Policy Insights from the
Behavioral and Brain Sciences
2015, Vol. 2(1) 33 –41
© The Author(s) 2015
Designing Education for Deep Learning: Use Research
Evidence about What to teach, How to teach it, and How to
know if they learned it.
Citizens of the 21st century need to be flexible prob-
lem solvers who can adapt what they know for use in
Research on how people learn provides principles for
revamping education systems to produce citizens for
the 21st century.
Changes to curriculum, instruction, and assessment
need to build on the knowledge and beliefs students
bring to learning situations.
Learning is inherently interpersonal and benefits from
collaboration as well as active self-monitoring and
Classroom instruction needs to promote student
agency and identity-as-learners through classroom
discussion, challenging tasks, and ongoing formative
assessment that provides feedback to guide the learn-
Business leaders, educational organizations, and researchers are
calling for new education policies that target the development of
broad, transferable skills and knowledge, often referred to as
“Deeper Learning” and/or “21st century skills” (e.g., see
Ananiadou & Claro, 2009; Bellanca, 2014; Pellegrino & Hilton,
2012). In response, the United States and other countries are
generating new standards for educational outcomes. These are
intended to produce “college and career ready” young adults
601866BBSXXX10.1177/2372732215601866Policy Insights from the Behavioral and Brain SciencesGoldman and Pellegrino
1University of Illinois, Chicago, USA
Susan R. Goldman, Learning Sciences Research Institute & Department of
Psychology, University of Illinois at Chicago, 1240 W Harrison St., Room
1535A, Chicago, IL 60607, USA.
Research on Learning and Instruction:
Implications for Curriculum,
Instruction, and Assessment
Susan R. Goldman1 and James W. Pellegrino1
There is considerable rhetoric about the need for our educational system to promote deeper learning and the development
of 21st-century skills. Missing from the discourse is recognition that much of what we know from research on learning and
instruction has yet to affect the design and enactment of everyday schooling in the form of curriculum, instruction, and
assessment. This article considers some of the key research-based principles on learning and knowing and their implications
for the design of instruction and assessment. Among these principles are differences in naïve and expert forms of knowing
and how the latter develops through a variety of instructional methods and materials. Another is the social nature of learning
and the classroom instructional and assessment practices that support students taking control of and monitoring their own
learning. Incorporating many of the findings from research on learning and instruction into the materials, structures, and
practices of everyday schooling involves addressing systemic challenges of practice and policy. These include the development
and implementation of curricular and instructional resources that incorporate proven, research-based features, the design
of assessment systems that balance and align classroom assessment and system monitoring needs, and more effective
approaches to teacher preparation and professional development. The knowledge base to support such changes exists but
for research-based educational interventions to move beyond isolated promising examples and to flourish more widely, these
larger systemic issues, many of them policy driven, will need to be addressed.
learning, instruction, assessment, sociocultural, cognition
34 Policy Insights from the Behavioral and Brain Sciences 2(1)
(e.g., Common Core State Standards Initiative, 2010a, 2010b).
Along with new standards are new assessments (Partnership for
Assessment of Readiness for College and Careers, 2014;
Smarter Balanced Assessment Consortium, 2014). Underlying
the new standards and assessments is the claim that knowledge
in the form of memorized facts and rote procedures is inade-
quate to support flexible, creative, and innovative problem solv-
ing or responding in new situations. Rather, in new situations,
people need knowledge that helps them understand when, how,
and why to apply what they know, so that they can appropriately
use it (Pellegrino & Hilton, 2012). National and international
assessments such as NAEP (National Assessment of Educational
Progress) and PISA (Programme for International Student
Assessment) indicate that many educational systems fall short
in equipping graduates with these competencies (National
Center for Educational Statistics, 2012; Organisation for
Economic Co-Operation and Development, 2010; Rampey,
Dion, & Donahue, 2009; Vanneman, Hamilton, Baldwin
Anderson, & Rahman, 2009).
The imposition of new standards and assessments alone
will not address the gap between the status quo and what is
needed. Currently, most educational systems are poorly
equipped to fulfill 21st-century needs. A major reason for
this is outmoded perspectives on how people learn and how
instruction and assessment can be designed and productively
used in the service of learning. Research on learning and
instruction conducted over the past 60 years provides impor-
tant principles that should inform the design and evaluation
of contemporary learning environments.
Principles of Learning and Instruction
Traditional approaches to what we teach—the curriculum; how
we teach it—instruction; and how we evaluate what is
learned—assessment, are based on theories and models of
learning that have not kept pace with modern knowledge of
how people learn. They fail to acknowledge what we know
about the cognitive, social, and cultural dimensions of learning
(Bransford, Brown, & Cocking, 2000; Nasir, Rosebery, Warren,
& Lee, 2006; Pellegrino & Hilton, 2012). Furthermore, while
general principles of learning (e.g., laws of repetition, practice,
and feedback) are broadly applicable to all subject-matter areas
(e.g., Pashler et al., 2007), it is critical to take into account dis-
ciplinary differences in content, organization, and knowledge
generation practices. Such disciplinary differences have impor-
tant implications for what is taught, how it is taught, and how it
is assessed (Goldman, 2012; Moje, 2008). In what follows, we
review major findings from research on principles of learning,
instruction, and assessment and their implications for what is
taught, how, and roles for assessment.
Research-Based Principles of Learning
While there are many important findings on learning, we
highlight four principles that have particular significance for
the design of curriculum, instruction, and assessment.
First, students do not come to classroom learning situa-
tions as “blank” slates. Rather they bring conceptions of
themselves and their worlds that include beliefs, knowl-
edge, and language and discourse practices. These concep-
tions come from various experiences in their homes,
communities, and prior schooling. People’s conceptions, or
funds of knowledge (Moll & Greenberg, 1990), shape how
people frame learning situations, their roles in them, efforts
they are willing to invest in learning, and ultimately what
they learn. Educational efforts need to acknowledge and
build on learners’ conceptions, so that they have opportuni-
ties to notice and confront consistencies and inconsisten-
cies and engage in productive knowledge integration
(Gutiérrez, Baquedano-López, Alvarez, & Chiu, 1999;
Moje et al., 2004). Thus, a critical feature of effective
teaching is that it elicits students’ preexisting understand-
ings of subject matter and provides opportunities to build
on, or challenge, them.
Indeed, research on early learning suggests beginning in
the preschool years because children develop sophisticated
understandings of many of the phenomena around them.
Sometimes, those understandings align with generally
accepted ideas and provide a foundation for building new
knowledge. But sometimes, they are incomplete and/or
inconsistent with established principles. For example, in sci-
ence, students often have conceptions of physical properties
that cannot be easily observed and that are at variance with
scientifically accepted conceptions (e.g., atoms do not move
in solids; Duit, 2004). In humanities, preconceptions often
include stereotypes or simplifications, as when history is
understood as a cut and dried struggle between good and evil
(Gardner, 1991). If the conceptions that students hold are not
brought into the learning situation, they may fail to grasp
new concepts, and preexisting conceptions remain their “go
It is also the case that existing understandings can bridge
between in-school and out-of-school knowledge and sense-
making practices (e.g., Gutiérrez et al., 1999). For example,
Lee (2007) developed the cultural modeling approach as a
means of making the structure of a domain visible and
explicit to students. Using everyday texts such as rap songs,
Lee asked high school students to be explicit about not only
what the song meant but also how they knew that it was not
to be taken simply at a literal level. Making the processes
explicit for distinguishing literal from symbolic meaning in
everyday discourse facilitates using these interpretive pro-
cesses with the texts of formal schooling.
Making everyday content and process knowledge visible
is not always sufficient for constructing new conceptions.
Numerous research studies demonstrate the persistence of
preexisting understandings even after a new model has been
taught that contradicts the naïve understanding. For example,
students at a variety of ages persist in their beliefs that sea-
sons are caused by the earth’s distance from the sun rather
than by the tilt of the earth despite instruction to the contrary
(Duit, 2004). For the scientifically accepted understanding to
Goldman and Pellegrino 35
replace the naïve understanding, students must reveal the lat-
ter and have the opportunity to see where it falls short.
The second principle about how people learn is that the
content and organization of knowledge matter. To develop
competence in an area of inquiry, students must (a) have a
deep foundation of factual knowledge, (b) understand facts
and ideas in the context of a conceptual framework, and (c)
organize knowledge in ways that facilitate retrieval and
application. This principle emerges from research that com-
pares the performance of experts and novices, and from
research on learning and transfer (e.g., Bransford et al.,
2000). Experts, regardless of the field, always draw on richly
structured information; they are not just “good thinkers” or
“smart people”; nor do they necessarily have better overall
memories than other people.
In their domain of expertise, experts do know more facts
than other people but more crucial is that the facts are con-
nected and organized into patterns, or schemas, that are
meaningful for the content domain (Ericsson, Charness,
Feltovich, & Hoffman, 2006). Organization of the facts
according to important domain principles and frameworks
transforms factual information into “usable knowledge” and
reflects deep understanding. These organizational patterns,
frameworks, or schemas allow experts to see patterns, rela-
tionships, or discrepancies that are not apparent to novices.
They play an important role in experts’ abilities to plan a
task, generate reasonable arguments and explanations, and
draw analogies to other problems. Experts’ schematized con-
ceptual understanding allows them to extract a level of mean-
ing from information that is not apparent to novices (Chi,
Glaser, & Rees, 1982). This helps them select and remember
relevant information. Experts are also able to fluently access
relevant knowledge because their understanding of subject
matter allows them to quickly identify what is relevant.
Furthermore, organizing information into a conceptual
framework allows for greater transfer: Students can apply
what was learned to new situations and learn related infor-
mation more quickly (Schwartz, Bransford, & Sears, 2005).
Students who have learned geographical information for the
Americas in a conceptual framework approach the task of
learning the geography of another part of the globe with
questions, ideas, and expectations that help guide acquisition
of the new information. For example, understanding the geo-
graphical importance of the Mississippi River sets the stage
for students’ inquiry into the geographical importance of the
Nile, the Rhine, or the Yangtze. Understanding why rivers
are geographically important connects geography to other
important systems of civilizations (e.g., economics, politics,
social structures). As schematic webs become elaborated and
embellished, they increasingly guide what learners attend to,
and observe, ask questions and make inferences about, and
notice as violations of expectations. For example, why did
some cities and countries develop rapidly and prosper but
others did not?
An important implication of expertise research is that to
support transfer, curriculum and instruction need to emphasize
the conceptual organization of knowledge and “big ideas” in a
discipline. This emphasis should be present from the earliest
stages of learning onward (National Research Council, 2012).
Third, learning is enhanced when people engage in think-
ing about their own thinking and learning, a process referred
to as metacognition. Metacognition is an active process of
monitoring how learning is going: what is understood, what
is not; what fits to current conceptions and what does not;
what questions are answered; whether progress toward learn-
ing goals is being made. Metacognition also refers to what
learners know about their own learning processes (e.g., What
strategies are useful in what situations?) and how they evalu-
ate their own performance, the learning task and materials
(Azevedo & Aleven, 2010). Metacognition is instrumental in
students taking control of their own learning because it helps
them define and monitor progress toward learning goals,
select strategies to enhance learning, evaluate their progress
toward the goal, and select alternate strategies when obsta-
cles are encountered. Research with experts who were asked
to verbalize their thinking as they worked revealed that they
monitored their own understanding carefully, making note of
when additional information was required and whether new
information was consistent with what they already knew
(e.g., Wineburg, 1994). Metacognitive activities are an
important component of adaptive expertise, the ability to
solve novel as well as routine problems (Hatano & Inagaki,
Metacognition and many of the strategies we use for
thinking reflect cultural norms and methods of inquiry. They
are acquired in social interaction and through observation of
the behavior of others, including their verbalizations, ges-
tures, and emotional displays. Research has demonstrated
that children can be taught these strategies, including the
ability to predict outcomes, explain to oneself to improve
understanding, note failures to comprehend, activate back-
ground knowledge, plan ahead, and apportion time
(Bransford et al., 2000). Metacognitive activities must be
incorporated into the subject matter that students are learn-
ing. Attempts to teach metacognition as generic strategies
can lead to failure to transfer.
The fourth principle is that learning is fundamentally
interpersonal, often occurring in and through social interac-
tions. Even when individuals are learning in physical isola-
tion from others, they rely on culturally transmitted “wisdom
of the past,” communicated through various material arti-
facts (e.g., written works; physical objects; visuals such as
photographs; Vygotsky, 1978; Wertsch, 1991). Sometimes,
people learn from more knowledgeable others by observing
explicit modeling or demonstration (e.g., teachers, older sib-
lings, parents; Rogoff, 2003; Rogoff & Angelillo, 2002).
Other times learning occurs in collaborative, peer-to-peer
interactions or through communities of practice (Gutiérrez &
Rogoff, 2003; Lave, 1988). When learners collaborate, they
make their thinking visible to one another, thereby sharing
perspectives and strategies that may challenge and extend
each other’s thinking and understanding.
36 Policy Insights from the Behavioral and Brain Sciences 2(1)
Research-Based Principles of Instruction
Instruction that is consistent with the four principles of learn-
ing delineated above requires a shift in the learner’s role
from passive recipient of knowledge to active participant in
learning processes. The shift has been described as moving
from transmission models to knowledge construction or gen-
eration models (Scardamalia & Bereiter, 2006).
Principles for the Design of Instruction
We outline two overarching principles for the design of
instruction that will support the achievement of deep learn-
ing through knowledge construction. These principles sum-
marize extensive bodies of learning sciences research on the
cognitive, motivational, and sociocultural dimensions of
learning in multiple curricular domains (Pellegrino & Hilton,
2012). Teaching consistent with these principles makes it
more likely that students will develop organized systems of
knowledge and general principles that support transfer.
However, achieving deeper learning takes time and repeated
practice. Thus, instruction aligned with these principles
should begin in preschool and continue across all levels of
learning, from kindergarten through college and beyond.
The first overarching design principle is that learning
environments should promote agency and self-regulated
learning. Agency and a sense of self-confidence as a learner
are important predictors of achievement (Dweck & Master,
2009). This relationship may be due, in part, to learners
being more willing to engage and persist at challenging
tasks when they perceive themselves as competent, respon-
sible, and accountable for regulating their own learning
(Winne, 1995). Research (Wigfield & Eccles, 2000;
Wigfield, Tonks, & Klauda, 2009) shows that students learn
more deeply when they:
attribute their performance to effort rather than to
have the goal of mastering the material rather than the
goal of performing well or not performing poorly;
expect to succeed on a learning task and value the
believe that they are capable of achieving the task at
How such environments are promoted is addressed at
least in part by the second overarching design principle.
Second, contexts for learning should pose challenging
tasks and provide guidance and supports that make the task
manageable for learners. A variety of studies across language
arts, mathematics, and science indicate that the cognitive
demands of tasks have a systematic relationship to achieve-
ment: Those that make reasonable but high demands on think-
ing and reasoning show higher student achievement compared
with low-demand tasks (e.g., Newmann & Associates, 1996;
Stein & Lane, 1996). However, students cannot be expected to
solve challenging problems without appropriate guidance and
support. For example, there is no compelling evidence that
beginners deeply learn science concepts or processes simply
by freely exploring a science simulation or game. In contrast,
asking students to solve challenging problems while providing
specific social support and cognitive guidance does promote
deeper learning. Social support in the form of various types of
collaborative learning positively affects individual learning.
Examples are peer-assisted learning (Fuchs, Fuchs, Mathes, &
Simmons, 1997), problem-based learning (Hmelo-Silver,
2004), and team-based learning (Vaughn et al., 2013).
Cognitive guidance. Three major forms of cognitive guidance
are classroom discourse, learning resources, and formative
Classroom discourse: Orchestrating talk. Associated with
the transmission metaphor for teaching and learning is
monologic discourse, otherwise dubbed the I–R–E sequence
(Mehan, 1979): Teachers ask a question, they call on stu-
dents and evaluate if it is the desired response. If so, they ask
the next question. If not, they ask another student until some-
one provides the “right” response or they provide it them-
selves. Often the questions are “known answer” questions
and the process is actually designed to test whether students
have done the reading or memorized some set of facts. This
form of monologic discourse can be contrasted with dialogic
discourse (Wells, 1999), also referred to as instructional con-
versations (Goldenberg, 1992; Tharp & Gallimore, 1988)
and accountable talk (Michaels, O’Connor, & Resnick,
2008): Teachers pose questions that encourage elaborations,
questions, and explanations that require students to actively
engage with the material. Dialogic discussions increase
student talk and decrease teacher talk (Murphy, Wilkinson,
Soter, Hennessey, & Alexander, 2009). Students transform
content into their own words, connect it to their prior knowl-
edge, initiate topics, make claims and counterclaims, support
their claims with evidence, and pose new questions and puz-
zles that set the stage for further investigation. In literature
classes, dialogic discourse is associated with students going
beyond only comprehension of plot to adopting an interpre-
tive stance (Applebee, Langer, Nystrand, & Gamoran, 2003).
In both science and mathematics, having students discuss and
explain different ways they solved the “same” problem leads
to deeper conceptual understanding (O’Connor & Michaels,
Classroom discussion is also an effective vehicle for focus-
ing students on how they know—the processes they are using
to understand. Making these thinking processes explicit
through classroom discussion validates and normalizes the
process of thinking about thinking—metacognition (Lee,
2007; Schoenbach, Greenleaf, & Murphy, 2012). This
becomes particularly important when students experience
confusion or discrepancies between what their prior
Goldman and Pellegrino 37
knowledge led them to expect and the new information they
are trying to understand. Discussion about what does not make
sense as well as what does can provide opportunities for sup-
porting learning that do not arise when the classroom norm is
that you are supposed to know the answers to the questions.
Thus, important as the cognitive outcomes are, dialogic class-
room discussion also enhances agency in learning—the degree
to which students take up the intellectual work of sense mak-
ing (e.g., Nystrand & Gamoran, 1991).
Material learning resources. Guidance and support for
success with challenging tasks also depend on the learning
resources that are provided for students. “Knowledge-telling”
materials such as textbooks that present static compendia of
facts obscure the dynamic epistemological processes that pro-
duced the “facts” in the first place. A steady diet of such mate-
rials obscures the tentative nature of science, the disputed
nature of historical arguments, and the legitimacy of multiple
interpretations of the same poem, novel or song.
Deeper learning is fostered by learning resources that
include multiple and varied representations of concepts.
Research has shown that adding diagrams to a text or adding
animation to a narration that describes how a mechanical or
biological system works can increase students’ performance
on a subsequent problem-solving transfer test. In addition,
allowing students to use concrete objects to represent arith-
metic procedures has been shown to increase their perfor-
mance on transfer tests. This finding has been shown both in
classic studies in which bundles of sticks are used to repre-
sent two-column subtraction and in an interactive, computer-
based lesson in which students move a bunny along a number
line to represent addition and subtraction of numbers (Mayer,
Using examples and cases can help students see how a
general principle or method is relevant to a variety of situa-
tions and problems. One approach is a worked-out example,
in which a teacher models how to carry out a procedure—for
example, solving probability problems—while explaining it
step by step. Offering worked-out examples to students as
they begin to learn a new procedural skill can help them
develop deeper understanding of the skill. In particular,
deeper learning is facilitated when the problem is broken
down into conceptually meaningful steps that are clearly
explained; the explanations are gradually taken away as stu-
dents’ proficiency increases with practice (Renkl, 2011).
Ongoing use of formative assessment. The third form of
cognitive guidance is the ongoing use of assessment for
learning. Assessment for learning, often labeled formative
assessment, is distinguished from assessment of learning or
summative assessment. At its best, formative assessment is
closely tied to what is being taught—curriculum, and how it
is being taught—instruction. Formative assessment is a pro-
cess that is used throughout teaching and learning to moni-
tor students’ progress and adjust instruction when needed,
to continually improve student learning. It is different from
traditional “summative” assessments that measure what stu-
dents have learned at the end of a set period of time.
Research indicates that teachers’ use of formative assess-
ment can significantly enhance learning by providing better
and timely feedback to students about their learning (Black
& Wiliam, 1998). The process of continuously monitoring
students’ learning progress allows teachers to clarify learn-
ing goals, respond adaptively based on individual learning
patterns, and involve students in the process of peer- and
self-assessment. Feedback available through formative
assessment contributes to students’ monitoring their own
learning at a local level and can cue them to the need to
adjust their learning activities. Such uses of formative assess-
ment are grounded in research demonstrating that practice
with informative feedback is essential for deeper learning
and skill development, whereas practice without such feed-
back yields little learning (Shute, 2008).
Teachers can make use of formative information to plan,
revise, or evaluate instructional activities and strategies.
Materials for formative assessment are typically more infor-
mal than summative assessments (Heritage, 2010). For
example, many teachers survey student thinking and under-
standing with “exit slips.” These are short notes that typically
indicate what students “took away” from a classroom lesson
or activity and are handed to the teacher as students leave
Ongoing formative assessment sits within a broader set of
considerations regarding contemporary views of assessment.
We assess students to find out what they know and can do,
but assessments do not provide direct pipelines into students’
minds. Unlike height or weight, the mental representations
and processes educators care about are not outwardly visible.
Thus, an assessment is a tool for generating observable evi-
dence from which reasonable inferences can be drawn about
what students know. Central to this entire process are theo-
ries, models, and data on how students learn and what stu-
dents know as they develop competence.
The principles of learning and instruction discussed above
provide a means of aligning curriculum, instruction, and
assessment. Alignment, in this sense, means that the three
functions are directed toward the same ends and reinforce
one another: Assessment should measure what and how stu-
dents are actually being taught, and what is actually being
taught should parallel the curriculum one wants students to
master. Although this may seem straightforward, numerous
reports over the last two decades indicate how challenging it
is to achieve effective alignment among curriculum, instruc-
tion, and assessment (e.g., Bransford et al., 2000; Gordon
Commission on the Future of Assessment in Education,
2013; National Academy of Education, 2009a, 2009b, 2009c,
2009d; National Center on Education and the Economy,
38 Policy Insights from the Behavioral and Brain Sciences 2(1)
2007; Pellegrino, Chudowsky, & Glaser, 2001; Pellegrino &
Hilton, 2012). Many of these reports have also argued that
significant improvement is not a simple matter and will
require changes to many elements of the education system.
We outline the nature of such changes for curriculum and
instruction, assessment, and teacher education and profes-
Curriculum and Instruction
Further efforts are needed to create instructional materials
and strategies that can be implemented by teachers in their
classrooms and that can support teacher practice in ways that
help students develop transferable knowledge and skills.
Multiple stakeholder groups need to actively support the
development and implementation of curriculum and instruc-
tional programs that incorporate principles of learning and
research-based instructional methods such as those discussed
earlier in this article.
Despite research showing the value of ongoing formative
assessment by teachers, current educational policies focus on
summative assessments that measure mastery of limited
forms of content knowledge and often hold schools and dis-
tricts accountable for improving student scores on such
assessments. This is at odds with a focus on the development
of 21st-century knowledge and skills. However, recent pol-
icy developments in the United States suggest that both stan-
dards and assessments aligned with 21st-century skills are
being entertained. For example, the Common Core State
Standards in mathematics and English-language arts, the
Framework for K-12 Science Standards, and the Next
Generation Science Standards (Achieve, 2013) include many
design facets well aligned with conceptions of deeper learn-
ing and 21st-century competencies (Pellegrino & Hilton,
However, the extent to which the educational goals articu-
lated in these disciplinary standards and frameworks can be
realized in educational settings will be strongly influenced
by their inclusion in district, state, and national assessments.
Because educational policy remains focused on outcomes
derived from summative assessments that are part of account-
ability systems, teachers and administrators will focus
instruction on whatever is included in state assessments.
Thus, the new assessment systems adopted by states need to
give significant attention to the inclusion of tasks and situa-
tions that focus on deep disciplinary knowledge and skills
and that call upon a range of important 21st-century
A major challenge to attaining such a vision of assessment
design and use involves political and economic forces influ-
encing adoption. Traditionally, policymakers have favored
the use of standardized, on-demand, end-of-year tests for
purposes of accountability. Composed largely of selected
response items, these tests are relatively cheap to develop,
administer, and score; have sound psychometric properties;
and provide easily quantifiable and comparable scores for
assessing individuals and institutions. However, such stan-
dardized tests have not been conducive to measuring deeper
learning or 21st-century competencies. In the face of current
fiscal constraints at the federal and state levels, policymakers
may seek to minimize assessment costs by maintaining lower
cost, traditional test formats. They may resist incorporating
into their systems relatively more expensive, richer perfor-
mance- and curriculum-based assessments that may better
measure 21st-century competencies.
Teacher Education and Professional Development
Current systems and programs will require major changes if
they are to support teaching that encourages deeper learn-
ing. Changes will need to be made not only in the concep-
tions of what constitutes effective professional practice but
also in the purposes, structure, and organization of preser-
vice and professional learning opportunities (Darling-
Hammond, 2006; Garrick & Rhodes, 2000; Lampert, 2010;
Webster-Wright, 2009). In particular, disjointed teacher
learning opportunities need to be replaced with more inte-
grated continuums of teacher preparation, induction, sup-
port, and ongoing professional development, For example,
Windschitl (2009; see also Wilson, 2011) proposed that
teacher preparation programs should (a) center on a core
curriculum grounded in a substantial knowledge of child or
adolescent development, learning, and subject-specific ped-
agogy; (b) provide future teachers with extended opportuni-
ties to practice under the guidance of mentors for extended
periods of time; and (c) integrate practice experiences with
Research to date has identified other characteristics of
effective teacher preparation programs, including extensive
use of case study methods, teacher research, performance
assessments, and portfolio examinations that are used to
relate teachers’ learning to classroom practice (Darling-
Hammond, 1999). Wilson (2011) and others have noted that
one of the most promising practices for both induction and
professional development involves bringing teachers
together to analyze samples of student work, such as draw-
ings, explanations, or essays, or to observe videotaped class-
room dialogues for formative purposes. Working from
principled analyses of how the students are responding to the
instruction, the teachers can then change their instructional
More generally, policies and practices need to recognize
the need for teachers to engage in ongoing learning that con-
nects to their everyday lives in classrooms. That is, profes-
sional development needs to connect to the challenges that
teachers experience as they implement new teaching
approaches to cultivate students’ 21st-century skills. Most
Goldman and Pellegrino 39
critically, preservice teachers and in-service teachers need
opportunities to engage in the kinds of teaching and learning
environments envisioned for their students. Experiencing
instruction designed to support transfer will help them design
and implement such environments in their own classrooms.
Characteristics of such professional development include
ongoing, active, and coherent opportunities to adopt an
inquiry stance toward the teaching and learning process amid
a professional community of learners (Desimone, Porter,
Garet, Yoon, & Birman, 2002; Garet, Porter, Desimone,
Birman, & Yoon, 2001; Kubitskey & Fishman, 2006). A pol-
icy challenge is finding the time within the workday for such
activities and the recognition of these experiences as inherent
to the job.
In reflecting on the implications of the research on learn-
ing and instruction discussed in this article, it is worth
reminding ourselves that a more coherent system of curricu-
lum, instruction, and assessment, one guided by contempo-
rary theory and research on learning and knowing, could
potentially reduce disparities in educational attainment.
Doing so would allow a broader swathe of young people to
enjoy the fruits of workplace success, improved health, and
greater civic participation. However, important challenges
remain in the areas of research, practice, and policy for
attaining such outcomes. For educational interventions to
move beyond isolated promising examples and to flourish
more widely, larger systemic issues, many of them policy
driven, will need to be addressed. These include the design of
assessment systems, curricular and instructional resources
that incorporate research-based features such as those
described above, and more effective approaches to teacher
preparation and professional development.
The opinions expressed are those of the authors and do not repre-
sent the views of the funding agencies.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect
to the research, authorship, and/or publication of this article.
The author(s) disclosed receipt of the following financial support
for the research, authorship, and/or publication of this article: The
authors were supported in the writing of this article in part by grants
from the Institute of Education Sciences, U.S. Department of
Education (Grant R305F100007 and Grant R305C100024), and the
National Science Foundation (Award 1316874).
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