to receive more funding in our current epoch. To do so, we
have to ignore the fact the a growing number of American’s do not believe in Darwin’s
theory of evolution through natural selection (Orr, 2005), and that the Bush
Administration, currently the ultimate arbiter of this funding, is regularly characterized as
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“distorting science,” “stacking the deck against science” (Philipkoski, 2004a, 2004b),
“misusing science,” “suppress scientific analyses” (Union of Concerned Scientists, 2004,
2005) and so on.
A final rationale for the devotion to the scientific method is the hope nestled
within science’s superordinate term positivism, which Toulmin (1990) characterizes as
the quest for certainty. That hope, expressed by Kant (1781) in the introduction to our
article, and later by Compte (1974, cited in Frankel & Wallen, 2000, p. 431), found its
way into education in Royce’s (1891) contribution to the inaugural edition of the journal
Educational Review. His article was titled Is There a Science of Education, and Lageman
(2002) suggests that the answer he offered was something like, “no, but there should be”.
Exactly 100 years later, the JLS began in the same manner. In its inaugural issue, the
editor presents a list of problems with education, some dubious solutions, and writes:
We simply do not have sufficiently concise theories of learning to be able
to tailor curricula to the natural way that kids learn. Our best teachers
follow their intuitions and provide wonderful opportunities for our kids,
but . . . something more concrete than intuition is necessary. . . A major
goal of the journal is to foster new ways of thinking about learning and
teaching that will allow cognitive science disciplines to have an impact on
the practice of education. We are interested in publishing articles that have
the potential to make real world contributions (Kolodner, 1991, p. 4-6)
Fourteen years later, this goal of convincingly uniting a science of education with its
everyday application remains elusive. As an example, the upcoming International
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Conference of the Learning Sciences (ISLS), subtitled “Making a Difference,” informs
attendees:
While learning scientists can present rich accounts of learning in complex
contexts, convincing policy makers, teachers, and other researchers of the
theoretical and practical value of our work is not a straightforward
process. We must show impact at the local level while at the same time,
work to have claims of more global significance. In other words, we must
make clear that the learning sciences make a difference (¶ 3-4).
The promise of a natural science of education, whose findings and hypotheses would
enable “real world contributions” and “make a difference” in everyday practice
apparently remains irresistible. However, clear and consistent evidence for such a science
remains doubtful and unacknowledged, and the (hopefully transitory) antics of the Bush
administration are not the only example. Miller (1999) provides examples of conclusions
developed from lengthy, well-funded research programs that are consistently ignored or
contravened by practice. The head of the Office of Educational Research and
Improvement (OERI) enthusiastically described the series of What Work’s pamphlets
produced by OERI in the late 80s, which synthesized robust research findings and
presented them in an accessible way to practitioners. However, he lamented that, despite
distributing over half a million copies, few practitioners had put them to use, or worse
still, had even heard of them (Kaestle, 1993). Our experiences have been similar. A
couple years ago one of us successfully bid on a government contract to conduct an
evaluation of the use of Internet Protocol video conferencing in a few school districts.
Briefly, our findings were no more enthusiastic than those presented by Fabos and Young
DRAFT: LEARNING SCIENCE: THE VERY IDEA 17
(1999) in their substantive and highly critical review of similar applications, and we
cautioned the government about expanding the program. The day after we submitted our
interim report, the government announced with fanfare six million dollars of funding to
ensure that every school district in the province would have a video conferencing
program (Alberta Government, 2004). We doubt there are seasoned program evaluators
who have not had similar experiences. Experienced evaluators and researchers do not
share the naïve belief that information, collected in a disinterested manner, is used
objectively to make rational decisions. More often, we suggest, information is often
collected selectively to legitimize decisions that have already been made.
Among a broad range of stakeholders in the educational process, there is a
consensus: Educational researchers, for the most part, have not been successful at
emulating the processes, let alone outcomes, of natural scientists. Some, especially a
growing community called learning scientists, argue that we should strive harder. If we
do so, we will be able to develop robust theories and improve educational practice. We
will gain legitimacy, and with it, funding. In this article, we have tried to demonstrate this
argument is untenable, and that the same conditions that prompt the argument can be
interpreted in different ways. In the final sections, we describe some alternatives
including interpretive and phronetic (ie., socially responsible) educational research and
development.
What Might We Do Instead?
Many learning scientists’ descriptions of DBR may suggest a gradual if not
unequivocal turn toward interpretivist approaches to educational inquiry (eg., Brown,
1992; Barab and Squire, 2004). If this is also a turn away from post-positive
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commitments --which are in any case incommensurable with interpretivism-- then it may
also be seen as a most propitious shift of paradigms. As such, it may point to a possible
way of reconstituting educational research in a different way. This would be a way of
understanding the study and improvement of learning and learning conditions not as a
“science” that would deny the reality of its own social construction, but that would be
explicitly aware of the sociological and other conditions that inform it. This research
would leverage this awareness, moreover, to its own advantage. It would utilize ways of
understanding the constructed, debatable and interpretable nature of knowledge as a
means of investigating its own subject matter.
Such an approach would be associated with a number of methodologies and
schools of thought. However, they all share the same underlying assumptions: That
human phenomena, such as language, action and learning cannot be sufficiently
understood as the outcome of rule-bound processes that can be predicted and controlled
through research. These phenomena are instead understood as being in the realm of
meaning and interpretation, rather than being subject to any ostensibly factual or
scientific certainty. As such, human action, language and learning would be seen as
necessarily occurring within a context --culture, society, institutions, history, groups-from which it cannot be separated. The nature of this context, moreover, is such that it
can never be exhaustively articulated, modeled or even understood. As a further result of
this fact, research cannot be understood as occurring at an objective remove from its
object or its subject matter. The observation and manipulation of the researcher are
themselves interpretable acts occurring in the context of the interpretable dimensions of
culture, history, and other domains of human meaning and action. Examples of this kind
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of research are provided by hermeneutic and post-cognitive forms of psychology (e.g.
Martin and Sugarman, 2001; Potter, 2000), phenomenology and ethnomethodology (e.g.
Dourish, 2001), and critical, historical, and genealogical methods (e.g. Holzkamp, 1992).
A Different Take on DBR: Phronetic research
Despite their mutually exclusive character, the process of relinquishing the postpositivistic elements of DBR while maintaining its interpretivist ones is not easy.
Together, they can be seen as providing a sympathetic balance that would allow
researchers to understand local practices while contributing to generalizable learning
theories. This harmonious intersection of goals was presented persuasively in Stokes’
(1997) book Pasteur’s Quadrant. The eponymous quadrant refers to one cell of a two-bytwo matrix in which the goals of pure research are fused with the goals of applied
research. The matrix has been so influential in the learning sciences that it requires little
explanation (eg., National Academy Press, 2000; Reeves, 2000; Schoenfeld, 1999).
However, this construction is deficient in an important way.
The division of knowledge-seeking goals into two types originates with Aristotle
(384/322 BC). He proposed that some of our efforts are directed toward episteme, pure
research, or knowledge for knowledge’s sake. Other efforts, Aristotle suggested, are
directed toward techne, applied research, the type associated with a Thomas Edison,
rather than an Einstein or Bohr. However, Stokes’ and other differentiations between pure
and applied science disregard a critical third category of knowledge proposed by
Aristotle: phronesis. Aristotle defined this type of knowledge as “ a true state, reasoned,
and capable of action with regard to things that are good or bad for man” (cited in
Flyvberg, 2003, p. 2). The goal of a phronesis, as Flyvberg explains “is to help restore
DRAFT: LEARNING SCIENCE: THE VERY IDEA 20
social science to its classical position as a practical, intellectual activity aimed at
clarifying the problems, risks, and possibilities we face as humans and societies, and at
contributing to social and political praxis” (p. 4).
These two alternatives—a wholly interpretivist and a phronetic approach to
research—are already incipient, we think, in minor shifts from dominant orientations in
learning science. Such approaches may certainly appear “unscientific” when compared to
some of the methodological and other strictures that have been associated with the natural
sciences and their methodology. However, this may simply be due to a very narrow
understanding of science, not inherent to the pursuit itself, but reinforced by the way the
term is used in many English-language contexts. In other linguistic contexts, the terms
“science” and “scientific” are used to designate the broadly interpretive critical,
hermeneutic and discursive methods enumerated above --and other possible approaches
as well. These are often referred to as the Human Sciences. Such a designation would be
appropriate to the kind of self-aware, consciously interpretive inquiry that is informed by
20th century theories of science --rather than one that harks back to the time of Kant and
Compte.
DRAFT: LEARNING SCIENCE: THE VERY IDEA 21
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