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Current perspectives on learning in classrooms make clear that students learn best when they are engaged in their learning and helped to develop rich conceptual understanding. These views on learning, often referred to as constructivist perspectives, propose that students actively and socially construct their knowledge. A challenge facing educators is how to create classrooms that support this learning.
Increasingly, educators have recognized the need to reconfigure classrooms as environments that encompass the complex individual and social processes necessary to promote understanding. For a learning environment to succeed, teachers need to change their traditional role of information delivery to effective scaffolding that supports students in integrating and applying ideas. In this type of learning environment, students also have new roles. They need to be more invested and responsible in their learning as they engage in authentic tasks, collaborate with classmates, and use technology for research and problem solving.
A number of K-12 programs have been developed that help teachers and students create ambitious learning environments. Examples include environments for elementary science and mathematics such as Rochel Gelman’s Preschool Pathways to Science, Douglas Clements’ Building Blocks mathematics environment for early elementary students, and Nancy Songer’s BioKIDS science environment for upper elementary classrooms. Secondary environments include Cognitive Tutors, a computer-based mathematics learning environment developed by researchers at Carnegie Mellon University; John Mergendoller and colleagues’ Problem-Based Economics; and Project-Based Science, developed by researchers at the University of Michigan. These environments for learning are carefully designed, theoretically framed, research-based programs that support all facets of the learning context. They represent ambitious pedagogy and strive for ambitious outcomes. Many include technology, such as computers or Web-based communication tools, either as a primary focus or as an important component. These environments for learning are changing the face of education.
In this research-paper, we examine how learning environments are engineered to support ambitious teaching and learning. We begin by considering the role of learning theory in the design of learning environments. We then examine the methods used to create and study environments. Next, we introduce features of learning environments and describe selected learning environments according to these features to illustrate how similar features are instantiated differently across environments. We close by discussing challenges and future directions in the design of environments for learning.
Learning Theory and Learning Environments
In contrast to previous views that emphasized learning as a process of transferring information from teachers or texts to learners, new views emphasize that learners are active constructors of knowledge. Accordingly, learning occurs through a constructive process in which students modify and refine what they know as they explore and try to make sense of the world around them. Students possess prior knowledge that they use to interpret learning experiences and construct new knowledge.
There are various formulations of constructivism and they explain different aspects of learning. Under this broad constructivist umbrella are two major perspectives on human learning. The first is cognitive in nature and focuses on individual thinking and learning. The second is social in nature and focuses on social interaction and the role of interactions within social contexts. Both perspectives are central in informing the design of new environments.
The cognitive perspective emphasizes the role of the individual in learning and is concerned with how complex information is handled mentally by learners, including how learners remember information, relate new information to prior knowledge to build schemas or knowledge networks that organize ideas, and develop understanding. Research on cognition suggests that prior knowledge and its organization plays a considerable role in learning and performance. For example, cognitive research provides insight into the skills and knowledge that underlie expert and novice performance. This research indicates that experts and novices differ in the amount and organization of knowledge and in their ability to apply knowledge to solve problems, compre-hend text, and respond to situations. Simply put, experts and novices differ in their cognitive resources, especially strategies for learning and performing tasks. Experts from all disciplines draw from a richly structured information base and are more likely to recognize meaningful patterns of information when problem solving. Experts know their disciplines thoroughly and their understanding of subject matter allows them to see patterns, identify relevant information, and notice inconsistencies or discrepancies that are not apparent to novices.
Research on how people learn and acquire expertise in various disciplines has given rise to notions about how to help students learn specific subject area content. Most students are novices in the content areas of reading, writing, mathematics, science, and social studies. They think differently from adult experts and draw from an information base that is often comprised of informal ideas that they have acquired through their everyday experiences. When working on mathematics problems, for instance, students will often apply thinking and reasoning strategies that are qualitatively different from what mathematics educators expect. This is because students draw from a limited set of cognitive resources to make sense of school mathematics. They are unfamiliar with the practices of mathematicians and the strategies that expert mathematicians use to solve problems and generate knowledge.
Many new environments for learning are designed to help students develop competence in content areas. Informed by studies on how novices think and what misconceptions they have, these environments strive to move students toward sophisticated ways of understanding that are characteristic of experts. Some of these environments provide tutoring and guidance in the use of strategies and thinking processes typical of experts. An example of this type of environment is Jack Mostow and colleagues’ computer-based reading environment, Literacy Innovation that Speech Technology Enables (LISTEN). LISTEN uses intelligent instructional software that provides specific hierarchical tasks and assistance to help elementary school students develop reading competence. In LISTEN, reading is guided and supported in one-on-one interactions between the individual student and computer. The computer acts as an expert tutor. It displays stories and uses speech recognition software to listen to children read aloud. Students wear headsets with microphones attached as they read aloud stories matched to their estimated reading levels. LISTEN software assigns stories to students based on their individual performance, monitors students’ reading, and provides feedback and hints. The software is based upon a careful analysis of reading skills and modeled after expert reading teachers.
Cognitive theory informs how to help students accomplish tasks and engage in specific thinking processes. The cognitive perspective has its roots in the work of Swiss psychologist Jean Piaget who focused on the mental structures underlying knowledge; he studied how children advance from novice to expert ways of thinking by constructing increasingly sophisticated knowledge. The body of research on human cognition has provided critical insight into how students think and reason about how the world works, how experts acquire their expertise, and the cognitive demands of thinking and problem solving in a range of situations and domains.
The social perspective is concerned with how learning is shaped by participation in activity and interactions within social contexts. This view draws from the work of Russian psychologist Lev Vygotsky who argued that all learning originates in, and is a product of, the settings in which learners navigate. This means that knowledge is contextualized, and learners build knowledge and deepen their understanding through observations and interactions with the physical world as well as discourse and participation in activities with others. In this sense, learning is regarded as inherently social and the setting for learning— consisting of materials, activities, learners, and social interactions among learners and teachers—shapes the knowledge that is produced.
Vygotsky’s ideas are prominent in the work of designers of learning environments. One of his most influential ideas is that meaningful learning occurs when learners are engaged in rich social activity in which they communicate, collaborate, and form a learning community. In a classroom learning community, teachers and students engage collectively in learning that produces shared understandings. Such a community consists of people collaborating on problems or projects, relying on one another for assistance when needed, and sharing, discussing, and debating ideas. Based on just such a notion of community, Ann Brown and Joseph Campione developed Fostering Communities of Learners (FCL), an environment for grades one through eight that fosters learning by developing group knowledge about a topic. In FCL, students and teacher select a topic of interest and then break into research groups that focus on relevant aspects of the topic. Research groups pursue different but related questions and then explain their work to the other groups. Collectively, the groups then synthesize the information to form a comprehensive understanding of the topic. To showcase their new understandings, students produce group reports, poster displays, and presentations or demonstrations. A feature of FCL is the jigsaw group, a learning group that contains a member representing each initial research group. In this new group, each jigsaw member is responsible for teaching their research information to everyone else. Thus, each member represents a piece of the puzzle that provides important and different knowledge for understanding the topic.
An important idea that has emerged from the work on the role of community in learning is the notion of communities of practice. Introduced by Jean Lave and Etienne Wenger (1991), a community of practice describes a situation in which robust knowledge and understandings are socially constructed though talk, activity, and interaction in an authentic, real-world context. In classrooms, this means having students communicate and engage in activities that reflect the discipline under study. For instance, establishing a community of scientific practice requires that learners participate in activities similar to that of scientists. This entails engaging in scientific inquiry much like scientists do, but in ways that are appropriate and meaningful for students. Such an approach actively involves students in scientific practices such as conducting investigations, making observations, gathering and analyzing data, and reporting findings. A benefit of situating science learning in an authentic context is that it provides a meaningful and motivating backdrop for introducing students to the conventional language, practices, tools, and values of the scientific community.
Another influential idea from Vygotsky is the critical importance of supporting learners to accomplish tasks that they otherwise cannot accomplish on their own. Vygotsky coined the phrase zone of proximal development to represent the capacity that learners have to perform tasks with the help of others that they would not be able to perform on their own. Helping learners advance by moving through a zone of proximal development requires support. Theorists refer to this specialized support as scaffolding. Instructional scaffolding is the support provided to a learner or groups of learners by a more knowledgeable person, such as a teacher, to help advance learning. In recent years, the notion of scaffolding has been expanded to include learning technologies, such as computer software, that help learners participate in activities that are just beyond their abilities. Scaffolding can help structure a learning task, guide learners through a task, and support thinking, planning, and performance. In a classroom community of practice, scaffolding is essential for aiding learners in developing disciplinary skills and knowledge.
An example of an environment that incorporates extensive scaffolding in a community of practice is Guided Inquiry supporting Multiple Literacies (GIsML), developed by Anne Marie Palincsar and Shirley Magnusson. GIsML is a science environment for elementary classrooms that promotes student learning through guided inquiry. The term guided refers to the teacher’s role in scaffolding the development of students’ science knowledge and reasoning as they proceed through cycles of inquiry. In GIsML, students work in pairs or small groups to conduct hands-on investigations in which they collect and analyze data and then report findings to the class. The role of the teacher is to support student thinking through key issues of investigation, such as specific questions to drive the investigation and the design of methods. When it is time to report findings, the teacher assists and guides students in making claims and supporting those claims with evidence (Palincsar & Magnusson, 2001). This process engages students in using the tools, language, and ways of reasoning that are characteristic of scientific inquiry.
From the social perspective, learning depends on the experience and knowledge of students, the knowledge and skills of the teacher, the design of tasks, the tools that are available, and the community that is developed. Furthermore, these factors are interdependent; a change in one will influence the effect of others on learning. Environments developed along social perspective lines include tasks that are typical of those used in the disciplines, instructional scaffolding by more knowledgeable others, tool use that supports learning, and development of learning communities that engage students in practices representative of the subject under study.
Relevance of Theory for Creating Environments
Theory serves as a blueprint that helps designers envision the instructional landscape for building environments. By starting with theory, designers are able to anticipate how to support and organize learning. This anticipatory thinking is important for articulating the how and why of instruction. The how is what teachers and students will do during instruction or, more broadly, how the environment will work to promote learning. When designers start with a theoretical framework, they can envision the kinds of classroom activities and interactions necessary to motivate and sustain learning. The why provides explanatory power or insight into why designed instructional activities and interactions are productive for learning. Theory explains why particular instructional experiences, when structured and enacted in particular ways, are more or less likely to result in learning. For example, social constructivist theory provides direct guidance for how to support students as they engage in inquiry through techniques that scaffold thinking, planning, and performance in the inquiry process. Scaffolding is important because it guides learners through a task, reducing confusion and increasing the likelihood that students will attend to the important ideas.
Learning environments based on constructivist theories often incorporate components of both cognitive and social views. Increasingly, designers recognize that both aspects need to be addressed when developing learning environments. The Cognitive Tutors environment developed by John Anderson and colleagues at Carnegie Mellon University is a computer-based learning environment for secondary school mathematics classrooms. Cognitive Tutors is based on a cognitive theory of learning and performance that describes how individual learners acquire and learn to use mathematical knowledge. Cognitive Tutors software provides tutoring by presenting problem-solving situations to students individually, monitoring students’ solution steps, and providing feedback. The environment is centrally focused on individual cognition, but the designers also attend to the social context in which Cognitive Tutors is used. They consider how individual tutor use can be integrated with classroom instruction and collaborative problem-solving experiences. By joining cognitive and social perspectives, they are able to make Cognitive Tutors comprehensive and usable for teachers and students.
Designing and Studying Learning Environments
To engineer learning environments, designers need to have a deep understanding about the reality of classrooms and schools. They need expertise in how people learn and the conditions that give rise to learning. They also need to understand academic standards and disciplinary content, the types of tasks and instructional materials that can help students attain learning goals, the role of the teacher in orchestrating instruction, and how to assess learning. Many learning environments feature technology as a tool for learning. To effectively design for learning with technology, designers need to grasp the benefits and challenges of using technologies in classrooms. Finally, designers need to work well with others because the building of learning environments is often too complex for any one designer.
Designers typically work in interdisciplinary teams, with members drawn from education, psychology, computer science, and cognitive sciences. These professionals are centrally concerned with how people learn and how to configure environments to optimally support learning. Many are part of an emerging interdisciplinary field known as the learning sciences, which is comprised of researchers who study teaching and learning in a variety of settings, including school classrooms. The goal of the learning sciences is to better understand the cognitive and social processes that promote learning and to use this knowledge to create learning environments that help teachers teach more effectively and students learn more deeply. A hallmark of the learning sciences is collaboration among researchers with diverse professional backgrounds and ways of thinking to envision and design the schools and classrooms of the future.
Design teams often include disciplinary specialists from mathematics, the sciences, or the social sciences as well as teachers who can help designers think through how materials can be enacted and sustained in real-world classrooms. Because all aspects of an environment are designed, bringing together experts with a range of skills and perspectives is essential. A team working on the design of a middle school mathematics learning environment, for instance, might include an educational psychologist who understands how children think and reason mathematically and the kinds of instructional practices that can best support mathematics learning, a mathematician familiar with the mathematics content and standards, a literacy specialist who can guide the development of text materials for math learning, an expert on educational technology who can design computer tools to support learning, and a mathematics teacher who can provide insight into how teachers might best be supported in enacting the environment. Another key person is a mathematics education researcher who can study how the newly designed environment is enacted by teachers and students in classrooms and the effect of the environment on math learning.
The Design Cycle
The designing and building of learning environments is an iterative process that proceeds through cycles of design, implementation, and evaluation. The first step in the cycle, design, is the process of going from a set of ideas derived from theory to a usable, workable, instructional road map for enacting the environment. For example, designers of the learning environment Project-Based Science (PBS) draw from social constructivist theory to inform the design of the environment. The key social constructivist ideas include active construction, situated learning, and social interaction, among others. These theoretical ideas serve as design principles that provide insight into the kinds of classroom activities necessary to support learning. The first principle, active construction, emphasizes the importance of having students actively construct their knowledge by participating in real-world science activities. The second principle, situated learning, suggests that students need to work in an authentic context that mirrors practices in the scientific community. This means providing a context in which students can use and explore scientific practices and apply scientific ideas so they can more readily see the relevance of their participation in activities. Social interaction, the third principle, addresses the need for students to work with one another to conduct investigations and to discuss their ideas and findings. Collaboration helps students build shared understandings of scientific ideas and the nature of science as they engage in discourse with their classmates and teacher. These principles define clearly specified activities within the PBS environment. Design principles are pathways from theory to practice; they are starting points for envisioning how a learning environment might come together.
Early in the design cycle, designers face uncertainty because the initial design of an environment is really only a tentative plan. Instructional sequences and activities are sketched; instructional materials such as a teaching guide and student workbooks are drafted; and technology tools, if integral to the environment, are initially developed. At this point, the hard work is just beginning as designers then move their design work to the complex classroom setting.
In implementation, the second step, the newly designed environment is enacted in a small number of classrooms. Implementation is where teachers and students bring an environment to life and often times, this is where tensions between the intended and enacted environment emerge. The intended environment is the ideal environment envisioned by designers; the enacted environment is what the environment actually looks like and how it works in the hands and minds of teachers and students in everyday classrooms. Implementation is a moment of truth for designers as they get a first glimpse into the practical realities of trying to create an effective environment for learning. Perhaps not surprisingly, issues often arise in early implementation efforts. This is where the third step, evaluation, comes into play.
Evaluation involves the careful study of the implementation. This is a critical step. By studying how an environment is enacted, designers get comprehensive accounts of what works in practice and what does not. This information is used for revising features that do not work as anticipated. For example, in early implementations of PBS, designers found that students were unaccustomed to working in groups and discussing ideas. Students were not used to learning from their own inquiries and had difficulty engaging in productive discussions with one another and the teacher. These issues required PBS designers to rethink how students could be more effectively supported in collaborative inquiry. PBS designers added teacher supports to the instructional materials that included a range of teaching strategies for fostering scientific inquiry and examples of questions and prompts to support discourse. Scaffolds from teachers, peers, and technology were incorporated to guide students through learning activities. Once these and other modifications were made, the PBS environment was implemented and studied again, using data collected from the implementation to inform the next round of design and implementation. After several cycles of design, implementation, and evaluation, the result was a research-based innovation that had been extensively field-tested for usability and effect on student learning and motivation.
The approach to designing environments described here is often referred to as design-based research. Design-based research can be traced back to the work of Ann Brown who was one of the first education researchers to promote the idea of designing, enacting, and studying innovations such as learning environments within everyday school settings. According to Brown, researchers can gain important insights about the conditions of learning by bringing theory into practical educational contexts (Brown, 1992). Design-based research enables designers to test whether their theoretical assumptions are usable in the real world. As designers follow a design-based research cycle, they generate knowledge that applies to classroom practice and leads to stronger connections between theory and practice. This work also contributes to a richer understanding of the guiding learning theories. Well done design-based research, then, is likely to yield theoretical and practical insights necessary to advance knowledge by informing theory, design principles, or practice recommendations.
Scaling Learning Environments
Once learning environments have been field-tested in a small number of settings, the challenge is to test their usability in a wide variety of circumstances. To scale up means to take a learning environment that is successful in a few settings and expand the implementation beyond those classrooms and teachers who participated in the design-based research cycle. This involves modifying a learning environment for widespread use with many teachers and students throughout a district, or across districts in a state, or in multiple schools and districts around the country.
When designers prepare to go to scale, their focus shifts from considering an environment’s implementation within one or several classrooms to implementation in the larger context of schools and school systems. This kind of design work is substantially different and requires designers to attend to professional development for teachers, consider school and district resources for implementation, redesign technology to work within the existing infrastructure of schools, and modify materials and activities for effective use by a wide range of teachers and students. A central goal is to modify the environment so that it is usable and sustainable given school realities, yet provides opportunities and supports for teachers and students to enact innovative and ambitious instruction. To achieve this goal, designers supply teachers with highly specified and developed materials that are critical for ensuring success. Highly specified and developed materials provide teachers with a model of how to enact an environment as well as resources and strategies to promote learning. Educational researchers Deborah Ball and David Cohen coined the term specified and developed to emphasize that materials should specify a clear theoretical stance, learning goals, intended teaching practices, and guidelines for enactment (Ball & Cohen, 1996). Furthermore, materials should include resources for teachers and students to use, such as student workbooks and readers, assessments, teacher manuals, and professional development materials that provide examples of ways to enact an environment.
Scaling up also entails modifying environments so that they align with important learning goals found in district, state, and national standards. This is another essential way that designers make their environments usable and sustainable for schools and districts. School administrators and teachers are unlikely to adopt an innovative environment if it does not emphasize content and instructional practice recommendations made in state and national standards documents. Additionally, designers are increasingly finding that they need to show that their environments improve learning as measured by high-stakes tests. For this reason, many discipline-based learning environments emphasize recommendations made in state and national standards documents and include assessments that are aligned with important learning goals.
Features of Environments for Learning
Building a comprehensive learning environment requires that designers attend to the major features of the learning setting. Features are basic aspects of learning environments that influence student learning and performance. Major features include goals, tasks, instructional materials, social organization, teacher, technology, and assessment.
The goals of learning environments can be academic, social, metacognitive, or developmental. A learning environment might encompass all four types of goals or only one or two. Academic goals focus on disciplinary content and often include learning about disciplinary practices and norms. Goals can also be social, such as the interpersonal goal of learning to work cooperatively, the motivational goal of improving attitudes and promoting interest, and the communicative goal of learning the discourse modes of different disciplines. A third type of goal, metacognitive, promotes a disposition for thinking and reasoning. These are mental habits such as persistence and posing questions that support self-directed or self-regulated learning. Developmental goals tend to focus on moving students forward in terms of knowledge and expertise.
Tasks are specific activities that students perform to learn academic content and skills. Learning environments usually emphasize authentic tasks that reflect the work of experts and require students to use their knowledge and skills in real-world situations. Authenticity in a social studies learning environment, for instance, might mean engaging students in tasks that are similar to what historians do in ways that are appropriate and meaningful for students. This might entail students researching an historical topic of interest and then presenting information in a historically correct manner, using terms and making arguments and explanations as historians would.
Learning environments often provide materials to support and guide enactment. Teachers have a unique position in enactment because their use of materials shapes the potential of the environment for enhancing student learning. Increasingly, designers recognize teachers’ important role and develop materials that are designed to be educative for teachers. The materials provide targeted assistance to teachers to support their learning so that they, in turn, can better support student learning. Environments that provide educative materials might include a comprehensive guide for enactment with rationales for activities; background on content; guidance in how to use materials and technology with students; examples of questions and prompts to support discourse; and teaching strategies for fostering inquiry, scaffolding student learning, or for building communities of practice. When materials are not extensively developed and teachers play a central role in enacting the learning environment, teachers need to have considerable expertise to meet the goals set by designers.
Many learning environments require that students actively engage in learning, communicate their ideas, and learn from one another. These environments promote a social context that allows students to feel comfortable asking questions, seeking help, and responding to questions. Students collaborate and communicate around authentic tasks and investigations, and they participate in a community of practice that mirrors the discipline under study. Some learning environments are linked to communities that extend beyond the classroom. They might support community participation by encouraging students to pre-sent findings to audiences in the community, such as local interest groups and students in other classes. Students’ community reach might be further extended to other schools and communities by publishing on the Internet. Technology-based learning environments, for instance, often connect students with other students across school sites to collect, share, and interpret data.
The success of any learning environment depends on the teacher, even though the role of the teacher can vary considerably across environments. In some learning environments, teachers play a central role. Their instructional efforts to scaffold student learning, orchestrate group problem solving and investigation, facilitate discussions, and assess understanding are critical. In others, the teacher’s position in enacting the learning environment is less central to helping students meet goals. This is the case for computer-based tutoring environments where the technology provides a high level of guidance and is the major influence on student learning. A challenge for teachers in enacting any type of environment is ensuring that the way the environment is enacted matches the theoretical stance of the environment. This requires that teachers have a firm understanding of the learning theory and goals underlying an environment.
Learning environments use technologies for many purposes. Students in many innovative learning environments are actively involved in using technology tools, such as Internet search engines for research, e-mail or instant messaging for communicating with peers and experts, and visualization or simulation software to create and study models. Some designers place technology at the core of their learning environments and provide custom-designed software tools to support students’ knowledge building and knowledge integration. Some of these environments are designed to foster collaborative inquiry. Other computer-based environments are designed for individual work. Still other learning environments may use technologies although they are not central to the enactment of the environment. Increasingly, teachers need technology expertise because they are primarily responsible for troubleshooting and using technology tools to leverage learning.
Most learning environments include or recommend several types of assessments to evaluate students’ learning. Individual and group portfolios, student reports and presentations, and traditional tests are characteristic of many environments. In some, students design and build artifacts that showcase their learning. Assessments in discipline-based learning environments typically target content knowledge, reasoning skills, and students’ understanding of the nature of the discipline. Some environments might also assess students’ motivation, including interest, feelings of efficacy, and goals for learning.
Although many learning environments share most, if not all, of the features described above, they differ in the emphasis they place on particular features and how they instantiate them. For instance, technology is the core in some environments; in others it is secondary or not present at all. Another difference is that content might be addressed through problem-based tasks representative of a particular discipline in some environments, and project-based tasks may be used in others. Learning environments also encompass different types of social organization and differ in their overarching goals. Features of any particular environment are presumed to work together to foster learning in an educational setting. This is because the goals and instantiations of each feature of a learning environment derive from the same underlying theoretical ideas about learning.
Examples of Environments for Learning
This section presents summaries of two learning environments designed to support ambitious teaching and learning. Each environment has a strong theoretical foundation: one environment is grounded in the social perspective, the other in the cognitive perspective. Each offers a different way of bringing theory into design and practice. Brief descriptions are included of goals, the types of tasks and instructional materials used to reach the goals, social organization of the environments, the role of the teacher, the use of technology, and how learning is assessed.
In a Project-Based Science (PBS) learning environment, middle school students engage in real-world investigations in ways that are similar to how scientists conduct inquiry. Developed by Joseph Krajcik, Ronald Marx, Phyllis Blumenfeld, Elliot Soloway, and others at the University of Michigan, PBS promotes instruction and learning through carefully designed and developed inquiry projects. Projects are framed around a driving question that guides instruction and serves to organize students’ investigations. Driving questions are crafted to encompass science content and to connect with students’ interests and curiosities about the world. For instance, students learn about microbiology and infectious diseases by engaging in inquiry tasks framed around the question, How can good friends make me sick? In this project, students explore how a communicable disease spreads through a community. A central goal of the PBS environment is to have students engage in extended inquiry to understand science content and practices that are outlined in state and national standards. Another important goal is to contribute to students’ attitudes toward science.
The theoretical foundation of PBS draws from a social constructivist perspective that emphasizes active, situated, and collaborative learning. In PBS classrooms, students are provided with a meaningful context in which to explore the driving question over a sustained period of time. For example, the driving question, Why do I need to wear a helmet when I ride my bike? situates the science topic of force and motion in an issue that is likely to be of interest to students. As students become involved in the project, they collaborate with peers and with their teacher to ask and explore smaller questions that contribute to understanding the driving question. They conduct investigations, weigh evidence, write explanations, and discuss and present findings. As they pursue answers to the driving question, they participate in situated activities that help them learn scientific content and practices relevant and necessary to construct a meaningful response.
Students in PBS classrooms produce artifacts, or products, that showcase their learning. For example, students create models that represent scientific phenomena, develop concept maps that illustrate their understanding of complex ideas, and prepare presentations and reports that explain their findings and the evidence for those findings. Teachers often use students’ artifacts for assessment purposes in combination with traditional tests. Additionally, surveys are used to explore students’ perceptions of the learning environment and its influence on attitudes toward science and motivation to learn science.
PBS uses technology tools and resources such as Web-based databases, model-building software, handheld technologies, and the Internet for interactive inquiry. Computers and other technologies extend students’ thinking by providing access to information and opportunities to communicate, explore phenomena, and build scientifically accurate models that represent phenomena.
Teachers play a central role in PBS classrooms by orchestrating instruction so that students develop the important skills and stance necessary for engaging in inquiry. They provide instructional scaffolds that help students engage in productive discussions with one another and their teacher, plan and carry out investigations, analyze data, and present findings. Highly specified and developed teacher materials that help create and sustain a PBS environment include detailed lesson descriptions and supports that clearly identify learning goals; examples of students’ likely ideas; questions and tasks for guiding and monitoring student understanding; instructional strategies to support students as they engage in inquiry; and key ideas that teachers can emphasize in helping students make sense of their inquiry experiences.
Technology is the centerpiece of the Cognitive Tutors learning environment developed by John Anderson, Albert Corbett, Kenneth Koedinger, and others at Carnegie Mellon University. Cognitive Tutors is a computer-based environment for high school mathematics classrooms that uses intelligent instructional software to teach students such topics as algebra, geometry, and integrated math. Cognitive Tutors software provides one-to-one tutoring by presenting problem-solving situations to students individually and monitoring and guiding students as they work through the tasks. The central goal of the environment is to raise mathematics achievement by developing students’ math problem-solving abilities and deepening their math knowledge.
Cognitive Tutors is based on a cognitive theory of learning and performance that proposes students learn best by doing rather than watching or listening. The software presents real-world problem-solving situations that require students to apply math knowledge and practice specific math skills. For instance, the algebra tutor emphasizes algebraic reasoning through such problems as comparing car rental options, engineering a highway, and organizing to make and sell T-shirts. As students engage in the problem-solving tasks, they also become adept at using and interpreting mathematical representations such as tables, graphs, and symbolic expressions.
Cognitive Tutors software monitors students’ problemsolving performance by following students as they work through a task and providing feedback. Each Cognitive Tutor employs a cognitive model that represents the skills and strategies required to complete each task. When a student makes an error, the tutor initially displays an error message and provides on-demand hints; multiple hints are available for each step of a problem to ensure that the correct path to a solution is followed. An error message serves as a prompt that allows a student to correct errors without assistance. Multiple hints allow the student to succeed with minimum assistance. The tutor provides tailored practice on math skills until students reach mastery performance levels. Once a student reaches mastery on a particular math skill, the tutor stops presenting new problems for that skill.
The Cognitive Tutors environment integrates individual tutor use with classroom instruction that includes collaborative problem-solving activities and class discussions. The teacher facilitates classroom instruction and circulates and assists students as they interact with the tutor. The teacher needs to have subject matter knowledge, be familiar with tutor software (including how to troubleshoot technical issues), and be comfortable facilitating collaborative problem solving.
Instructional materials that help teachers enact the environment accompany the software. The materials include a problem-based textbook for students and a teacher’s guide that consists of assignments, assessments, teaching suggestions, and classroom management techniques. The purpose of the textbook and classroom activities is to extend the development of concepts emphasized in the software.
Assessment is an integral part of the Cognitive Tutors environment. Cognitive Tutors software includes step-by-step assessments of students’ mathematical skills and provides a skill report to identify math skill levels and progress for each student. Assessments provided in the teacher’s materials include exams, quizzes, and rubrics for grading class presentations. Teachers are also encouraged to create and share their own assessments in an online teacher community.
Challenges and Future Directions
Designing an environment for learning requires significant time, effort, and resources. A design-based research team will typically work for three or more years to develop, modify, and refine a learning environment. Designers work closely with teachers in classrooms to observe how an enactment unfolds and to study how the environment enhances learning. The iterative approach enables a design team to modify their environment in a real-world setting, carefully observe as teachers introduce the refinements, and then make further adjustments as needed. In fact, designers may follow teachers’ classes over several years to gain insight and guidance into optimally supported learning.
This approach requires long-term partnerships between educational researchers, school administrators, and teachers. It requires that schools change their culture and routines to support innovative practice and that designers find creative ways to help teachers reconfigure their classrooms as environments for ambitious learning. It is clear that contemporary learning environments represent a considerable departure from the type of classroom experience with which most teachers, students, administrators, and parents are familiar. Learning environments, then, pose special challenges that require considerable knowledge, skill, and foresight to address.
The present work on learning environments marks efforts to design the schools of the future. These first generation environments provide a glimpse of the potential of this work for transforming classrooms. Students in these environments have been introduced to new ways of learning. They solve meaningful problems, collaborate with others, use cutting-edge technology, and create artifacts that showcase their learning. They gain important knowledge and skills, appreciation for disciplinary practices, and new dispositions for learning. For designers, these environments provide a rich context for interdisciplinary research. As this work continues, we will gain a better understanding of how instructional interactions shape learning and how effective environments can be designed.
A necessary next step is to design environments for a wider range of school contexts. This is important for scaling up. Schools are becoming more linguistically and culturally diverse every year, and carefully designed environments that support students from different backgrounds is essential. Similarly, designers need to examine how learning environments can be created or adapted for inclusiveness of special needs learners. There is evidence that learning environments can help address diversity because they offer a variety of instructional techniques, activities, technology tools, and different ways for students to participate.
New knowledge about how people learn has enriched understanding of how to create successful conditions for learning. Learning environments represent an expanded view of teaching and learning that encompasses the social context and recognizes the complexity of instruction. Over the next decade, new learning environments will emerge that may prove critical for preparing students for the 21st century. This research-paper examined the building of learning environments in schools and classrooms. It is important to note that many others are being designed for informal learning settings such as museums, science centers, and afterschool programs.
Learning environments represent ambitious pedagogy and strive for ambitious outcomes. The designers of these environments are committed to transforming schools and classrooms into dynamic places where teachers teach more effectively and students learn more deeply. Design-based research is a new approach that strengthens the bridge between learning theory and educational practice and advances our understanding of both. Design work is challenging and complex, requiring collaborations among educational researchers, teachers, disciplinary experts, school leaders, and others. The work is vital for improving schools to meet the needs of our rapidly changing knowledge-based and technological society. The schools of the future are on the horizon, and the interdisciplinary efforts of designers promise to create innovative environments that will serve as a foundation for the next generation of schools.
- Ball, D. L., & Cohen, D. K. (1996). Reform by the book: What is—or might be—the role of curriculum materials in teacher learning and instructional reform? Educational Researcher, 25(9), 6-8.
- Blumenfeld, P., Marx, R. W., & Harris, C. J. (2006). Learning environments. In W. Damon, R. M. Lerner, K. A. Renninger, & I. E. Sigel (Eds.) Handbook of child psychology, 6th edition, volume 4: Child psychology in practice (pp. 297-342).
- Hoboken, NJ: Wiley. Bransford, J. D., Brown, A. L., & Cocking, R. R. (Eds.). (2000). How people learn: Brain, mind, experience, and school (Expanded Ed.). Washington, DC: National Academies Press.
- Brown, A. L. (1992). Design experiments: Theoretical and methodological challenges in creating complex interventions in classroom settings. Journal of the Learning Sciences, 2, 141-178.
- Brown, A. L., & Campione, J. C. (1994). Guided discovery in a community of learners. In K. McGilly (Ed.), Classroom lessons: Integrating cognitive theory and classroom practice (pp. 229-270). Cambridge, MA: MIT Press.
- Corbett, A. T., Koedinger, K. R., & Hadley, W. S. (2001). Cognitive Tutors: From the research classroom to all classrooms. In P. Goodman (Ed.), Technology enhanced learning: Opportunities for change (pp. 235-263). Mahwah, NJ: Lawrence Erlbaum Associates.
- Davis, E. A., & Krajcik, J. S. (2005). Designing educative curriculum materials to promote teacher learning. Educational Researcher, 34(3), 3-14.
- Design-Based Research (2003). Design-based research: An emerging paradigm for educational inquiry.
- Educational Researcher, 32(1), 5-8. Gelman, R., & Brenneman, K. (2004). Science learning pathways for young children. Early Childhood Research Quarterly, 19, 150-158.
- Krajcik, J., & Blumenfeld, P. (2006). Project-based learning. In R. K. Saywer (Ed.), Cambridge handbook of the learning sciences (pp. 317-334). New York: Cambridge University Press.
- Lave, J., & Wenger, E. (1991). Situated learning: Legitimate peripheral participation. New York: Cambridge University Press.
- Maxwell, N., Bellisimo, Y., & Mergendoller, J. (2001). Problem-based learning: Modifying the medical school model for teaching high school economics. Social Studies, 92, 73-78.
- Palincsar, A. S., & Magnusson, S. J. (2001). The interplay of first-hand and second-hand investigations to model and support the development of scientific knowledge and reasoning. In S. Carver & D. Klahr (Eds.), Cognition and instruction: Twenty-five years of progress (pp. 151-193). Mahwah, NJ: Lawrence Erlbaum Associates.
- Sarama, J., & Clements, D. H. (2004). Building blocks for early childhood mathematics. Early Childhood Research Quarterly, 19, 181-189.
- Saywer, R. K. (Ed.). (2006). Cambridge handbook of the learning sciences. New York: Cambridge University Press.
- Singer, J., Marx, R. W., Krajcik, J., & Chambers, J. C. (2000). Constructing extended inquiry projects: Curriculum materials for science education reform. Educational Psychologist, 35(3), 165-178.
- Songer, N. B. (2006). BioKIDS: An animated conversation on the development of curricular activity structures for inquiry science. In R. K. Sawyer (Ed.), Cambridge handbook of the learning sciences (pp. 355-369). New York: Cambridge University Press.
- Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Cambridge, MA: Harvard University Press.
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