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Many innovative approaches to education such as problem-based learning (PBL) and inquiry learning (IL) situate learning in problem-solving or investigations of complex phenomena. Kirschner, Sweller, and Clark (2006)45. Kirschner , P. A. , Sweller , J. and Clark , R. E. 2006. Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discovery, problem-based, experiential, and inquiry-based teaching. Educational Psychologist., 41: 75–86. [Taylor & Francis Online], [Web of Science ®]View all references grouped these approaches together with unguided discovery learning. However, the problem with their line of argument is that IL and PBL approaches are highly scaffolded. In this article, we first demonstrate that Kirschner et al. have mistakenly conflated PBL and IL with discovery learning. We then present evidence demonstrating that PBL and IL are powerful and effective models of learning. Far from being contrary to many of the principles of guided learning that Kirschner et al. discussed, both PBL and IL employ scaffolding extensively thereby reducing the cognitive load and allowing students to learn in complex domains. Moreover, these approaches to learning address important goals of education that include content knowledge, epistemic practices, and soft skills such as collaboration and self-directed learning.
2007, Lawrence Erlbaum Associates, Inc.
Scaffolding and Achievement in Problem-Based and Inquiry Learning:
A Response to Kirschner, Sweller, and Clark (2006)
Cindy E. Hmelo-Silver, Ravit Golan Duncan, and Clark A. Chinn
Department of Educational Psychology
Rutgers University
Many innovative approaches to education such as problem-based learning (PBL) and inquiry
learning (IL) situate learning in problem-solving or investigations of complex phenomena.
Kirschner, Sweller, and Clark (2006) grouped these approaches together with unguided discov-
ery learning. However, the problem with their line of argument is that IL and PBL approaches
are highly scaffolded. In this article, we first demonstrate that Kirschner et al. have mistakenly
conflated PBL and IL with discovery learning. We then present evidence demonstrating that
PBL and IL are powerful and effective models of learning. Far from being contrary to many
of the principles of guided learning that Kirschner et al. discussed, both PBL and IL employ
scaffolding extensively thereby reducing the cognitive load and allowing students to learn in
complex domains. Moreover, these approaches to learning address important goals of educa-
tion that include content knowledge, epistemic practices, and soft skills such as collaboration
and self-directed learning.
All learning involves knowledge construction in one form or
another; it is therefore a constructivist process. The question
of what sorts of instructional practices are likely to promote
such knowledge construction, or learning, is at the core of the
argument presented by Kirschner, Sweller, and Clark (2006).
The authors loosely define minimally guided instruction as
a learning context in which “learners, rather than being pre-
sented with essential information, must discover or construct
essential information for themselves” (p. 1). They conversely
define direct guidance instruction as “providing information
that fully explains the concepts and procedures that students
are required to learn. In their argument, Kirschner et al.
contrast minimally guided instructional approaches with ap-
proaches that provide direct instructional guidance and assert
that minimally guided instructional approaches are ineffec-
tive and inefficient.
Correspondence should be addressed to Cindy E. Hmelo-Silver, Depart-
ment of Educational Psychology, Rutgers University, 10 Seminary Place,
New Brunswick, NJ 08901-1183. E-mail:
There are two major flaws with Kirschner et al’s argument.
The first is a pedagogical one. Kirschner and colleagues have
indiscriminately lumped together several distinct pedagog-
ical approaches—constructivist, discovery, problem-based,
experiential, and inquiry-based—under the category of min-
imally guided instruction. We argue here that at least some
of these approaches, in particular, problem-based learning
(PBL) and inquiry learning (IL), are not minimally guided
instructional approaches but rather provide extensive scaf-
folding and guidance to facilitate student learning.
The second is a flaw in their evidentiary base. The claim
by Kirschner et al. that approaches such as PBL and IL
are ineffective is contrary to empirical evidence that indeed
does support the efficacy of PBL and IL as instructional
approaches. This evidence suggests that these approaches
can foster deep and meaningful learning as well as significant
gains in student achievement on standardized tests.
In our article we will discuss how PBL and IL provide
instructional guidance and provide evidence that supports
the efficacy of these pedagogical approaches. We will exam-
ine the claims of Kirschner et al. specifically in the context
of PBL and IL, as these approaches clearly provide scaf-
folding for student learning. We begin with a brief discus-
sion of the qualities of some of the pedagogical approaches
Kirschner et al. have included under their “minimally guided”
Constructivist theories of learning stress the importance of
learners being engaged in constructing their own knowledge
(Mayer, 2004; Palincsar, 1998). An assumption that leads to
the minimally guided discovery approach is that the learn-
ers need to explore phenomena and/or problems without any
guidance. This assumption has been repeatedly demonstrated
to be flawed (Mayer, 2004). We agree with Kirschner et al.
(2006) that there is little evidence to suggest that unguided
and experientially-based approaches foster learning. How-
ever, IL and PBL are not discovery approaches and are not
instances of minimally guided instruction, contrary to the
claims of Kirschner et al. Rather, PBL and IL provide con-
siderable guidance to students.
Before we discuss the ways in which PBL and IL are not
minimally guided, we begin by clarifying what is meant by
PBL and IL. In PBL, students learn content, strategies, and
self-directed learning skills through collaboratively solving
problems, reflecting on their experiences, and engaging in
self-directed inquiry. In IL, students learn content as well
as discipline-specific reasoning skills and practices (often in
scientific disciplines) by collaboratively engaging in investi-
gations. Both PBL and IL are organized around relevant, au-
thentic problems or questions. Both place heavy emphasis on
collaborative learning and activity. In both, students are cog-
nitively engaged in sense making, developing evidence-based
explanations, and communicating their ideas. The teacher
plays a key role in facilitating the learning process and may
provide content knowledge on a just-in-time basis.
The major distinction that we perceive between PBL and
IL is their origins. PBL has its origins in medical education
and is based on research on medical expertise that empha-
sized a hypothetical-deductive reasoning process (Barrows
& Tamblyn, 1980). PBL often uses text-based resources for
both the problem data and self-directed learning. IL has its
origins in the practices of scientific inquiry and places a heavy
emphasis on posing questions, gathering and analyzing data,
and constructing evidence-based arguments (Kuhn, Black,
Keselman, & Kaplan, 2000; Krajcik & Blumenfeld, 2006).
As we have examined the broad variety of instantiations of
PBL and IL, we have not uncovered any dimensions that con-
sistently distinguish between PBL and IL. Indeed, we think
there are no clear-cut distinguishing features. PBL frequently
engages students in explorations and analyses of data, such
as one would expect IL environments to do, and IL frequently
poses problems and asks students to consult various resources
to solve them as PBL environments do. For example, prob-
lems in medical PBL present students with rich sets of pa-
tient data to analyze (Barrows, 2000; Hmelo-Silver, 2004).
Similarly, IL environments such as the Web Integrated Sci-
ence Environment (WISE) provide students with scientific
problems and the research materials that students examine
in order to reach a conclusion about the problem (Linn &
Slotta, 2006). Students may read a variety of resources in ad-
dition to reading about data and conducting their own studies.
Thus, in practice PBL and IL environments are often indis-
tinguishable, despite divergent origins and so we treat them
as synonymous in this article.
As we have noted, PBL and IL environments are not mini-
mally guided because of many forms of scaffolding provided.
Moreover, these approaches may include direct instruction
as one of the strategies they employ (Krajcik, Czerniak, &
Berger, 1999; Schmidt, 1983; Schwartz & Bransford, 1998).
However, in these contexts, direct instruction may be pro-
vided on a just-in-time basis and generally once students ex-
perience a need to know the information presented (Edelson,
2001). Thus a mini-lecture or benchmark lesson presenting
key information to students is used when students understand
the necessity of that information and its relevance to their
problem-solving and investigational practices. Such just-in-
time direct instruction promotes knowledge construction in a
way that makes knowledge available for future use in relevant
contexts (Edelson, 2001).
There is an extensive body of research on scaffold-
ing learning in inquiry- and problem based environments
(Collins, Brown, & Newman, 1989; Davis & Linn, 2000;
Golan, Kyza, Reiser, & Edelson, 2002; Guzdial, 1994; Jack-
son, Stratford, Krajcik, & Soloway, 1994; Reiser, 2004; Toth,
Suthers, & Lesgold, 2002), and researchers have developed
theory-driven and empirically based design guidelines for in-
corporating effective scaffolding strategies to support learn-
ing (Hmelo & Guzdial, 1996; Hmelo-Silver, 2006; Quintana
et al., 2004; Reiser et al., 2001).
Scaffolded inquiry and problem-based environments
present learners with opportunities to engage in complex
tasks that would otherwise be beyond their current abilities.
Scaffolding makes the learning more tractable for students
by changing complex and difficult tasks in ways that make
these tasks accessible, manageable, and within student’s zone
of proximal development (Rogoff, 1990; Vygotsky, 1978).
Quintana et al. (2004) conceived of scaffolding as a key ele-
ment of cognitive apprenticeship, whereby students become
increasingly accomplished problem-solvers given structure
and guidance from mentors who scaffold students through
coaching, task structuring, and hints, without explicitly giv-
ing students the final answers. An important feature of scaf-
folding is that it supports students’ learning of both how to
do the task as well as why the task should be done that way
(Hmelo-Silver, 2006).
Scaffolding not only guides learners through the complex-
ities of the task, it may also problematize important aspects
of students’ work in order to force them to engage with key
disciplinary frameworks and strategies (Reiser, 2004). Such
scaffolds act by “rocking the boat” and stopping mindless
progress through the task, thus redirecting students’ atten-
tion to important learning goals such as examining counter
claims, articulating explanations and reflecting on progress.
Scaffolding is often distributed in the learning environ-
ment, across the curriculum materials or educational soft-
ware, the teachers or facilitators, and the learners themselves
(Puntambekar & Kolodner, 2005). Teachers play a signifi-
cant role in scaffolding mindful and productive engagement
with the task, tools, and peers. They guide students in the
learning process, pushing them to think deeply, and model
the kinds of questions that students need to be asking them-
selves, thus forming a cognitive apprenticeship (Collins et
al., 1989; Hmelo-Silver & Barrows, 2006). In the next sec-
tions, we consider how scaffolding is implemented in PBL
and IL environments.
The Use of Scaffolding in PBL and IL
PBL and IL situate learning in complex tasks. Such task
require scaffolding to help students engage in sense mak-
ing, managing their investigations and problem-solving pro-
cesses, and encouraging students to articulate their think-
ing and reflect on their learning (Quintana et al., 2004).
These aspects of IL and PBL tasks are challenging for stu-
dents in many ways, and different researchers aiming to help
learners overcome these conceptual and practical hurdles
have used several scaffolding strategies (e.g., Chinn, 2006;
Guzdial, 1994; Jackson et al., 1996; Linn, Bell, & Davis,
2004; Reiser et al., 2001). Due to space considerations, we
will only discuss a few of these strategies that highlight the
ways in which scaffolding can reduce cognitive load, pro-
vide expert guidance, and help students acquire disciplinary
ways of thinking and acting. All these strategies can support
sense making, process management, and articulation and re-
flection. The examples we present provide a stark contrast
to the Kirschner and colleagues’ argument that inquiry and
PBL environments provide minimal guidance and therefore
increase cognitive load.
Scaffolding That Makes Disciplinary Thinking
and Strategies Explicit
In PBL and IL environments facilitators and teachers make
key aspects of expertise visible through questions that scaf-
fold student learning by modeling, coaching, and eventually
fading some of their support. Student learning occurs as
students collaboratively engage in constructive processing.
For example, in studying an expert PBL teacher in the con-
text of medical education, Hmelo-Silver and Barrows (2006)
showed that the teacher frequently pushed students to ex-
plain their thinking to help them build a causal explanation
or identify the limits of their knowledge. This helps support
students in sense making and in articulating their ideas.
IL and PBL environments also make disciplinary strate-
gies explicit in students’ interactions with the tasks and tools
as well as the artifacts they create (Quintana et al., 2004). For
example, in the scaffolded software tool for analyzing animal
behavior, Animal Landlord, students create a chronological
“storyboard” of the behavioral components they identify in
a short video clip of animal behavior. In creating this sto-
ryboard students are expected to identify behavioral com-
ponents, label them, and annotate their observations and in-
terpretations about these components. This artifact makes
salient the disciplinary strategies of analyzing animal behav-
ior which include decomposing complex behavior into its
constituents, categorizing the constituents, and interpreting
their significance (Golan et al., 2001; Smith & Reiser, 1998).
In addition to providing an investigation model for student
to emulate, this also supports students’ sense making and
Many other environments provide students with: (a)
prompts to use particular reasoning strategies (e.g., Derry,
Hmelo-Silver, Nagarajan, Chernobilsky, & Beitzel, 2006;
White & Frederiksen, 1998); (b) structures for students to
follow or fill in, such as filling in argument diagrams to learn
to distinguish between claims and reasons (Bell, 2002; Toth
et al., 2002) or templates for domain-specific explanations
(Duncan, 2006; Sandoval & Reiser, 2004); and (c) models
of expert performance for students to emulate (Chinn et al.,
2000; Loh et al., 2001). Chinn and Hung (2007) demon-
strated the effectiveness of expert models in promoting sev-
enth graders’ scientific reasoning. In a curriculum centered
on argumentation about the interpretation of scientific stud-
ies, students in some classrooms were presented with models
of children discussing how to evaluate the methodology of
studies with scientists. The participants in these short dis-
cussions engaged in argumentative give and take about the
strengths and weaknesses of studies. Students who received
these models of effective argumentation demonstrated more
individual progress than students who engaged in the same
argumentation-based learning activities without the models.
The models scaffolded students’ reasoning by showing dia-
logic instances of expert reasoning.
Scaffolds That Embed Expert Guidance
In many IL and PBL environments, expert information and
guidance is sometimes offered directly to the learner. For
example in WISE, students are provided with expert’s hints
and explanations of the rationale underlying the processes
students engage in (Davis, 2003). In some cases, such as goal-
based scenarios (Schank & Cleary, 1995), expert information
is offered directly to the learner through “conversations” with
experts in the form of embedded video clips.
Schwartz and Bransford (1998) showed that providing ex-
planations when needed can be a very effective form of scaf-
folding (see also Minstrell & Stimpson, 1996). Schwartz and
Bransford presented some students with a lecture on memory
after they had tried to explain the pattern of results in data
from real memory experiments. Other students received the
lecture without having engaged in the inquiry activity. The
students who received the lecture after trying to explain the
data learned much more from the lecture. In the context of
students trying to explain data, the lecture provided scaffold-
ing that helped students make sense of the data, and hence
was more meaningful than the same lecture presented not as
scaffolding for inquiry but as direct instruction.
In PBL in medical education, the facilitator models a
hypothetical-deductive reasoning process (Hmelo-Silver &
Barrows, 2006). In STELLAR PBL, an adaptation of PBL
to teacher education, preservice teachers use video cases of
expert teachers as models for adapting instructional plans
(Derry et al., 2006). In addition, the video cases are linked to
appropriate concepts in a learning sciences hypermedia. The
indexing of the video to the hypermedia is another form of
expert guidance.
Scaffolds That Structure Complex Tasks or
Reduce Cognitive Load
A great deal of structure is provided through scaffolds in
the IL and PBL environments. In PBL, structure is provided
through whiteboards that communicate a problem-solving
process as well through the human facilitator (Barrows, 2000;
Hmelo-Silver, 2004). For example, the whiteboard provides
columns for the group to keep track of the facts of the case,
their evolving hypotheses,thelearning issues, which are con-
cepts that the group needs to learn more about in order to
solve the problem, and an action plan, which helps remind the
group of what they need to do. Maintaining the whiteboard
is a part of the PBL process and becomes a routine that helps
support intellectual discourse. Such routines provide pre-
dictable ways to move through activity structures, set social
norms for participation and use of resources, and foster in-
teraction (Leinhardt & Steele, 2005). Because these routines
become automated, the PBL routine itself reduces cognitive
demands. Although there is initial adaptation required, stu-
dents quickly learn that they need to take on particular roles
and to work together to identify the important facts of the
problem, generate potential ideas about the problems, and
what they need to learn about in order to solve the problem.
Scaffolding can also guide instruction and decrease cog-
nitive load by structuring a task in ways that allow the learner
to focus on aspects of the task that are relevant to the learning
goals (Hmelo-Silver, 2006; Salomon, Perkins, & Globerson,
1991). For example, scaffolding can reduce cognitive load
by automating the generation of data representations, labor
intensive calculations, or storing information. By structuring
the tasks and the available functionality (e.g., in computer-
based environments), scaffolding can restrict the options that
are available to the learner at any point in time to make
the task accessible and manageable (Quintana et al., 2004).
For example in Model-It, a software environment that allows
students to build object-based models of natural phenomena
(such as the effects of pollutants on a stream ecosystem),
there are three functional modes: plan, build, and test (Jack-
son et al., 1996). The software restricts the options avail-
able to students such that students may only proceed to the
build stage after they have planned their models, and they
may not test it until they have identified some of the impor-
tant objects and relationships in the system. Model-It further
scaffolds students by allowing them to qualitatively express
complex mathematical relationships as the software converts
their verbally stated relationships into mathematical formulas
used for running the model, thereby reducing cognitive load
and situating the task within the learner’s zone of proximal
In summary, many of the types of scaffolding described
provide very strong forms of guidance that seem to us to be
indistinguishable from some of the forms of guidance rec-
ommended by Cognitive Load theorists. We fail to see that
the instruction recommended by Kirschner et al. differs so
clearly from instructional practices in IL methods. Kirschner
et al. touted worked examples and process worksheets as ef-
fective methods of guided learning. But PBL and IL methods
employ modeling that seems very similar to worked examples
as well as scaffolds to guide inquiry that strongly resemble
process worksheets (e.g., Kirschner & Erkens, 2006; White
& Frederiksen, 1998). We think a close analysis of IL and
PBL methods indicates that they are indeed strongly guided
form of instruction. Studies showing that unguided or min-
imally guided instruction is inferior to direct instruction are
simply irrelevant to most approaches implementing PBL or
It is important to consider learning outcomes as multifaceted.
The goals of learning should include not only conceptual and
procedural knowledge but also the flexible thinking skills and
the epistemic practices of the domain that prepare students
to be lifelong learners and adaptive experts (Bereiter & Scar-
damalia, 2006; Bransford, Brown, & Cocking, 2000; San-
doval & Reiser, 2004). But even on similar outcomes, PBL
and IL often prove to be superior in studies of classroom-
based instruction.
Evidence that PBL is Effective
Although Kirschner et al. (2006) report on several studies and
meta-analyses of PBL, they overlooked other reviews that
were more favorable to PBL. At around the same time as the
Albanese and Mitchell (1993) and Berkson (1993) reviews
that Kirschner et al. (2006) cited, there was a third meta-
analysis conducted by Vernon and Blake (1993). This analy-
sis found that medical students in PBL curricula performed
slightly worse on tests of basic science knowledge but per-
formed better on tests of clinical knowledge than traditional
medical students. In a more recent meta-analysis of the effects
of PBL, Dochy, Segers, Van den Bossche, and Gijbels (2003)
found there was no effect of PBL on declarative knowledge
tests, but studies that compared PBL students with those in
traditional curricula on measures of knowledge application
showed a moderate effect size favoring PBL students.
Kirschner et al. cited the results of Patel, Groen, and Nor-
man’s (1993) research. In this study, students from very dif-
ferent universities with different entering characteristics were
compared (and indeed there is a self-selection bias in most
studies of PBL). They were compared at a single time on
a single task, but the PBL students did indeed transfer the
hypothesis-driven reasoning strategy they were taught to new
problems whereas students in a traditional curriculum did not
use this reasoning strategy. The PBL students were also more
likely to make errors. But a close examination of these results
reveals that although the PBL students made more errors,
they also created more elaborated explanations compared to
the sparse explanations of students in the traditional curricu-
lum. Patel et al. concluded (and Kirschner et al. concurred)
that PBL impedes the development of expert data-driven
reasoning strategies. However, other research suggests that
when faced with unfamiliar problems, experts go back to ba-
sic principles and effectively use hypothesis-driven reasoning
rather than the data-driven reasoning used in familiar prob-
lems (Norman, Trott, Brooks, & Smith, 1994). In an experi-
mental study comparing medical students trained to use either
data-driven or hypothesis-driven
reasoning while learning
about electrocardiograms, the hypothesis-driven reasoning
strategy led to superior learning (Norman, Brooks, Colle, &
Hatala, 2000).
The accuracy effect found in the Patel et al. study has not
been a robust effect, as the Dochy et al.s (2003) study sug-
gests. A more recent longitudinal quasi-experimental study
of first year medical students found that PBL students gen-
erated more accurate and coherent problem solutions than
traditional medical students (Hmelo, 1998).
Although research at other grade levels and disciplines
outside medicine is rare, there is other work that supports the
positive effects of PBL. Derry et al. (2006) compared preser-
vice teachers in the technology-supported STELLAR PBL
course in educational psychology with students in other sec-
tions of educational psychology on a video analysis transfer
task. Over three semesters of the class, there were consistently
positive effects favoring the students in the PBL class on tar-
geted outcomes. In a carefully controlled crossover study of
MBA students, Capon and Kuhn (2004) randomly assigned
students to either PBL-first, lecture-second or lecture-first,
PBL-second condition for two different concepts. On mea-
sures of declarative knowledge, there were no differences
between the conditions; however, the students constructed
more integrative explanatory essays for the concepts that
they had learned using a PBL approach.
Data-driven and hypothesis-driven reasoning are also referred to as
forward and backward reasoning, respectively.
PBL has been successfully applied at secondary educa-
tion. In a study comparing traditional and problem-based in-
struction in high school economics, Mergendoller, Maxwell,
and Bellisimo (2006) found that across multiple teachers and
schools, students in the PBL course gained more knowledge
than the students in a traditional course.
Another variant of PBL is anchored instruction, exempli-
fied by the Adventures of Jasper Woodbury used in middle
school mathematics (Cognition and Technology Group at
Vanderbilt [CTGV], 1992). In a large-scale implementation
study comparing students using the Jasper PBL instruction
with matched comparison students across 16 school districts
in 11states, PBL had positive outcomes on standardized tests.
On researcher-developed measures, the results showed no
differences between PBL and traditional math instruction on
single-step word problems but significant positive effects on
solving multistep word problems and on other aspects of
problem solving such as planning and problem comprehen-
sion for the PBL group.
The results reported here include fairly traditional mea-
sures of knowledge and knowledge application. It is impor-
tant to note that the goals of PBL go beyond these kinds of
measures. There is evidence that PBL supports the devel-
opment of reasoning skills (e.g., Hmelo, 1998), problem-
solving skills (e.g., CTGV, 1992; Gallagher, Stepien, &
Rosenthal, 1992) and self-directed learning skills (e.g.,
Hmelo & Lin, 2000). PBL methods are also effective
at preparing students from future learning. For instance,
Schwartz and Martin (2004) found that ninth graders who
initially learned through exploratory problem solving em-
ploying statistical principles learned more from a subsequent
lecture than students who had initially learned from a worked
example that the instructor explained in class.
Evidence for Effectiveness of IL Approaches
Kirschner and colleagues asserted that there is a lack of re-
search using controlled experimentation which shows the
relative effectiveness of IL methods. They presented evi-
dence that lower-performing students assigned to minimally
guided instruction showed a decrement in performance fol-
lowing such interventions. It is true that controlled experi-
ments of inquiry-, project-, and problem-based environments
are scarce. However, a few such studies do exist, and those
show significant and marked effect sizes and gains in favor
of inquiry-, problem-, and project-based environments (Geier
et al, in press; Hickey, Kindfeld, Horwitz, & Christie, 1999;
Hickey, Wolfe, & Kindfeld, 2000; Lynch, Kuipers, Pyke, &
Szesze, 2005).
is an inquiry-based environment that has
been extensively and systematically studied and has been
shown to engender learning gains that are significantly larger
than those attained in the comparison classrooms. The Gen-
Scope software is an open-ended inquiry environment de-
signed to support high school students’ investigations of
genetic phenomena (Horwitz, Neumann, & Schwartz, 1996).
Despite its exploratory and open-ended nature the GenScope
environment scaffolds student learning in several comple-
mentary ways: (a) complex simulations make the causal
mechanisms underlying genetic phenomena visible; (b) stu-
dents can easily manipulate representations of biological en-
tities at different biological organization levels; and (c) repre-
sentations of the phenomena at the multiple levels are linked
such that manipulations of one level have consequences (that
students can see) at subsequent levels. Several iterations of
the GenScope environment and related curriculum materials
have been implemented in secondary classrooms and a vali-
dated assessment system was developed to evaluate student
learning (Hickey et al., 2000).
Hickey et al. (1999) found that 381 students in 21 Gen-
Scope classrooms “showed significantly larger gains from
pretest to posttest than the 107 students in 6 comparison
classrooms. The largest gains were attained by students
from general science and general biology classrooms (com-
pared to honors and college prep classrooms). The mean
performance of these students increased from the more basic
forms of domain reasoning (cause-to-effects) to more sophis-
ticated domain reasoning (effect-to-cause). This is contrary
to Kirschner et al.s argument that IL disadvantages weaker
performing students.
Particularly impressive are the recent findings from a
study by Geier et al. (in press), which shows significantly
higher pass rates on high-stakes standardized exams for mid-
dle school students (Michigan Educational Assessment Pro-
gram) in science classes that use inquiry-based materials
compared to their peers in a large urban district in the Mid-
western United States. This study involved two cohorts com-
prising 1,803 students in the intervention condition (in 18
schools) and 17,562 students in comparison schools over
three years of enactment. The intervention included up to
three inquiry units, each unit lasting between six and nine
weeks of instruction and focused on concepts in physical sci-
ences and ecology/earth science. These project-based units
scaffolded learning using technology tools that expanded
the types of questions students could investigate, the data
they could collect and provided curricular support for model-
building and scientific reasoning (Amati, Singer, & Carrillo,
1999; Schneider & Krajcik, 2002; Singer et al., 2000).
Geier et al. (in press) demonstrated that the observed
gains occurred up to a year and a half after participation
in inquiry-based instruction, and the effect was cumulative
such that higher levels of participation (exposure to more
inquiry-based units) resulted in higher gains. The high scores
were attained in all three science content areas (earth, phys-
ical, and life) and both process skills (constructing and re-
flecting) assessed on the test. The effect sizes reported were
0.44 (14% improvement in total score) for students in the
first cohort and 0.37 (13% overall improvement) for students
in the larger second cohort. Thus, effect size was not ap-
preciably reduced with the scale-up. Even more compelling
is their finding that inquiry-based instruction was success-
ful in reducing the achievement gap experienced by urban
African-American boys. African-American boys in the in-
quiry classrooms “caught up” to and showed no statistically
significant difference from girls after exposure to at least one
inquiry-based unit.
Recent research by Lynch et al. (2005) also suggests that
inquiry-based learning environments foster better engage-
ment and mastery goal orientation among disadvantaged stu-
dents. In their comparison study of over 2,000 eighth grade
students (approximately 1,200 in the treatment and 1,000
in the comparison group) in ten middle schools in a large
and diverse Maryland school district, Lynch et al. (2005)
found overall higher gains for all diversity groupings (based
on ethnicity, socioeconomic status, gender, and ESOL sta-
tus) in the inquiry-based curriculum condition (a six to ten
week unit in chemistry). Thus, inquiry students of all groups
outperformed their comparison peers. The curriculum was
also more effective (than traditional instruction) in increas-
ing certain aspects of motivation and engagement, particu-
larly among historically disadvantaged student groups.
There are other studies that we interpret as supporting
the effectiveness of IL and other constructivist environments
(e.g., Guthrie et al., 2004; Langer, 2001; Wu & Tsai, 2005).
For example, Guthrie et al. found that an elementary school
reading program that combined strategy instruction with en-
hanced student choice, ample hands-on experiences, and
substantial student collaboration was more effective at ad-
vancing students’ reading than either traditional instruction
or a strategies-instruction-only treatment. We suspect that
Kirschner et al. might claim that this study supports their
position, because teachers who used the reading program
provided students with guided instruction on strategies. If
they did make this claim, they would only reinforce our cen-
tral point. What Kirschner et al. view as effective instruction
is often fully compatible with IL and other constructivist in-
struction. Most proponents of IL are in favor of structured
guidance in an environment that affords choice, hands-on
and minds-on experiences, and rich student collaborations.
In conclusion, there is growing evidence from large-scale
experimental and quasi-experimental studies demonstrating
that inquiry-based instruction results in significant learning
gains in comparison to traditional instruction and that disad-
vantaged students benefit most from inquiry-based instruc-
tional approaches. In many or most cases, exemplars of IL
instruction incorporate strong forms of guidance that propo-
nents of guided instruction will find attractive.
Goals for Learning and Instruction
Kirschner et al. (2006) claimed that the pursuit of inquiry-
based instructional methodologies has resulted in a shift of
instructional focus “away from teaching a discipline as a body
of knowledge towards an exclusive emphasis on learning a
discipline by experiencing the processes and procedures of
the discipline. This claim is problematic for at least two rea-
sons. First, the change in instructional focus is not merely
a result of inquiry methods of instruction but rather a much
broader call for reform in the goals of education. Recent re-
form documents (AAAS, 1993; NCTM, 2000; NRC, 1996),
in the United States as well as other countries (DFE/WO,
1995; Ministry of Education [Taiwan], 2001), have empha-
sized the importance of understanding not only content but
also disciplinary epistemologies and investigative strategies.
In the case of science education in particular, a large body of
research supports the importance of understanding the nature
of scientific research and the practices involved as a critical
part of scientific literacy (e.g., DeBoer, 1991; Driver, Leach,
Millar, & Scott, 1996; Duschl, 1990; Lederman, 1998; Mc-
Comas, Clough, & Almazroa, 1998). This suggests broad
goals for learning and instruction.
Second, current reforms and the inquiry approach are not
substituting content for practices; rather, they advocate that
content and practices are central learning goals. IL models
do in fact foster rich and robust content learning (Shyman-
sky, 1984; Wise & Okey, 1983; Von Secker & Lissitz, 1999).
While it is challenging to develop instruction that fosters the
learning of both the theoretical frameworks and investigative
practices of a discipline, examples of such environments do
exist (Linn, Bell, & Hsi, 1999; Reiser et al., 2001; White &
Frederiksen, 1998), and recent design frameworks offer guid-
ance for the development of such rich learning environments
(Edelson, 2001; Quintana et al., 2004).
The notion that learning the concepts and theories of a dis-
cipline is best situated in the context of the practices of that
discipline is supported by current theories of learning. Both
situated and cognitivist perspectives on cognition recognize
the influence of the learning context on the accessibility of
the knowledge for future use (Collins, Brown, & Newman,
1989; Greeno, 2006; Kolodner, 1993; Schank, 1982). Given
that students need to develop scientific understandings as in-
terconnected, meaningful, and useful, it is imperative that the
learning environments in which students acquire this knowl-
edge be similar to its likely context of use. These likely ap-
plication contexts are situations in which students will face
ill-defined problems such as evaluating scientific findings and
arguments presented in the media, determining the benefits
and risks of policies (or health procedures) through research
and investigation, and constructing logical and scientifically
sensible explanations of everyday phenomena. It follows then
that learning situations should provide students with oppor-
tunities to engage in the scientific practices of questioning,
investigation, and argumentation as well as learning content
in a relevant and motivating context.
Even in this limited review of research on PBL and IL, it
is clear that the claim that PBL and IL “does not work” is
not well supported, and, in fact, there is support for the al-
ternative. But we would argue that “Does it work?” is the
wrong question. The more important questions to ask are un-
der what circumstances do these guided inquiry approaches
work, what are the kinds of outcomes for which they are
effective, what kinds of valued practices do they promote,
and what kinds of support and scaffolding are needed for
different populations and learning goals. The questions that
we should be asking are complex as is the evidence that
might address them. It requires one to also consider the goals
of education—including not only learning content but also
learning “softer skills” (Bereiter & Scardamalia, 2006) such
as epistemic practices, self-directed learning, and collabora-
tion that are not measured on achievement tests but are impor-
tant for being lifelong learners and citizens in a knowledge
society. In many ways, we do not yet have adequate answers
to these questions concerning the conditions under which
various types of scaffolded learning environments are most
effective. While we are not arguing against various forms of
direct and more heavily guided instruction, of the sort that
Kirschner et al advocate, it is still unclear how to balance
IL and PBL (which are more constructivist and experiential)
with direct instructional guidance. We believe that more di-
rected guidance needs to build on student thinking. As a field
we need to develop deeper and more detailed understandings
of the interrelationships between the various instructional ap-
proaches and their impact on learning outcomes in different
We wish to conclude this article with the common wisdom
of Confucius on the nature of instruction and human learning:
“Tell me and I will forget; show me and I may remember;
involve me and I will understand. We argue that IL and PBL
approaches involve the learner, with appropriate scaffolding,
in the practices and conceptualizations of the discipline and in
this way promote the construction of knowledge we recognize
as learning.
Albanese, M. A., & Mitchell, S. (1993). Problem-based learning: A review of
literature on its outcomes and implementation issues. Academic Medicine,
68, 52–81.
Amati, K., Singer, J., & Carrillo, R. (1999, April). What affects the quality
of air in my community? Paper presented at the Annual Meeting of the
American Educational Research Association, Montreal, Canada.
American Association for the Advancement of Science (AAAS). (1993).
Benchmarks for science literacy. New York: Oxford University Press.
Barrows, H. S. (2000). Problem-based learning applied to medical educa-
tion. Springfield, IL: Southern Illinois University Press.
Barrows, H. S., & Tamblyn, R. (1980). Problem-based learning: An ap-
proach to medical education. New York: Springer.
Bell, P. (2002). Using argument representations to make thinking visible for
individuals and groups. In T. Koschmann, R. Hall, & N. Miyake (Eds.),
CSCL II: Carrying forward the conversation (pp. 449–455). Mahwah, NJ:
Lawrence Erlbaum Associates.
Bereiter, C., & Scardamalia, M. (2006). Education for the knowledge age:
Design-centered models of teaching and instruction. In P. A. Alexander
& P. H. Winne (Eds.), Handbook of educational psychology (2nd ed., pp.
695–713). Mahwah, NJ: Erlbaum.
Berkson, L. (1993). Problem-based learning: Have the expectations been
met? Academic Medicine, 68, S79–S88.
Bransford, J. D., Brown, A. L., & Cocking, R. (2000). How people learn.
Washington DC: National Academy Press.
Capon, N., & Kuhn, D. (2004). What’s so good about problem-based learn-
ing? Cognition and Instruction, 22, 61–79.
Chinn, C. A. (2006). Learning to argue. In A. M. O’Donnell, C. Hmelo-
Silver, & G. Erkens (Eds.), Collaborative learning, reasoning, and tech-
nology (pp. 355–383). Mahwah, NJ: Erlbaum.
Chinn, C. A., & Hung, C.-C. (2007, April). Learning to reason about the
methodology of scientific studies: A classroom experiment in the middle
school. Paper presented at the annual meeting of the American Educa-
tional Research Association, Chicago, IL.
Chinn, C. A., O’Donnell, A. M., & Jinks, T. S. (2000). The structure of
discourse in collaborative learning. Journal of Experimental Education,
69, 77–97.
Cognition and Technology Group at Vanderbilt. (1992). The Jasper series
as an example of anchored instruction: Theory, program description and
assessment data. Educational Psychologist, 27, 291–315.
Collins, A., Brown, J. S., & Newman, S. E. (1989). Cognitive apprenticeship:
Teaching the crafts of reading, writing, and mathematics. In L. B. Resnick
(Ed.), Knowing, learning, and instruction: Essays in honor of Robert
Glaser (pp. 453–494). Hillsdale, NJ: Erlbaum.
Davis, E. A. (2003). Prompting middle school science students for produc-
tive reflection: Generic and directed prompts. Journal of the Learning
Sciences, 12, 91–142.
Davis, E. A., & Linn, M. C. (2000). Scaffolding students’ knowledge inte-
gration: Prompts for reflection in KIE. International Journal of Science
Education, 22, 819–837.
DeBoer, G. E. (1991). A history of ideas in science education.NewYork:
Teachers College Press.
Department for Education /Welsh Office (DFE/WO). (1995). Science in the
national curriculum (1995). London: HMSO.
Derry, S. J., Hmelo-Silver, C. E., Nagarajan, A., Chernobilsky, E., & Beitzel,
B. (2006). Cognitive transfer revisited: Can we exploit new media to
solve old problems on a large scale? Journal of Educational Computing
Research, 35, 145–162.
Dochy, F., Segers, M., Van den Bossche, P., & Gijbels, D. (2003). Effects of
problem-based learning: A meta-analysis. Learning and Instruction, 13,
Driver, R., Leach, J., Millar, R., & Scott, P. (1996). Young people’s images
of science. Buckingham, England: Open University Press.
Duncan, R. G. (2006). The role of domain-specific knowledge in promoting
generative reasoning in genetics. In S. A. Barab, K.E. Hay, & D. T.
Hickey (Eds.), Proceedings of the seventh international conference for
the learning sciences: Making a difference (pp. 147–154). Mahwah, NJ:
Duschl, R. (1990). Restructuring science education: The importance of
theories and their development. New York: Teachers College Press.
Edelson, D. C. (2001). Learning-for-use: A framework for integrating con-
tent and process learning in the design of inquiry activities. Journal of
Research in Science Teaching, 38, 355–385.
Gallagher, S. A., Stepien, W. J., & Rosenthal, H. (1992). The effects of
problem-based learning on problem solving. Gifted Child Quarterly, 36,
Geier, R., Blumenfeld, P., Marx, R., Krajcik, J., Fishman, B., & Soloway, E.
(in press). Standardized test outcomes for students engaged in inquiry-
based science curriculum in the context of urban reform. Journal of
Research in Science Teaching.
Golan, R., Kyza, E. A., Reiser, B. J., & Edelson, D. C. (April, 2002). Scaf-
folding the task of analyzing animal behavior with the Animal Landlord
software. Paper presented at the Annual Meeting of the American Educa-
tional Research Association, New Orleans, LA.
Greeno, J. G. (2006). Learning in activity. In R. K. Sawyer (Ed.), The
Cambridge handbook of the learning sciences (pp. 79–96). New York:
Guthrie, J. T., Wigfield, A., Barbosa, P., Perencevich, K. C., Taboada, A.,
Davis, M. H., et al. (2004). Increasing reading comprehension and en-
gagement through concept-oriented reading instruction. Journal of Edu-
cational Psychology, 96, 403–423.
Guzdial, M. (1994). Software-realized scaffolding to facilitate programming
for science learning. Interactive Learning Environments, 4, 1–44.
Hickey, D. T., Kindfeld, A. C. H., Horwitz, P., & Christie, M. A. (1999).
Advancing educational theory by enhancing practice in a technology-
supported genetics learning environment. Journal of Education, 181, 25–
Hickey, D. T., Wolfe, E. W., & Kindfield, A. C. H. (2000). Assessing learning
in a technology-supported genetics environment: Evidential and conse-
quential validity issues. Educational Assessment, 6, 155–196.
Hmelo, C. E. (1998). Problem-based learning: Effects on the early acquisi-
tion of cognitive skill in medicine. Journal of the Learning Sciences, 7,
Hmelo, C. E., & Guzdial, M. (1996). Of black and glass boxes: Scaffolding
for learning and doing. In D. C. Edelson & E. A. Domeshek (Eds.),
Proceedings of ICLS 96 (pp. 128–134). Charlottesville, VA: AACE.
Hmelo, C. E., & Lin, X. (2000). Becoming self-directed learners: Strategy
development in problem-based learning. In D. Evensen & C. E. Hmelo
(Eds.), Problem-based learning: A research perspective on learning in-
teractions (pp. 227–250). Mahwah, NJ: Erlbaum.
Hmelo-Silver, C. E. (2003). Analyzing collaborative knowledge construc-
tion: Multiple methods for integrated understanding. Computers and Ed-
ucation, 41, 397–420.
Hmelo-Silver, C. E. (2004). Problem-based learning: What and how do
students learn? Educational Psychology Review, 16, 235–266.
Hmelo-Silver, C. E. (2006). Design principles for scaffolding technology-
based inquiry. In A. M. O’Donnell, C. E. Hmelo-Silver, & G. Erkens
(Eds.), Collaborative reasoning, learning and technology (pp. 147–170).
Mahwah, NJ: Erlbaum.
Hmelo-Silver, C. E., & Barrows, H. S. (2006). Goals and strategies of a
problem-based learning facilitator. Interdisciplinary Journal of Problem-
based Learning, 1, 21–39.
Hmelo-Silver, C. E., Derry, S. J., Woods, D., DelMarcelle, M., & Chernobil-
sky, E. (2005). From parallel play to meshed interaction: The evolution
of the EStep system. In D. Suthers & T. Koschmann (Eds.), Proceedings
of CSCL 2005. Mahwah, NJ: Erlbaum.
Horwitz, P., Neumann, E., & Schwartz, J. (1996). Teaching science at mul-
tiple levels: The GenScope program. Communications of the ACM, 39,
Jackson, S., Stratford, S. J., Krajcik, J. S., & Soloway, E. (1996). Making
system dynamics modeling accessible to pre-college science students.
Interactive Learning Environments, 4, 233–257.
Kirschner, P. A., & Erkens, G. (2006). Cognitive tools and mindtools for
collaborative learning. Journal of Educational Computing Research, 35,
Kirschner, P. A., Sweller, J., & Clark, R. E. (2006). Why minimal guidance
during instruction does not work: An analysis of the failure of construc-
tivist, discovery, problem-based, experiential, and inquiry-based teaching.
Educational Psychologist, 41, 75–86.
Kolodner, J. L. (1993). Case-based reasoning. San Mateo, CA: Morgan
Krajcik, J. S., & Blumenfeld, P. (2006). Project-based learning. In R. K.
Sawyer (Ed.), The Cambridge handbook of the learning sciences (pp.
317–334). New York: Cambridge.
Krajcik, J. S., Czerniak, C., & Berger, C. (1999). Teaching children science:
A project-based approach. Boston, MA: McGraw-Hill.
Kuhn, D., Black, J., Keselman, A., & Kaplan, D. (2000). The development
of cognitive skills to support inquiry learning. Cognition and Instruction,
18, 495–523.
Langer, J. A. (2001). Beating the odds: Teaching middle and high school
students to read and write well. American Educational Research Journal,
38, 837–880.
Lederman, N. G. (1998). The state of science education: Subject matter
without context. Electronic Journal of Science Education, 41.
Leinhardt, G., & Steele, M. D. (2005). Seeing the complexity of standing to
the side: Instructional dialogues. Cognition and Instruction, 23, 87–163.
Linn, M. C., Bell, P., & Hsi, S. (1999). Lifelong science learning on the
Internet: The knowledge integration environment. Interactive Learning
Environments, 6, 4–38.
Linn, M. C., Davis, E. A., & Bell, P. (2004). Internet environments for
science education. Mahwah, NJ: Erlbaum.
Linn, M. C., & Slotta, J. D. (2006). Enabling participants in online forums
to learn from each other. In A. M. O’Donnell, C. E. Hmelo-Silver, &
G. Erkens (Eds.), Collaborative learning, reasoning, and technology (pp.
61–98). Mahwah, NJ: Erlbaum.
Loh, B., Reiser, B. J., Radinsky, J., Edelson, D. C., Gomez, L. M., & Marshall,
S. (2001). Developing reflective inquiry practices: A case study of soft-
ware, the teacher, and students. In K. Crowley, C. Schunn, & T. Okada
(Eds.), Designing for science: Implications from everyday, classroom, and
professional settings (pp. 279–324). Mahwah, NJ: Erlbaum.
Lynch, S., Kuipers, J., Pyke, C., & Szesze, M. (2005). Examining the effects
of a highly rated science curriculum unit on diverse students: Results from
a planning grant. Journal of Research in Science Teaching, 42, 921–946.
Mayer, R. E. (2004). Should there be a three-strikes rule against pure dis-
covery learning? American Psychologist, 59, 14–19.
McComas, W. F., Clough, M. P., & Almazroa, H. (1998). The role and char-
acter of the nature of science in science education. Science and Education,
7, 511–532.
Mergendoller, J. R., Maxwell, N. L., & Bellisimo, Y. (2006). The effective-
ness of problem-based instruction: A comparative study of instructional
method and student characteristics. Interdisciplinary Journal of Problem-
based Learning. 1, 49–69.
Ministry of Education (2001). Standards for nine-year continuous curricu-
lum at elementary and junior high level in Taiwan. Taipei: Ministry of
Education, R.O.C.
Minstrell, J., & Stimpson, V. (1996). A classroom environment for learning:
Guiding students’ reconstruction of understanding and reasoning. In L.
Schauble & R. Glaser (Eds.), Innovations in learning: New environments
for education (pp. 175–202). Mahwah, NJ: Erlbaum.
National Council of Teachers of Mathematics (NCTM). (2000). Principles
and standards for school mathematics. Reston, VA: NCTM.
National Research Council (NRC). (1996). National science education stan-
dards. Washington DC: National Academy Press.
Norman, G. R., Brooks, L. R., Colle, C. L., & Hatala, R. M. (2000). The
benefit of diagnostic hypotheses in clinical reasoning: Experimental study
of an instructional intervention for forward and backward reasoning. Cog-
nition and Instruction, 17, 433–448.
Norman, G. R., Trott, A. D., Brooks, L. R., & Smith, E. K. (1994). Cognitive
differences in clinical reasoning related to postgraduate training. Teaching
and Learning in Medicine, 6, 114–120.
Palincsar, A. S. (1998). Social constructivist perspectives on teaching and
learning. Annual Review of Psychology, 45, 345–375.
Patel, V. L., Groen, G. J., & Norman, G. R. (1993). Reasoning and instruction
in medical curricula. Cognition and Instruction, 10, 335–378.
Puntambekar, S., & Kolodner, J. L. (2005). Toward implementing distributed
scaffolding: Helping students learn from design. Journal of Research in
Science Teaching, 42, 185–217.
Quintana, C., Reiser, B. J., Davis, E. A., Krajcik, J., Fretz, E., Duncan, R.
G., et al. (2004). A scaffolding design framework for software to support
science inquiry. Journal of the Learning Sciences, 13, 337–386.
Reiser, B. J., Tabak, I., Sandoval, W. A., Smith, B. K., Steinmuller, F.,
& Leone, A. J. (2001). BGuILE: Strategic and conceptual scaffolds for
scientific inquiry in biology classrooms. In S. M. Carver & D. Klahr (Eds.),
Cognition and instruction: Twenty-five years of progress (pp. 263–305).
Mahwah, NJ: Erlbaum.
Reiser, B. J. (2004). Scaffolding complex learning: The mechanisms of
structuring and problematizing student work. Journal of the Learning
Sciences, 13, 273–304.
Rogoff, B. (1990).Apprenticeship in thinking: Cognitive development in
social context. New York: Oxford University Press.
Salomon, G., Perkins, D. N., & Globerson, T. (1991). Partners in cognition:
Extending human intelligences with intelligent technologies. Educational
Researcher, 20, 2–9.
Sandoval, W. A., & Reiser, B. J. (2004). Explanation-driven inquiry: Inte-
grating conceptual and epistemic supports for science inquiry. Science
Education, 88, 345–372.
Schank, R.C. (1982). Dynamic Memory: A theory of reminding and
learning in computers and people. Cambridge: Cambridge University
Schank, R., & Cleary, C. (1995). Engines for education. Hillsdale, NJ:
Schmidt, H. G. (1983). Problem-based learning: rationale and description.
Medical Education, 17, 11–16.
Schneider, R. M., & Krajcik, J. (2002). Supporting science teacher learning:
The role of educative curriculum materials. Journal of Science Teacher
Education, 13, 221–245.
Schwartz, D. L., & Bransford, J. D. (1998). A time for telling. Cognition and
Instruction, 16, 475–522.
Schwartz, D. L., & Martin, T. (2004). Inventing to prepare for future learn-
ing: The hidden efficiency of encouraging original student production in
statistics instruction. Cognition and Instruction, 22, 129–184.
Shymansky, J.A. (1984). BSCS programs: Just how effective were they? The
American Biology Teacher, 46, 54–57.
Singer, J., Rivet, A., Schneider, R. M., Krajcik, J. S., Amati, K., & Marx, R.
W. (2000, April). Setting the stage: Engaging students in water quality.
Paper presented at the Annual Meeting of the American Educational
Research Association, New Orleans, LA.
Smith, B. K., & Reiser, B. J. (1998). National Geographic unplugged: De-
signing interactive nature films for classrooms. In C.-M. Karat, A. Lund,
J. Coutaz, & J. Karat (Eds.), Proceedings of CHI 98: Human factors in
computing systems (pp. 424–431). New York: ACM Press.
Toth, E. E., Suthers, D. D., & Lesgold, A. M. (2002). “Mapping to know”:
The effects of representational guidance and reflective assessment on
scientific inquiry. Science Education, 86, 244–263.
Vernon, D. T., & Blake, R. L. (1993). Does problem-based learning work?
A meta-analysis of evaluative research. Academic Medicine, 68,550
Von Secker, C., & Lissitz, R. W. (1999). Estimating the impact of instruc-
tional practices on student achievement in science. Journal of Research
in Science Teaching, 36, 110–1126.
Vygotsky, L. S. (1978). Mind in society. Cambridge, MA: Harvard Univer-
sity Press.
White, B. Y., & Frederiksen, J. R. (1998). Inquiry, modeling, and metacogni-
tion: Making science accessible to all students. Cognition and Instruction,
16, 3–118.
Wise, K., C., & Okey, J. R. (1983). A meta-analysis of the effects of var-
ious science teaching strategies on achievement. Journal of Research in
Science Teaching, 20, 419–435.
Wu, Y.-T., & Tsai, C.-C. (2005). Effects of constructivist-oriented instruction
on elementary school students’ cognitive structures. Journal of Biological
Education, 39, 113–119.
... Inquiry-based environments also vary in the types of guidance embedded within the inquiry process, which differ in their specificity and include process constraints, status overviews, prompts, heuristics, scaffolds, and explanations (De Jong & Lazonder, 2014;Lazonder & Harmsen, 2016). This line of research indicates that with adequate guidance and support, students are able to successfully overcome the numerous challenges posed inquiry-based learning, leading inquiry to be even more effective than other more expository instructional approaches (Belland et al., 2013;Hmelo-Silver et al., 2007;Kirschner et al., 2010;Kuhn et al., 2000;Minner et al., 2010). A recent meta-analysis indicates that diverse types of guidance, albeit differences in their specificity are equally effective in promoting learning outcomes (Lazonder & Harmsen, 2016). ...
... Studies about inquiry-based teaching and learning emphasize the teachers' crucial role in effectively guiding students' learning in inquiry-based learning environments (Dobber et al., 2017;Furtak et al., 2012;Marshall et al., 2017). Teacher guidance can be seen as a form of structure necessary to facilitate learning, especially in complex activities such as scientific inquiry (Hmelo-Silver et al., 2007;Schmidt et al., 2007), which includes feedback, comments, suggestions, and scaffolding (Zhang & Cobern, 2021). Adequate teacher guidance is needed to support learners, which may otherwise face cognitive overload and fail to meaningfully engage in the inquiry process (Kirschner et al., 2010). ...
... Inquiry-based approaches pose numerous challenges for learners (Quintana et al., 2004). Research indicates that to effectively engage students in inquiry-based learning, appropriate guidance should be embedded within the process (Hmelo-Silver et al., 2007;Quintana et al., 2004). Lazonder and Harmsen (2016) defined guidance as "any form of assistance offered before and/or during the inquiry learning process that aims to simplify, provide a view on, elicit, supplant, or prescribe the scientific reasoning skills involved" (Lazonder & Harmsen, 2016, p. 687). ...
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Inquiry includes a broad spectrum of approaches, depending on students’ responsibility over the process and the extent of the teacher’s guidance. While numerous studies have examined students’ achievements and engagement across different types of inquiry-based environments, analyses of teachers’ guidance during the process are lacking. Therefore, our overarching goal was to examine the interplay between characteristics of the inquiry-based environment and teacher’s just-in-time support. Specifically, we examined the learning processes and achievements of middle-school students as they collaboratively engaged in either a structured or a guided inquiry-based task and were supported by their teacher. Structuring scaffolds were designed to support the structured inquiry task, while problematizing scaffolds were designed to support the guided inquiry task. Post-test scores indicated a similar significant increase in students’ scientific understanding for both research conditions, despite significant differences in students’ engagement in metacognitive processes during their scientific trials. Students from the guided inquiry group engaged in longer discussions and made more references to metacognitive processes, in comparison to students from the structured inquiry group. A low to moderate correlation between students’ engagement in metacognitive processes and test-scores was identified. The teacher’s regulation of students’ discourse in the structured inquiry group was significantly greater than in the guided inquiry group, though the nature of regulation was similar. We propose that the teacher’s regulation of students’ metacognitive discourse outweighed the differences between students’ learning processes in the two learning environments, resulting in similar achievements in the two conditions albeit differences in metacognitive engagement. Implications are discussed.
... This shift in the teaching paradigm emphasizes the adaptation of learner-centric instruction and inclusive pedagogies to stimulate the effectiveness of the instructional processes [1,2]. Differentiated instruction (DI) strategies have a significant impact on the degree to which teachers can maximize the heterogeneity of the potential of all learners to access personalized instruction and equitable academic successes within learner-centred pedagogies [3,4,5]. Differentiated instruction is a teaching practice based on constructivist learning theory that promotes the adaptation of content to the unique environmental experiences, cognitive capacities, and learning styles of students [5,6]. ...
... Interesting outcomes were found for autonomous projects, inquiries, and independent studies in first-cycle schools. The constructivist learning paradigm, which promotes learner independence, is compatible with this predisposition, which emphasizes developing independent learning [3,32]. However, the desire for interest centres, interest groups, and learning stations was stronger in second-cycle schools. ...
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The emphasis on adapting learner-centric education and inclusive pedagogies to promote learning effectiveness is part of the paradigm shift in teaching. By maximizing variability, differentiated education methodologies ensure individualized instruction and equal academic success for all students. Based on this justification, this study sought to investigate Ghanaian pre-tertiary teachers' adaption of differentiated instruction strategies during the teaching and learning processes. Pre-tertiary teachers within the Kwahu Ridge of the Eastern Region of Ghana were sampled to respond to the close-ended questionnaire. A multi-pronged approach was employed in the data analysis. Respondents possessed knowledge of the differentiated instruction strategies. However, there were some disparities between first and second-cycle teachers. Significant factors influenced the range of diversity in the classroom and knowledge and experience, with the latter showing an unexpected negative influence, possibly due to experienced teachers' preference for traditional methods of teaching. Notwithstanding, a perfect alignment of instructional techniques, activities and assessment practices to accommodate the heterogeneity of students stimulate active participation, interest and readiness to learn. It is recommended that educational stakeholders should recognize the dynamic nature of the learning environment and better provide pre-tertiary teachers with the tools and support needed to employ differentiated instruction techniques successfully to ensure inclusive, individualized and intensive instruction in the classroom.
... topics are interconnected through a scaffolding instructional approach with the course's driving focus being to have students develop a "sophisticated project" by creating a website. Scaffolding is a commonly used method within problem-based learning to limit cognitive load issues (Greening, 1998;Hmelo-Silver et al., 2007). Scaffolding may also be used within project-based learning. ...
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Assessments play a pivotal role in student performance within higher education courses. In this article the effect of deemphasizing homework assignments and focusing on the course driven project had on undergraduate students’ performance is clearly described. Using student grades as data sets, performance is compared over the Fall 2020, Fall 2021, and Fall 2022 semesters. Grade computation has slightly changed over these three semesters, primarily related to the deemphasizing of homework assignments. During the Covid-19 impacted Fall 2020 course participation was calculated using weekly quizzes instead of through in-class participation. Due to the varied majors of students, a scaffolding approach was used to deliver course content, so all students were allowed the opportunity to build a sophisticated website through project-based learning. While deemphasizing homework assignments did not positively affect student performance, students produced more professional websites for their final project.
... Finally, the personal development (Fraser, 1998) or instructional dimension (Wang et al., 2020b) assesses the perceptions of instruction strategies and learning processes, which favor (or not) students' personal growth and learning in the classroom (Fraser, 1998). This dimension is dependent on supportive interactions that facilitate learning, the provision of challenging tasks, and constructive feedback (Hmelo-Silver et al., 2007;Fauth et al., 2014). ...
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Education institutional guidelines around the world agree that building more inclusive schools is a priority. The reality of school practice, however, belies this institutional will. To help fill the gap, this theoretical review documents the value that the construct of classroom climate brings to research and practice in terms of inclusive school development. The article firstly points out that the current main challenge is to develop Inclusive Mainstream Teaching (IMT) in diverse classrooms. Indeed, IMT is needed in all classrooms to guarantee the effectiveness of special accomodating measures in schools that are targeted at special education needs students. Intervening at classroom level is both a pragmatic and powerful way of developing inclusive schooling. However, developing IMT in the classroom remains a challenge for both teachers and researchers. Thus this review documents the central role that classroom climate should play in the development of IMT. More precisely, the factors of classroom climate that are associated with inclusive outcomes are identified. We also highlight how these factors and the measurements associated with them are efficient tools to guide IMT development. These measures are proximal, sensitive, complementary, and pragmatic indicators of effective IMT. Such indicators are very useful in helping research empirically document effective IMT, ensure that any small improvement is assessed, monitor teachers' progress, and assist their professional growth. Theoretically positioned as a mediator between inclusive teaching in mainstream classrooms and inclusive school outcomes, inclusive classroom climate is a tool that appears to be effective in supporting IMT development and, consequently, in the establishment of more inclusive schools.
... Consequently, some of them explored the level of guidance along with teachers' understanding of students' difficulties (Kapici et al., 2022). The results depict that if teachers understand their students' difficulties while learning, then they can support them more efficiently (Engelhardt & Beichner, 2004;Gaigher, 2014;Hmelo-Silver et al., 2007;Moodley & Gaigher, 2019). According to some other researchers (e.g. ...
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Laboratories are considered to play a unique role in circuits teaching. Laboratories can be traditional, with physical components and desks, or virtual with graphical simulators. Applying these facilities in teaching, students can make experiments or measurements by exploring electric circuits’ features. However, an intriguing research question is whether physical components or graphical simulators are more appropriate to build knowledge, enhance skills and improve attitudes. Thus, the aim of this article is: 1) to perform a review in order to explore the characteristics of the studies that compare the tangible and graphical user interfaces and 2) to apply a meta-analysis for the effects of the interfaces under study. The meta-analysis included 88 studies with pre/post-tests designs with 2798 participants, which were emerged from: a) 4 databases, b) forward snowballing method. The review showed that the majority of researchers have focused on the knowledge gaining, while a few researchers have examined skills and attitudes. The meta-analysis showed that the combination of user interfaces (tangible/graphical) appears to be the most beneficial for students in the domain of electric circuits teaching.
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We propose a design science research approach to entrepreneurship. We introduce the notion of 'scaffolding artifacts', which support and enable entrepreneurs to pursue the venturing process. We suggest creating such artifacts in a manner that is inspired by design science practices in information systems. The researcher can build on different knowledge types in the research process by drawing from science and practice. We see the design science researcher as a specific 'third role', which differs from the practitioner and the 'naturalistic' researcher. Design science researchers combine knowledge generation with the design of purposeful artifacts, constituting a third way. In entrepreneurship, this third role may become a fruitful way of looking not just 'at the entrepreneurs but looking with them. 1 We suggest an iterative process with five steps to create scaffolding artifacts. It starts with a heuristic front-end, followed by requirement definition, design and implementation of an artifact, validation, and reflection and communication.
Authentic learning is gaining attention due to being perceived as a more engaging and effective way of teaching students. Many schools are incorporating authentic learning into their curricula, and numerous studies have also been conducted investigating the effectiveness of authentic learning in improving student outcomes. Various primary studies have been conducted in Turkey examining the effect of authentic learning on academic achievement and learning retention, which have an important place among learning outcomes. It was observed that the results of these individual studies reported different effect sizes on the effectiveness of authentic learning. This review aimed to report the overall effect sizes by analyzing the results of experimental and quasi-experimental studies examining the effect of authentic learning on academic achievement and learning retention through meta-analysis. Of the 180 studies listed as a result of the literature search, 11 studies (13 effect sizes) for academic achievement and four studies (six effect sizes) for the learning retention variables that meet the inclusion criteria were coded and analyzed. The results of the analysis showed a moderate overall effect size for the effectiveness of authentic learning on both academic achievement (g = 0.991) and learning retention (g = 0.925). It is possible to say that the overall effect sizes obtained as a result of the meta-analysis are moderate, quite remarkable for educational research, and that authentic learning is more effective in increasing academic achievement and learning retention than traditional education processes.
A feature of student–teacher–scientist partnerships (STSPs) involves students working with scientists for the purpose of helping them learn more about how scientists work and think. Previous research on STSPs has generally focused on identifying the best practices of partnerships and on identifying challenges of these partnerships. The study reported here employed a cluster-randomized trial design to test the effectiveness of the PlantingScience STSP that combines high-quality curriculum, teacher preparation, and online mentoring by professional scientists. The results of the current study show that students who participated in the PlantingScience STSP showed significant improvements in science content knowledge and attitudes about scientists compared with students in the control group. The study sample was highly representative, demographically, to the U.S. population of high schools. These results add to the limited empirical evidence about the effectiveness of STSPs on student outcomes related to science achievement and attitudes.
Background To create design solutions experienced engineering designers engage in expert iterative practice. Researchers find that students struggle to learn this critical engineering design practice, particularly when tackling real‐world engineering design problems. Purpose/Hypothesis To improve our ability to teach iteration, this study contributes (i) a new teaching approach to improve student teams' expert iterative practices, and (ii) provides support to existing frameworks—chiefly the Design Risk Framework—that predict the key metacognitive processes we should support to help students to engage in expert iterative practices in real‐world engineering design. Design/Method In a 3‐year design‐based research study, we developed a novel approach to teaching students to take on real‐world engineering design projects with real clients, users, and contexts to engage in expert iterative practices. Results Study 1 confirms that student teams struggle to engage in expert iterative practices, even when supported by problem‐based learning (PBL) coaching. Study 2 tests our novel approach, Planning‐to‐Iterate, which uses (i) templates, (ii) guiding questions to help students to define problem and solution elements, and (iii) risk checklists to help student teams to identify risks. We found that student teams using Planning‐to‐Iterate engaged in more expert iterative practices while receiving less PBL coaching. Conclusions This work empirically tests a design argument—a theory for a novel teaching approach—that augments PBL coaching and helps students to identify risks and engage in expert iterative practices in engineering design projects.
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Evidence for the superiority of guided instruction is explained in the context of our knowledge of human cognitive architecture, expert–novice differences, and cognitive load. Although unguided or minimally guided instructional approaches are very popular and intuitively appealing, the point is made that these approaches ignore both the structures that constitute human cognitive architecture and evidence from empirical studies over the past half-century that consistently indicate that minimally guided instruction is less effective and less efficient than instructional approaches that place a strong emphasis on guidance of the student learning process. The advantage of guidance begins to recede only when learners have sufficiently high prior knowledge to provide “internal” guidance. Recent developments in instructional research and instructional design models that support guidance during instruction are briefly described.
By allowing key scientists, researchers, professors, and classroom teachers of science to speak for themselves through their published writing about what is best and needed for the field, Dr. DeBoer presents a fascinating account of the history of science education in the United States from the middle of the nineteenth century to the present. The book relates how science first struggled to find a place in the school curriculum and recounts the many debates over the years about what that curriculum should be. In fact, many of that we consider modern ideas in science education are not new at all but can be traced to writings on education of one hundred years ago. A History of Ideas in Science Education is the only book of its kind to summarize the history of science education in this way. It identifies the goals of science education and shows how these goals have competed with one another for the public’s attention. Besides discussing the origins of science teaching in this country, the book also pays attention to the larger educational goals of science instruction and the strategies that have been used to accomplish these goals.
Meeting ambitious content and process (inquiry) standards is an important challenge for science education reform particularly because educators have traditionally seen content and process as competing priorities. However, integrating content and process together in the design of learning activities offers the opportunity to increase students' experience with authentic activities while also achieving deeper content understanding. In this article, I explore technology-supported inquiry learning as an opportunity for integrating content and process learning, using a design framework called the Learning-for-Use model. The Learning-for-Use model is a description of the learning process that can be used to support the design of content-intensive, inquiry-based science learning activities. As an example of a technology-supported inquiry unit designed with the Learning-for-Use model, I describe a curriculum called the Create-a-World Project, in which students engage in open-ended Earth science investigations using WorldWatcher, a geographic visualization and data analysis environment for learners. Drawing on the Learning-for-Use model and the example, I present general guidelines for the design of inquiry activities that support content learning, highlighting opportunities to take advantage of computing technologies.
Suggestions for improving text understanding often prescribe activating prior knowledge, a prescription that may be problematic if students do not have the relevant prior knowledge to begin with. In this article, we describe research about a method for developing prior knowledge that prepares students to learn from a text or lecture. We propose that analyzing contrasting cases can help learners generate the differentiated knowledge structures that enable them to understand a text deeply. Noticing the distinctions between contrasting cases creates a "time for telling"; learners are prepared to be told the significance of the distinctions they have discovered. In 3 classroom studies, college students analyzed contrasting cases that consisted of simplified experimental designs and data from classic psychology experiments. They then received a lecture or text on the psychological phenomena highlighted in the experiments. Approximately 1 week later, the students predicted outcomes for a hypothetical experiment that could be interpreted in light of the concepts they had studied. Generating the distinctions between contrasting cases and then reading a text or hearing a lecture led to more accurate predictions than the control treatments of (a) reading about the distinctions between the cases and hearing a lecture, (b) summarizing a relevant text and hearing a lecture, and (c) analyzing the contrasting cases twice without receiving a lecture. We argue that analyzing the contrasting cases increased students' abilities to discern specific features that differentiated classes of psychological phenomena, much as a botanist can distinguish subspecies of a given flower. This differentiated knowledge prepared the students to understand deeply an explanation of the relevant psychological principles when it was presented to them. These results can inform constructivist models of instruction as they apply to classroom activities and learning from verbal materials. In particular, the results indicate that there is a place for lectures and readings in the classroom if students have sufficiently differentiated domain knowledge to use the expository materials in a generative manner.
The notion of scaffolding learners to help them succeed in solving problems otherwise too difficult for them is an important idea that has extended into the design of scaffolded software tools for learners. However, although there is a growing body of work on scaffolded tools, scaffold design, and the impact of scaffolding, the field has not yet converged on a common theoretical framework that defines rationales and approaches to guide the design of scaffolded tools. In this article, we present a scaffolding design framework addressing scaffolded software tools for science inquiry. Developed through iterative cycles of inductive and theory-based analysis, the framework synthesizes the work of prior design efforts, theoretical arguments, and empirical work in a set of guidelines that are organized around science inquiry practices and the challenges learners face in those practices. The framework can provide a basis for developing a theory of pedagogical support and a mechanism to describe successful scaffolding approaches. It can also guide design, not in a prescriptive manner but by providing designers with heuristics and examples of possible ways to address the challenges learners face.
Collins, A., Brown, J.S., & Newman, S.E. (1989). Cognitive apprenticeship: Teaching the crafts of reading, writing, and mathematics. In L. B. Resnick (Ed.) Knowing, learning, and instruction: E...