This chapter addresses the second question in the study charge by analyzing how deeper learning and 21st century skills relate to academic skills and content in the disciplines of reading, mathematics, and science,1 especially as the content and skill goals are described in the Common Core State Standards for English language arts and mathematics and NRC’s A Framework for K-12 Science Education (hereafter referred to as the NRC science framework; National Research Council, 2012).
The existing Common Core State Standards, as well as the Next Generation Science Standards that are under development in 2012 based on the NRC science framework (National Research Council, 2012), are expected to strongly influence teaching and learning in the three disciplines, including efforts to support deeper learning and development of 21st century skills. The English language arts and mathematics standards were developed by state education leaders, through their membership in the National Governors Association and the Council of Chief State School Officers, and have been adopted by nearly all (45) states, along with 2 territories and the District of Columbia. The Next Generation Science Standards are being developed through a similar process and are also likely to be widely adopted by the states.
1In keeping with its charge, the committee explored deeper learning in the individual disciplines of reading, mathematics, and science. It only briefly addressed integrated approaches to teaching across disciplines (see Box 5-2), as this topic lay outside its charge. A separate NRC committee has been charged to review the relevant research and develop a research agenda for integrated teaching of science, technology, engineering, and mathematics (STEM).
The first, second, and third sections of the chapter focus, respectively, on English language arts, mathematics, and science and engineering. For each discipline we
- discuss how “deeper learning” has been characterized in the discipline, including issues and controversies that have played out over time;
- describe the relevant parts of the Common Core State Standards or the NRC science framework (along with selected other reports outlining expectations for student learning) in light of the historical context; and
- analyze how the new standards and framework map to our characterization of deeper learning and to the clusters of 21st century skills defined in Chapter 2.
In the final section of the chapter, we present conclusions and recommendations based on a broad look across all three disciplines. In this broad look, we compare the expectations included in the Common Core State Standards and the NRC science framework with deeper learning (as characterized within each discipline) and 21st century skills.
ENGLISH LANGUAGE ARTS
The Context: A History of Controversy
Discussions of how to teach reading and writing in the United States have a reputation for contentiousness, reflected in the military metaphors used to describe them, such as “the reading wars” or “a curricular battleground.” The public debates surrounding the fairly regular pendulum swings of the curriculum reveal fundamental differences in philosophy and widely variant interpretations of a very large but sometimes inconsistent research base.
Divergent Positions on Reading for Understanding
Beliefs about how to develop reading for understanding diverge greatly, with the spectrum of opinions defined by two extreme positions. One position, which we will refer to as the simple view of reading, holds that reading comprehension is the product of listening comprehension and decoding. Proponents of this position argue that students in the early grades should learn all of the letters of the alphabet and their corresponding sounds to a high degree of accuracy and automaticity. Agile decoding combined with a strong oral language (i.e., listening vocabulary) base will lead to fluent
reading for understanding, limited only by the reader’s store of knowledge and language comprehension. After the code is mastered, further development of reading for understanding is expected through either or both of (a) a wide reading of literature and nonfiction to gather new ideas and insights about the natural and social world and (b) solid instruction in the disciplines—the sciences, the social sciences, mathematics, and the humanities.
The polar opposite position, which might best be labeled a utilitarian view of reading, writing, and language, contends that from the outset of kindergarten, educators should engage children in a systematic quest to make sense of their world through deep engagement with the big ideas that have puzzled humankind for centuries. These are, of course, the very ideas that prompted humans to develop the disciplinary tools we use to understand and improve the natural and social world in which we live. Proponents of the utilitarian view argue that students will need to use, and hence refine, their reading and writing skills as they seek information to better understand and shape their worlds. Once students feel the need to learn to read, it will be much easier to teach students the lower-level skills needed to transform print into meaning. A side benefit is that students will have learned an important lesson about the purpose of reading—that it is always about making meaning and critiquing information on the way to acquiring knowledge.
Disagreements Over Curricular Focus, Integration, and Complexity
Disagreements on curriculum and epistemology both confound and intensify the polarized views on teaching reading for understanding. One area of disagreement is curricular focus. Instructional approaches based on the simple view tend to be curriculum centered. All students are expected to march through the same lessons and assessments, and whole-class instruction is commonplace. By contrast, instructional approaches based on the utilitarian view tend to be student centered, and each student may consume a slightly different pedagogical diet. Teachers differentiate activities and assignments for individual students based on feedback about how they are progressing, and instruction is more likely to be delivered in small groups or individualized settings.
A second area of disagreement focuses on whether the English language arts curriculum should be integrated with or separate from instruction in other disciplines. In the simple view, reading, writing, and language skills should be taught separately from the disciplinary curriculum, at least in the early stages of reading, until these fundamental skills become highly automatic. Then and only then, the argument goes, will students be ready to meet the challenges of disciplinary learning from text. The utilitarian view,
by contrast, calls for integration between English language arts and disciplinary learning from the earliest stages. Acquiring disciplinary knowledge plus discourse and inquiry skills is the goal to which reading, writing, and language skills are bound, even as they are still being acquired.
A third area of disagreement centers on strategies for coping with complexity. Advocates for the simple view argue for decomposing complex processes into component parts. For example, to help students learn to read words in connected text, they propose that teachers should first focus on teaching the parts of reading—the correspondences between individual letters (or groups of letters) and sounds. Only when students have learned these correspondences to a high degree of accuracy and automaticity should they be asked to synthesize the letters and corresponding sounds into words by reading aloud. Similarly, in writing, advocates of the simple view argue that teachers should first help students learn the parts—the correspondences between the sounds within spoken words and letters that represent these sounds. Only after students have mastered these correspondences should teachers ask them to synthesize the sounds and corresponding letters into the spelling of words.
In contrast, advocates for the utilitarian view would cope with complexity through scaffolding. They argue that students should be encouraged to perform the ultimate target task, such as reading words in connected text. Teachers should scaffold students’ performance of the task with various tools, such as reading aloud to convey the “whole of the story”; repeated readings (I’ll read a sentence, then you read it); choral readings; and encouraging students to use context and picture cues to figure out pronunciations and word meanings. In writing, students would be encouraged to get their ideas on paper and to spell things the way they sound, with the expectation that later they would, with teacher guidance, transform their sound-based spellings into conventional spellings so that others will be able to read their stories. Students would also be expected to share their written pieces with peers even before they can write and spell fluently, in an effort to represent their attempts to communicate complex ideas.
A fourth area of disagreement centers on where the locus of meaning lies—in the text, the reader, the context in which the reading is completed, or a hybrid space involving all three. A committee chaired by Snow (2002) specified a hybrid space by defining reading comprehension as “the process of simultaneously extracting and constructing meaning through interaction and involvement with written language.” The committee viewed the text as an important but insufficient determinant of reading comprehension. Kintsch (1998), in his widely accepted “construction–integration” model of reading comprehension, also discussed the importance of both extracting and constructing meaning, viewing the text as an important but insufficient resource for constructing a model of meaning. He proposed that readers
construct a mental representation of what they thought the text said (a text base) and then integrate it with key concepts from memory to create a representation (what he called the situation model) of what they thought the text meant.
Pedagogical approaches reflect these different views of where meaning lies. Approaches based on the simple view tend to stay very close to the text. Teachers pose questions to lay out the “facts” of the text prior to any interpretation, critique, or application of what was learned through reading to accomplish a new task. Approaches based on the utilitarian view may engage students in using the text as a reservoir of evidence to evaluate the validity of different claims, interpretations, critiques, or uses of the text.
The research base for reading, as reflected in key summary documents in the field—such as the report of the National Institute of Child Health and Human Development (2000), the National Academy of Sciences’ Preventing Reading Difficulties in Young Children (National Research Council, 1998), and the four volumes of the Handbook of Reading Research (Pearson et al., 1984; Barr et al., 1991; Kamil et al., 2000, 2011)—tend to provide consistent support for a balanced position that emphasizes both basic and more advanced processes. Such a balanced approach strongly emphasizes the basic skills of phonemic awareness, alphabet knowledge, and decoding for accurate word learning in the early stages of reading acquisition, but places an equal emphasis on reading for meaning at all stages of learning to read. As students mature and the demands of school curriculum focus more on the acquisition of disciplinary knowledge, the emphasis on reading for meaning increases. Thus the polar views that define the extremes of the continuum of views on reading acquisition and pedagogy ultimately converge in a more comprehensive view of written language acquisition. For the all-important early stages of reading, while there is strong support for early emphasis on the basics, there is no evidence that such an emphasis should preclude an equally strong emphasis on learning to use the range of skills and knowledge acquired early on to engage in transfer to new situations and in monitoring one’s reading and writing to see if it makes sense.
Although all the parties in the debate share the goal of deeper learning in English language arts, they propose different routes. Some want to start with shallower or more basic tasks as a foundation for deeper or higher-order tasks. Others want to start with the deeper learning tasks and engage the more basic tasks and information as resources to help students complete the more challenging tasks. In the final analysis, the research supports a more balanced view that incorporates both the “basics” and the need to monitor reading and writing for sense-making and to apply whatever is
learned about reading and writing to the acquisition of knowledge within disciplinary settings.
The Four Resources Model as an Approach to Defining Deeper Learning
In the early 1990s, Australian scholars Freebody and Luke took an important step forward in reconciling the various controversies described above (Freebody and Luke, 1990; Luke and Freebody, 1997). They created what is now known as the “four resources model.” The model consists of a set of different stances that readers can take toward a text, each of which approaches reading from a different point of view: that of the text, the reader, the task, or the context. Taken together, the stances constitute a complete “theory” of a reader who is capable of managing all of the resources at his or her disposal. The authors propose that any reader can assume any one of these four stances in the quest to make meaning in response to a text. The confluence of reader factors (how much a reader knows or is interested in a topic), text (an assessment of the complexity and topical challenge of the text), task (what a reader is supposed to do with the topic), and context (what is the purpose or challenge in dealing with this text) will determine the particular stance a reader assumes when reading a particular text. That stance can change from text to text, situation to situation, or even moment to moment when reading a given text. The various stances (resources) and the key questions associated with each are
- The reader as decoder, who asks: What does the text say? In the process, the reader builds a coherent text base where each idea is tested for coherence with all of the previous ideas gleaned from a close reading of the text.
- The reader as meaning maker, who asks: What does the text mean? In answering that question, the reader seeks to develop meaning based on: (a) the ideas currently in the text base and (b) the reader’s prior knowledge.
- The reader as text analyst, who asks: What tools does the author use to achieve his or her goals and purposes? The text analyst considers how the author’s choice of words, form, and structure shape our regard for different characters or our stance toward an issue, a person, or a group. The text analyst reads through the texts to get to the author and tries to evaluate the validity of the arguments, ideas, and images presented.
- The reader as text critic, who asks questions about intentions, subtexts, and political motives. The text critic assumes that no texts are ideologically neutral, asking such questions as: Whose interests are served or not served by this text? Who is privileged,
marginalized, or simply absent? What are the political, economic, epistemological, or ethical goals of the author?
When the stances of the text critic and the text analyst are combined, the goals of truly critical reading can be achieved. The reader can examine both the assumptions (what knowledge base is required to make sense of the text) and consequences (whose views are privileged and whose are ignored) of a text.
All four stances are in play as well when a writer creates texts for others to read. Writers have various conceptual intentions toward their readers—to inform, for example, or to entertain, persuade, or inspire. They sometimes focus on the code in getting the words on paper. They always employ the two standards of the meaning maker—that what they write in any given segment is consistent with the ideas in the text up to this point, and that it is consistent with the assumed knowledge of the ideal reader. Writers are most expert at handling the form-function (or purpose-structure) relationship of the text analyst; in fact, the crux of the author’s craft is to seek and find just the right formal realization of each particular conceptual intention toward the reader. Finally, writers have ulterior motives along with transparent ones. They privilege, marginalize, omit, or focus—sometimes intentionally and other times unwittingly as agents of the cultural forces that shape their work.
The four resources model allows us to define deeper learning in English language arts in a way that recognizes the controversies in the discipline yet meets the need for a balanced approach that equips the reader or writer to take different stances toward the reading or writing of a text depending on the purposes, the context, and the actual task confronting the reader or writer. Reading and writing are simultaneously code-breaking, meaning making, analytic, and critical activities; which stance dominates at a particular moment in processing depends upon the alignment of reader, text, task, and contextual factors. This perspective on deeper learning, recognizing that the reader or writer may adopt various stances from moment to moment, contrasts sharply with the “simple view” of reading and writing. The simple view would limit beginning readers to the code-breaking stance and limit beginning writers to codifying language, by putting down letters and words.
Drawing on the four resources model, we can now define deeper learning in English language arts from two perspectives: (1) as privileging activities that are successively higher on the list—in which the reader acts as meaning maker, text analyst, or text critic; or (2) as privileging the management of all four stances in relation to the reader’s assessment of the difficulty of the text or task and the reader’s purpose and knowledge resources. In the first perspective on deeper learning, analysis and critique
take precedence over making meaning, which takes precedence over decoding. Such a hierarchy is consistent with the research base we will discuss in Chapter 6, in which we will describe the pedagogy of deeper learning as encouraging generative processing, elaboration, and questioning—all of which would lead us down the pathway toward meaning making, analysis, and critique. Indeed, the research on discussion protocols in reading text suggests that the effects of discussion questions are highly specific—that unless one focuses directly on analysis and critique, it is not likely to emerge on its own (Murphy et al., 2009). In the second perspective on deeper learning, reflecting on and managing one’s own knowledge matters most in shaping the particular stance that one takes toward the understanding or construction of a text. This perspective builds on other principles of deeper learning elaborated in Chapter 4, namely, the notions of developing metacognitive strategies, self-monitoring, and self-explanation—all dispositions that encourage the learner to intentionally engage in his or her own comprehension and learning processes. This view also suggests that deeper learning involves knowing when and why to privilege lower-order over higher-order skills in pursuit of understanding or problem solving.
These two perspectives on deeper learning in English language arts are not mutually exclusive. Deeper learning could involve the deliberate selection of a stance that elicits the skills and processes that best fit the situation and problem that a learner faces at any given moment and also suggest a procedural preference for always selecting the highest level among alternative stances when the situation or problem allows more than one approach. For example, if assuming either the meaning making stance or the analysis stance will allow the learner to solve a reading or writing problem, the learner should opt for an analytic stance to complete the task. From either perspective, beginning readers and writers as well as those who are more advanced, can engage in deeper learning.
Common Core State Standards
The widely adopted Common Core State Standards in English language arts (CCSS-ELA; Common Core State Standards Initiative, 2010a) are likely to shape any attempt to infuse deeper learning initiatives into school curricula. In other words, it is likely that whatever purchase deeper learning initiatives accrue in the next decade will be filtered through this set of standards. From this perspective, the prospects for reading and writing instruction aligned with the four resources model seem promising.
The full title of the CCSS-ELA, Standards for English Language Arts and Literacy in History/Social Studies, Science, and Technical Subjects (Common Core State Standards Initiative, 2010a), provides the first indication that these standards will be different from state English language arts
(ELA) standards created before 2010. The title signals the adoption of an integrated view of the topics of reading, writing, speaking/listening, and language. This integrated view is applied to two domains—literature and informational text—for reading and writing in grades K-5. The standards for grades 6-12 are first organized by ELA topic and then by subject matter (history and science) to distinguish which standards are the responsibility of the ELA teacher and which might better be addressed by science and history teachers. Within ELA, the four topics are again applied to the domains of literature and informational text. By contrast, the subject area sections address only the topics of reading and writing, broken down according to history/social studies and science/technical subjects.
This integrated view of ELA contrasts sharply with the heavy emphasis that in recent years has been placed on reading as a separate subject, almost to the exclusion of other language arts topics and other school subjects. The integration of reading with other topics and subjects represents a dramatic shift away from the “big five” approach—phonemic awareness, phonics, fluency, vocabulary, and comprehension—which has dominated reading instruction for over a decade (National Institute of Child Health and Human Development, 2000). The new standards present reading, writing, and oral language as tools for knowledge acquisition, effective argumentation, and clear communication across the disciplines of literature, science (and technical subjects), and history (and social studies). The standards address phonemic awareness, phonics, and fluency primarily in the foundational skills addendum to the K-5 standards. Vocabulary is highlighted in the language strand, and comprehension, alongside composition, is emphasized throughout. This combined with the standards’ focus on reading and writing in the disciplines of history and science indicates that the CCSS-ELA can be interpreted as calling for a major shift from the current emphasis on decoding to comprehension of and learning with text.
The CCSS-ELA include 10 college and career readiness anchor standards, representing the “end state”—what high school graduates should know and be able to do if all of the specific grade-level and disciplinary variations of these 10 standards were to be successfully implemented. As shown in Box 5-1, the 10 anchor standards for reading are arranged in four clusters.
The mapping of these standards onto the four resources model (Luke and Freebody, 1997) is reasonably transparent. The three standards in Cluster 1, Key Ideas and Details, reflect the stance of the reader as decoder, with a hint of reader as meaning maker (because of the requirement of invoking prior knowledge to complete each task). The three standards in Cluster 2, Craft and Structure, reflect the stance of the reader as text analyst, focusing on form-function (or purpose-structure) relationships. The three standards in Cluster 3, Integration of Knowledge and Ideas, entail
College and Career Readiness Anchor Standards for Reading
Key Ideas and Details
1. Read closely to determine what the text says explicitly and to make logical inferences from it; cite specific textual evidence when writing or speaking to support conclusions drawn from the text.
2. Determine central ideas or themes of a text and analyze their development; summarize the key supporting details and ideas.
3. Analyze in detail where, when, why, and how events, ideas, and characters develop and interact over the course of a text.
Craft and Structure
4. Interpret words and phrases as they are used in a text, including determining technical, connotative, and figurative meanings, and explain how specific word choices shape meaning or tone.
5. Analyze the structure of texts, including how specific sentences, paragraphs, and larger portions of the text (e.g., a section or chapter) relate to each other and the whole.
6. Assess how point of view or purpose shapes the content and style of a text.
Integration of Knowledge and Ideas
7. Synthesize and apply information presented in diverse ways (e.g., through words, images, graphs, and video) in print and digital sources in order to answer questions, solve problems, or compare modes of presentation.
8. Delineate and evaluate the reasoning and rhetoric within a text, including assessing whether the evidence provided is relevant and sufficient to support the text’s claims.
9. Analyze how two or more texts address similar themes or topics in order to build knowledge or to compare the approaches the authors take.
Range and Level of Text Complexity
10. Read complex texts independently, proficiently, and fluently, sustaining concentration, monitoring comprehension, and, when useful, rereading.
SOURCE: Common Core State Standards Initiative (2010a). © Copyright 2010. National Governors Association Center for Best Practices and Council of Chief State School Officers. All rights reserved. Reprinted with permission.
all four stances—decoder, meaning maker, analyst, and critic, but favor the text critic (especially 8) and meaning maker (especially 7 and 9). And, of course, the standard in Cluster 4, Range and Level of Text Complexity, involves all four stances in constant interaction.2
Relating the Standards to Deeper Learning and 21st Century Skills
The CCSS-ELA offer a policy framework that is highly supportive of deeper learning (as reflected in the four resources model) in English language arts. On the other hand, it remains to be seen whether the assessments that emerge from the two state assessment consortia, which have been funded by the Department of Education to develop next-generation assessments aligned to the Common Core State Standards, will be equally supportive of the goal of deeper learning, a question we will return to in Chapter 7.
In the previous chapters, we identified three broad domains of 21st century skills—cognitive, intrapersonal, and interpersonal. To examine the relationship between these clusters of 21st century skills and the various disciplinary standards documents, the committee created a list of some of the most frequently cited 21st century and deeper learning skills and then examined the standards for the degree of support provided for these skills.3 The domain of cognitive 21st century skills, developed through deeper learning, is well represented in the CCSS-ELA. What is missing, both from the new CCSS and from the larger discussion of goals for reading and writing instruction presented above, is any serious consideration of the intrapersonal and interpersonal domains (see Figure 5-1).
Although the word “motivation” appears three times in the CCSS-ELA, the new standards do not seriously address the motivational factors (engagement, interest, identity, and self-efficacy) and dispositional factors (conscientiousness, stamina, persistence, collaboration) that we know
2It is fortunate that we can continue this mapping of cognitive constructs of CCSS onto the NAEP infrastructure for cognitive targets for reading assessment. NAEP’s locate and recall target corresponds quite closely to the key ideas and details CCSS category. NAEP’s integrate and interpret corresponds to CCSS’s integration of knowledge and ideas, and NAEP’s critique and evaluate incorporates much of what falls into CCSS’s craft and structure (though it entails much more than craft and structure). This set of correspondences should facilitate longitudinal analyses of the course of reform engendered by the CCSS.
3The classifications in the figures in this chapter represent common sense judgments by an expert in each discipline who is familiar with the standards, with curriculum and practice, and with the cognitive and educational research literatures in the discipline. Undoubtedly other judges would classify some components differently. The study committee was not charged with conducting a more elaborate analytic study with multiple independent raters and assessments of reliability. Thus these diagrams and observations are meant to represent a plausible illustrative view rather than a definitive analysis.
FIGURE 5-1 Overlap between ELA-CCSS standards and 21st century skills.
SOURCE: Created by the committee.
support deeper learning. However, recent research in English language arts illustrates the potential for developing these intrapersonal factors, as well as interpersonal factors. One example is described in Box 5-2 below, and another is found in the work of Guthrie, Wigfield, and You (2012). As noted in Chapter 4, the development of self-regulated strategies in writing—including motivation and feelings of self-efficacy—has been shown to improve writing performance among diverse groups of learners (Graham, 2006). The most probable explanation for the conspicuous absence of these factors from the standards is that, as noted in Chapter 6, they represent skills that are difficult to measure, at least without a very heavy reliance on human judgment. Therefore, these factors are unlikely candidates for systematic monitoring in accountability systems, which have traditionally relied on standardized measures that minimize reliance on human judgment. Presumably the authors of the standards were aware of research showing that reading and writing instruction focused on domain-specific learning goals can develop motivation and positive dispositions toward disciplinary learning, such as the example presented below, but felt that this was beyond the purview of the ELA standards.
The Context: Typical Mathematics Instruction
Research studies provide a clear, consistent picture of typical school mathematics instruction in the United States. What we know is largely derived from two kinds of data and associated research analyses. One type of study that has been carried out over several decades has involved direct observation of classroom teaching (e.g., Stake and Easley, 1978; Stodolsky, 1988; Stigler et al., 1999; Hiebert et al., 2005), and another has used teacher self-report data from surveys (e.g., Weiss et al., 2001; Grouws, Smith, and Sztajn, 2004).
These studies present a remarkably consistent characterization of mathematics teaching in upper elementary school and middle-grade classrooms in the United States: Students generally work alone and in silence, with little opportunity for discussion and collaboration and little or no access to suitable computational or visualization tools. They focus on low-level tasks that require memorizing and recalling facts and procedures rather than tasks requiring high-level cognitive processes, such as reasoning about and connecting ideas or solving complex problems. The curriculum includes a narrow band of mathematics content (e.g., arithmetic in the elementary and middle grades) that is disconnected from real-world situations, and a primary goal for students is to produce answers quickly and efficiently without much attention to explanation, justification, or the development of meaning (e.g., Stodolsky, 1988; Stigler and Hiebert, 1999). As earlier chapters in this volume have indicated, reflecting research evidence regarding how people learn best when the goal is developing understanding (National Research Council, 1999), such pedagogy is at odds with goals aimed at deeper learning and transfer.
Although this pervasive approach to mathematics teaching has not been directly established as the cause of the generally low levels of student achievement, it is difficult to deny the plausibility of such a connection. In response, an array of reform initiatives has been aimed at changing what and how mathematics is taught and learned in American schools. Although reformers have disagreed on some issues, they share the goal of enhancing students’ opportunities to learn mathematics with understanding and hence the attendant goal of promoting teaching mathematics for understanding. These goals reflect a focus on deeper learning in school mathematics.
Evolution of National Standards in Mathematics
School mathematics reform has a long history that cannot be adequately described in the limited space here, so we focus on the most recent
An Example of Deeper Learning in English Language Arts
The Common Core State Standards for English language arts (Common Core State Standards Initiative, 2010a) provide many opportunities to enact the principles of deeper learning embodied in this report. First, they promote a double vision of integration—(a) that reading, writing, and discourse ought to support one another’s development, and (b) that reading, writing, and language practices are best taught and learned when they are employed as tools to acquire knowledge and inquiry skills and strategies within disciplinary contexts, such as science, history, or literature. Hence the standards for reading, writing, and language are unpacked in grades 6 through 12 within the three domains of literature, science and technology, and history. Further, a common criterion for rigorous thinking embedded in the standards centers on developing argumentation skill—the ability to understand, critique, and construct arguments that are valid within the norms of each discipline. Students are asked to deal with what counts as evidence, how arguments are constructed, what constitutes a counter claim and counter evidence—in short, both the structure and substance of reasoning is privileged. While not as ubiquitous as cognitive skills, interpersonal skills are strongly implicated in the speaking and listening standards, with an emphasis on collaboration and listening with care to understand and evaluate others’ utterances as a part of rigorous discourse.
At the elementary level, project-based learning has a long history dating back to days of John Dewey and the progressive education movement in schools, a tradition in which the goal was to minimize the distance between school learning and the learning that occurs in the enactment of everyday life outside of school. In one (of many) modern instantiation of this tradition, literacy and science educational researchers at the University of California-Berkeley’s Lawrence Hall of Science and in the Graduate School of Education have worked with elementary classroom teachers on an NSF-sponsored curriculum in which reading, writing, and academic language are used as tools to support the acquisition of science knowledge, inquiry strategies, and argumentation skills (Cervetti et al., 2012). Aptly named Seeds of Science/Roots of Reading, the program combines hands-on science activities (e.g., designing mixtures such as glue or hair gel from everyday household ingredients or using models to understand the formation of sand on a beach) with a host of reading, writing, and oral discourse activities to support and extend students’ investigations and projects. Over the course of an 8-week unit, students read nine different types of books about various aspects of the topic (e.g., the science of sand, light, soil habitats) in a range of genres. These genres may include reference books, brief biographies of scientists, information pieces, books that model an aspect of either a scientific or a literacy process, and books that connect science to everyday life. All of the books are coordinated with specific subtopics within the unit. For example, a hands-on investigation of snails’
preferred habitats is paired with a parallel trade book about a science class that collects and analyzes data about the same investigation. Similarly, the students’ investigation of “mystery” sand is paired with a biography of a sand scientist that describes how he investigates the size, shape, color, texture, and origin of sand.
Students write in their science journals almost daily and engage in spirited discussions and debates (they call them discourse circles) about unsettled issues that arise from hands-on investigations and/or readings (e.g., they might hold a debate about the origin of a mystery sand). In a typical week in this approach, students will spend about 50 percent of their time in science activities and about 50 percent in reading, writing about their investigations, and talking about their reading, and their personal writing. Several times a week, students are asked to reflect on the quality and focus of their personal learning and participation as well as the learning and participation of their work groups—and even the class as a whole.
The curriculum is designed to foster deeper learning in the cognitive domain, through all of the reading, writing, and inquiry activities. At the same time, deeper learning of intrapersonal competencies is supported by the individual and group reflection activities, which encourage metacognition, taking personal responsibility for one’s learning, stamina, and persistence. In the interpersonal domain, deeper learning is fostered by ongoing collaboration, including the discussions about the readings, the small group collaborative investigations, the discourse circles, and even in the division of labor students work out for extended investigations or projects. Reflection activities encourage students to reflect not only on their learning but also on how well their group cooperated and how they could improve their discussions.
The approach was tested in 94 fourth-grade classrooms in one Southern state. Half of the teachers taught the integrated science-literacy curriculum, while the other half of the teachers taught the two topics separately, covering the same science content with materials provided by their school districts along with their regular literacy instruction. Students in the integrated lessons made significantly greater gains on measures of science understanding, science vocabulary, and science writing, and both groups made comparable gains in science reading comprehension. Examples like these demonstrate that cognitive outcomes, which are clearly emphasized in most educational testing and accountability schemes in our country, need not suffer—indeed can prosper—when they are taught and learned in a context in which inter- and intrapersonal skills and practices are equally emphasized. Such examples also demonstrate that at least some disciplines—in this case, English language arts—can benefit from being taught in another disciplinary context, like science. Research has demonstrated the effectiveness of similar curricula integrating English language arts in the disciplines of literature (Guthrie et al., 2004) and social studies (De La Paz, 2005).
SOURCE: Adapted from Cervetti et al. (2012).
reform efforts. In 1989, the National Council of Teachers of Mathematics (NCTM) published the Curriculum and Evaluation Standards for School Mathematics (CESSM), which was the first attempt to lay out comprehensive national goals for mathematics learning. The curriculum goals portion of the document was divided into three sections representing grade-level clusters: 1-4, 5-8, and 9-12. Each section contained goals for all students and additional goals for college-intending students. CESSM promoted a view of mathematics as accessible to all students if instruction were changed to place greater emphasis on understanding and applicable knowledge and less emphasis on the memorization of facts and procedures.
CESSM, serving as the first national model of content expectations in school mathematics, had substantial influence on the mathematics instructional goals and frameworks later developed by a number of individual states. Nevertheless, over time it became clear that CESSM lacked the specificity needed by state policy makers to set objectives at and across grade levels and by teachers to implement the report’s pedagogical and curricular ideas in their classrooms. In response to these perceived limitations, in 2000 the NCTM developed and published a successor document, Principles and Standards for School Mathematics (PSSM) (National Council of Teachers of Mathematics, 2000).
While PSSM preserved the essential tenets of the earlier CESSM, especially its emphasis on the importance of learning mathematics with understanding, it also added several enhancements. To provide more grade-level-specific clarity and guidance, PSSM was divided into narrower grade-level bands: K-2, 3-5, 6-8, and 9-12. For each band, PSSM presented only one set of goals for all students. PSSM also had a common set of overarching curricular expectations across the K-12 spectrum, which was intended to help state officials develop logical progressions of instruction from grade to grade for inclusion in state curriculum guidelines. PSSM was much more specific than the CESSM about the research basis for its recommendations, and the NCTM published a companion document that reviewed research in a number of areas directly related to the content of PSSM.
PSSM was subjected to extensive field review prior to publication, and it was generally well received when published in 2000, but it arrived at the dawn of the No Child Left Behind (NCLB) era in American education. Because extant standardized tests of school mathematics were not well aligned with PSSM, and because NCLB regulations required that these tests be a regular feature of every school year in grades 3-8 in order to determine whether adequate yearly progress was being made, PSSM had far less impact on states, schools, teachers, and students than had been envisioned by the NCTM.
One decade later, the move toward national guidance regarding expectations for school mathematics learning took a giant leap forward with the
publication of the Common Core State Standards for Mathematics (CCSSM; Common Core State Standards Initiative, 2010b). CCSSM presents grade-level-specific expectations that are intended to be the core expectations for mathematics learning in the United States. CCSSM diverges from CESSM and PSSM in certain ways, including how it names the strands of content to be taught and learned and how it distributes certain content across the grades, but it retains the same focus on the importance of teaching in ways that enable students to learn mathematics with understanding. The CCSSM states, “These Standards define what students should understand and be able to do in their study of mathematics” (Common Core State Standards Initiative, 2010b, p. 4). Not only is this a consistent theme across the reform documents, it is also a topic that has received considerable attention from the research community.
Research Perspectives on Teaching Mathematics for Understanding
Studies conducted over the past 60 years provide a solid body of evidence concerning the benefits of teaching mathematics for understanding. As summarized in Silver and Mesa (2011, p. 69), teaching mathematics for understanding is sometimes referred to as:
authentic instruction, ambitious instruction, higher order instruction, problem-solving instruction, and sense-making instruction (e.g., Brownell and Moser, 1949; Brownell and Sims, 1946; Carpenter, Fennema, and Franke, 1996; Carpenter et al., 1989; Cohen, 1990; Cohen, McLaughlin, and Talbert, 1993; Fuson and Briars, 1990; Hiebert and Wearne, 1993; Hiebert et al., 1996; Newmann and Associates, 1996). Although there are many unanswered questions about precisely how teaching practices are linked to students’ learning with understanding (see Hiebert and Grouws, 2007), the mathematics education community has begun to emphasize teaching that aims for this goal.
Among the hallmarks of this conceptually oriented version of instruction are (a) mathematical features, or tasks that are drawn from a broad array of content domains and are cognitively demanding, and (b) pedagogical features, or teaching practices that are suitable to support multiperson collaboration and mathematical discourse among students, as well as their engagement with mathematical reasoning and explanation, consideration of real-world applications, and use of technology or physical models (e.g., Hiebert and Carpenter, 1992; Fennema and Romberg, 1999).
The mathematics curriculum in the United States, especially in elementary and middle grades, has long been characterized as incoherent, cursory, and repetitive (e.g., Balfanz, Mac Ivar, and Byrnes, 2006). Many have argued that the excessive attention paid to numbers and operations has restricted students’ opportunities to learn other interesting and important mathematics content. Reflecting this concern, the National Council of Teachers of Mathematics standards (1989, 2000) noted the importance of including topics in algebra, geometry, measurement, and data analysis in the middle grades. Broader coverage is expected not only to enrich mathematics learning by exposing students to more topics but also to make salient the connections that exist among different content domains and topics—connections that are viewed by psychologists as hallmarks of student understanding (National Research Council, 1999).
Reformers have also called for a new approach to the mathematics tasks that provide daily opportunities for student learning. For example, the Professional Standards for Teaching Mathematics (National Council of Teachers of Mathematics, 1991) claimed that student learning of mathematics with understanding depended to a great extent on the teacher using “mathematical tasks that engage students’ interests and intellect” (p. 1). Although such tasks can help students develop understanding, establish and maintain curiosity, and communicate with others about mathematical ideas, mathematics teachers in grades K-8 usually present cognitively undemanding tasks, such as recalling facts and applying well-rehearsed procedures to answer simple questions (Stake and Easley, 1978; Stodolsky, 1988; Porter, 1989; Stigler and Hiebert, 1999). Research has shown that it is not easy for teachers to use cognitively demanding tasks well in mathematics classrooms (Stein, Grover, and Henningsen, 1996; Henningsen and Stein, 1997). However, the regular use of such tasks to maintain high levels of cognitive demand can lead to increased student understanding and the development of problem solving and reasoning (Stein and Lane, 1996) and greater overall student achievement (Hiebert et al., 2005).
Reformers have also advocated a broader array of pedagogical strategies to increase students’ understanding of mathematics, moving beyond the limited current practices described above. As noted earlier in this chapter, current practice is at odds with research findings about how people learn with understanding (National Research Council, 1999). Silver and Mesa (2011) describe the goals of the reformers as follows:
Advocates for conceptually oriented teaching in school mathematics (e.g., National Council of Teachers of Mathematics, 1989, 2000) have suggested the potential value of fostering communication and interaction among students in mathematics classrooms through the use of complex tasks that are suitable for cooperative group work and that provide settings in which students need to explain and justify their solutions. Moreover, to increase students’ engagement with mathematical tasks and their understanding of concepts, instructional reform efforts have also encouraged the use of hands-on learning activities and technological tools, as well as connecting work done in the mathematics classroom to other subjects and to the world outside school. Beyond exhortations, there is also some research evidence to support these hypotheses about pedagogy that might support students’ development of mathematical understanding (e.g., Boaler, 1998; Fawcett, 1938; Fuson and Briars, 1990; Good, Grouws, and Ebmeier, 1983; Hiebert and Wearne, 1993; Stein and Lane, 1996). (Silver and Mesa, 2011, p. 69)
Two examples of instruction incorporating these types of pedagogical features are found in Box 5-3.
Deeper Learning Expectations in Mathematics
As noted earlier, the three major reform documents in school mathematics—CESSM, PSSM, and CCSSM—all emphasize deeper learning of mathematics, learning with understanding, and the development of usable, applicable, transferable knowledge and skills. These themes are in line with the broader statements we discussed earlier regarding the importance of 21st century learning skills. Generally speaking, the mathematics curriculum reform documents are much more explicit about expectations in the cognitive domain than they are about expectations in the intrapersonal and interpersonal domains. Yet, even in the domains less explicitly dealt with in the curriculum reform documents, one finds attention to some key 21st century goals, such as collaborative work, self-regulation, and the formation of positive attitudes and a mathematical identity. Moreover, there is a robust research literature on the matters of collaboration, metacognition, attitudes, motivation, and identity as they pertain to the teaching and learning of school mathematics. Chapter 3 of Engaging Schools: Fostering High School Students’ Motivation to Learn (National Research Council and Institute of Medicine, 2004) provides an analysis of how many of these factors might interact with issues of race and culture to affect the learning of mathematics.
Again, the committee mapped the reform documents and the lists of 21st century learning skills to ascertain areas of overlap and emphasis. A
Examples of Deeper Learning in Mathematics
In Chapter 4, we provided an illustration of deeper learning of mathematics at the high school level (Boaler and Staples, 2008). Here, we focus on early mathematics learning. The weak performance of U.S. 15-year-olds on the mathematics component of the Programme for International Student Assessment (PISA) test (OECD, 2010) reflects the weakness of early math education in the United States. Deeper learning of mathematics in early childhood could potentially reverse the problem of persistent gaps in mathematics knowledge between children from low-income and middle-income backgrounds.
Example 1: Using Board Games for Early Mathematics Learning
One approach to helping preschoolers learn basic number concepts and strategies involves the use of board games. Playing board games with linearly arranged, consecutively numbered, equal-size spaces provides young children with multiple cues about the magnitude of the numbers. Ramani and Siegler (2011) compared the number knowledge of middle-income preschoolers who played a linear board game to the number knowledge of preschoolers from low-income backgrounds who also played this game. Among both groups of preschoolers, those with less initial knowledge of numbers gained more in understanding than those with greater initial knowledge. Significantly, the children from low-income backgrounds learned at least as much, and on several measures more, than preschoolers from middle-income backgrounds.
The study built on an earlier study of low-income preschoolers (Ramani and Siegler, 2008; Siegler and Ramani, 2009), which found that a brief game-playing intervention led to greater improvements in numeracy than alternative numerical activities lasting the same amount of time. The low-income preschoolers showed gains in their ability to estimate number lines, compare magnitudes, identify numerals, and in basic arithmetic, and these gains were stable over a 9-week period. Those who had earlier played the linear board game learned more from subsequent practice and feedback on addition problems than their peers who engaged in other numerical activities, suggesting that they were able to transfer the knowledge they had gained through game play.
A higher percentage of preschoolers from middle-income families than from low-income families report playing board games at home (Ramani and Siegler, 2011), and this difference may contribute to the gap in mathematics knowledge between young children from low-income and middle-income backgrounds. The authors suggest that parents and teachers more frequently engage young children in playing linear board games, which require minimal time to play and are extremely inexpensive.
Example 2: Restructuring the Elementary School Mathematics Classroom
Deeper learning as called for in the Common Core State Standards and other documents reviewed above remains rare in U.S. classrooms. In the 2005 NRC
report How Students Learn: History, Mathematics, and Science in the Classroom, Griffin (2005) describes very different mathematics classroom activities that are part of the research-based program, Number Worlds, for prekindergarten through grade 2. The program is based on six guiding principles (National Research Council, 2005, p. 283), and we describe illustrative activities related to a few of these principles below:
- Expose children to the major ways that numbers are represented and talked about.
- Provide opportunities to link the “world of quantity” with the “world of counting numbers” and the “world of formal symbols.”
- Provide visual and spatial analogs of number representations that children can actively explore in hands-on fashion.
- Engage children and capture their imagination so knowledge constructed is embedded not only in their minds but also in their hopes, fears, and passions.
- Provide opportunities to acquire computational fluency as well as conceptual understanding.
- Encourage the use of metacognitive processes (e.g., problem solving, communication, reasoning) that will facilitate knowledge construction.
To implement the first principle, children explore five different lands at each grade level. In each land, they learn about a particular form of number representation while simultaneously addressing specific knowledge goals (developmental milestones) for that grade level. They begin in Object Land, where they initially work with real objects and then move on to work with pictures of objects. Next, they visit Picture Land, where numbers are represented as semiabstract patterns of dots that are equivalent to mathematical sets. By playing various card and dice games, the students gradually come to think of these patterns in the same way that they think of the words they use to talk about numbers. Third, they explore Line Land, where numbers are represented as segments along a line, and they play linear games. Later, they visit Sky Land, where numbers are represented with vertical bar graphs and scales, and Circle Land, where numbers are represented by sundials and clocks, and they learn that numbers are used to measure time and the seasons of the year.
All of the activities are designed to help early elementary students mentally link physical quantities with counting numbers and formal symbols (design principle 2) as illustrated by the game “Plus Pup.” To start, the teacher and children put a certain number of cookies into a lunch bag, and then the teacher or a child takes a walk with the bag. Along the way, the teacher or child picks up the Plus Pup card, and receives one more cookie. The teacher then invites the children to figure out how many cookies are in the bag. At first, the children open up the bag and count the cookies, but as they continue to replay the game, they gradually realize that they can use numbers to find the answer.
To support metacognitive processes (design principle 6), the program includes question cards that draw children’s attention to the changes in quantities they enact during game play and prompt children to perform any calculations nec-
essary to answer the questions. Additional follow-up questions encourage children to reflect on their own reasoning. The teacher usually uses the question cards at first, but over time, the children gradually begin to pose the questions themselves, assuming greater responsibility for their own learning. In a wrap-up period at the end of each lesson, a reporter from each small group first describes what the group did and learned and then takes questions from the rest of the class. This time for communication and reflection supports significant learning.
Evaluation studies indicate that the program is effective in helping diverse young children develop number knowledge that is deep, lasting, and transferable to further mathematics learning. A longitudinal 3-year study compared the performance of three groups of kindergarten through ninth grade students: (1) an urban, low-income group who participated in Number Worlds; (2) a low-income group who had been tested and identified as high achievers in mathematics; and (3) a largely middle-class group, also tested and designated as high achievers, who were enrolled in a magnet school with an enriched mathematics program. Over the course of the study period, from kindergarten entry to the end of second grade, the mathematics achievement of the Number Worlds group first caught up with, and then gradually exceeded, the achievement of the other two groups.
In addition to clearly enhancing mathematics achievement in the cognitive domain, the program generates positive dispositions toward mathematics among both students and teachers in the intrapersonal domain (Griffin, 2005) as well as enhances the interpersonal skills of communication, collaboration, and teamwork.
summary is provided in Figure 5-2, and outcomes of the mapping process are elaborated briefly below.
In mathematics, as is the case with the other content areas treated in this chapter, the cognitive domain affords the strongest correspondence between 21st century skills and school learning goals for the subject. In particular, the CCSSM, PSSM, and CESSM documents all consider critical thinking, problem solving, constructing and evaluating evidence-based arguments, systems thinking, and complex communication to be important learning goals for mathematics, though there is some variation in how these skills are treated and the relative emphasis placed on each.
The two most prominent areas of overlap between 21st century skills and learning goals for school mathematics are found for the themes of argumentation/reasoning and problem solving. Problem solving and reasoning are central to mathematics and have long been viewed as key leverage
FIGURE 5-2 Overlap between CCSS mathematics standards and 21st century skills.
SOURCE: Created by the committee.
points in efforts to teach mathematics for understanding (Fawcett, 1938; Schoenfeld, 1985; Silver, 1985, 1994; Charles and Silver, 1988).
As the PSSM reasoning and proof standard states
Being able to reason is essential to understanding mathematics…. [I]nstructional programs across PK-12 should enable students to … recognize reasoning and proof as fundamental aspects of mathematics; make and investigate mathematical conjectures; develop and evaluate mathematical arguments and claims; and select and use various types of reasoning and methods of proof. (National Council of Teachers of Mathematics, 2000, p. 56)
Students are expected to have opportunities to explore mathematical patterns in order to detect regularities, to formulate conjectures and hypotheses based on observed patterns and regularities, and to investigate and test the validity of these conjectures and hypotheses using mathematical reasoning. Students should learn to use varieties of mathematical reasoning
and argumentation (e.g., probabilistic, geometric, algebraic, and proportional reasoning) and to generate mathematically valid proof arguments and counterarguments (e.g., develop validity justifications and produce a counterexample) (National Council of Teachers of Mathematics, 2000, pp. 56-59).
This theme of argumentation and reasoning is touched on explicitly in two of the CCSSM standards for mathematical practice: “Reason abstractly and quantitatively,” and “Construct viable arguments and critique the reasoning of others.” In discussing the latter standard, CCSSM states
Mathematically proficient students understand and use stated assumptions, definitions, and previously established results in constructing arguments. They make conjectures and build a logical progression of statements to explore the truth of their conjectures. They are able to analyze situations by breaking them into cases, and can recognize and use counterexamples. They justify their conclusions, communicate them to others, and respond to the arguments of others…. Students at all grades can listen to or read the arguments of others, decide whether they make sense, and ask useful questions to clarify or improve the arguments. (Common Core State Standards Initiative, 2010b, p. 6)
The CCSSM also deals explicitly with problem solving. Its first standard in the category of mathematic practice is “Make sense of problems and persevere in solving them.” In discussing this standard, CCSSM states
Mathematically proficient students start by explaining to themselves the meaning of a problem and looking for entry points to its solution. They analyze givens, constraints, relationships, and goals. They make conjectures about the form and meaning of the solution and plan a solution pathway rather than simply jumping into a solution attempt. They consider analogous problems, and try special cases and simpler forms of the original problem in order to gain insight into its solution. They monitor and evaluate their progress and change course if necessary…. They can understand the approaches of others to solving complex problems and identify correspondences between different approaches. (Common Core State Standards Initiative, 2010b, p. 6)
This view that problem-solving processes play a central role in mathematical activity is resonant with the earlier characterization provided in PSSM’s problem-solving standard:
Problem solving means engaging in a task for which the solution method is not known in advance. In order to find a solution, students must draw on their knowledge, and through this process, they will often develop new mathematical understandings. Solving problems is not only a goal of learning mathematics but also a major means of doing so … instructional programs across PK-12 should enable students to … build new
mathematical knowledge through problem solving, solve problems that arise in mathematics and in other contexts, apply and adapt a variety of appropriate strategies to solve problems, and monitor and reflect on the process of mathematical problem solving. (National Council of Teachers of Mathematics, 2000, p. 52)
Students should learn to recognize classes of problems that can be solved using routine procedures and should also learn to use a wide range of problem-solving strategies (e.g., heuristic processes such as drawing a diagram, considering special cases, working backward, solving a simpler problem, and looking for patterns and regularities) that can be useful in solving nonroutine problems.
Intrapersonal and Interpersonal Skills
Unlike skills in the cognitive domain, those in the intrapersonal and interpersonal domains are not particularly prominent in the mathematics curriculum reform documents. Historically the interpersonal and intrapersonal domains have been represented in research conducted on mathematics teaching and learning (McLeod and Adams, 1989; McLeod, 1992; Schoenfeld, 1992), but they have tended to receive less attention as curricular or instructional outcomes. The two prominent areas of overlap between 21st century skills and learning goals for school mathematics in these domains are self-regulation and motivation/persistence.
The theme of self-regulation is evident in the CCSSM standard of mathematical practice, “Make sense of problems and persevere in solving them.” The expectation is clear that students must learn to monitor and evaluate their progress when solving problems, and to change course if necessary. Within this CCSSM standard one also finds explicit attention to persistence, as the earlier quote illustrates. Students are expected to spend time examining a problem, considering pathways, reflecting on progress, and adjusting solution approaches rather than leaping immediately onto a solution path and then abandoning it at the first obstacle.
SCIENCE AND ENGINEERING
The Context: Evolution of National Standards in Science
National initiatives to outline disciplinary content standards for K-12 science education have undergone significant evolution over the past two decades. The American Association for the Advancement of Science’s (AAAS’s) reports Science for All Americans (American Association for the Advancement of Science, 1989) and Benchmarks for Science Literacy (American
Association for the Advancement of Science, 1993) and the National Research Council’s National Science Education Standards (National Research Council, 1996) were ambitious efforts to lay out systematic guidelines and standards for science literacy for K-12 education based on reviews of research by national panels of experts. More recently, in July 2011, the National Research Council released the NRC science framework (National Research Council, 2012), and Achieve, Inc., has been commissioned by the Carnegie Corporation to develop a full set of standards based on this framework. These standards are intended to be the science education counterpart of the Common Core State Standards in English language arts and mathematics, and it is expected that they too will be adopted in many states.
The following analysis of the correspondence between disciplinary standards for science education and 21st century skills is based primarily on the NRC science framework as well as on several recent volumes published by the NRC that review and synthesize current research on students’ learning and on curricular and pedagogical models in science. These reports include How Students Learn: History, Mathematics, and Science in the Classroom (National Research Council, 2005); America’s Lab Report: Investigations in High School Science (National Research Council, 2006); Taking Science to School: Learning and Teaching Science in Grades K-8 (National Research Council, 2007); and Exploring the Intersection of Science Education and 21st Century Skills (National Research Council, 2010).
Science Content and Process
One of the long-standing issues in science education has been the relative emphasis that should be placed on—and the nature of the relationship between—“content” (facts, formulas, concepts, and theories) and “process” (scientific method, inquiry, discourse). AAAS’s Project 2061 aimed to transform science education in the United States by placing a heavy emphasis on inquiry, often interpreted primarily as hands-on investigation, as a corrective to the overemphasis on isolated factual content common in so many science classrooms (American Association for the Advancement of Science, 1989, 1993). The National Science Education Standards, too, called for engaging students in inquiry, both to motivate their interest in science and to help them learn about science content and the nature of science (National Research Council, 1996).
As these calls for more inquiry in science classrooms have been acted upon in recent decades, certain trends have emerged that indicate a need to further articulate what is meant by scientific inquiry. One trend was that inquiry in some circles came to be associated primarily with “hands-on” science, often reflecting a commitment by education practitioners to a change in the pedagogy from passive, teacher-led instruction to active,
student-driven discovery. “Hands-on” laboratory activities can effectively support science learning if they are designed with clear learning goals in mind; are thoughtfully sequenced into the flow of science instruction; integrate learning of science content with learning about the processes of science; and incorporate time for student reflection and discussion (National Research Council, 2006). However, such approaches are not typical in American high schools. Instead, the calls for more inquiry sometimes resulted in a particular neglect of critical reasoning, analysis of evidence, development of models, and written and oral discourse associated with constructing and evaluating arguments and explanations—all aspects of inquiry that may be downplayed when “hands-on” activities are not carefully designed and scaffolded.
A second trend was the tendency to treat scientific methodology as divorced from content (National Research Council, 2007). Many students, for instance, are introduced to a generic “scientific method,” which is presented as a fixed linear sequence of steps, emphasizing experimental investigations, which the students are often asked to apply in a superficial or scripted way. This approach to the scientific method often obscures or distorts the processes of inquiry as they are practiced by scientists. Practices, such as reasoning carefully about the implications of models and theories; framing questions and hypotheses so that they can be productively investigated; systematically analyzing and integrating data to serve as evidence to evaluate claims; and communicating and critiquing ideas in a scientific community are vital parts of inquiry. However, they tend to be missed when students are taught a scripted procedure designed to obtain a particular result in a decontextualized investigation. Furthermore, these higher-level reasoning and problem-solving practices require a reasonable depth of familiarity with the content of a given scientific topic if students are to engage in them in a meaningful way.
Debates over content versus process are not in step with the current views of the nature of science. Philosophers of science and scientists themselves now view science as both a body of established knowledge and an ongoing process of scientific discovery that can lead to revisions in that body of knowledge (National Research Council, 2005). Science is seen as a fundamentally social enterprise that is aimed at advancing knowledge through the development of theories and models that have explanatory and predictive power and that are grounded in evidence. In practice this means that the content and the process are deeply intertwined. Similarly, as highlighted in Chapters 4 and 6, strategies involving higher-order thinking and problem solving tend to be domain specific and are best developed and practiced in a suitably rich content domain (National Research Council, 2005).
Understanding the Structure of Scientific Knowledge
In recent decades, our understanding of what constitutes an appropriate foundation of factual and conceptual knowledge in science has been further developed. Research in cognitive science has emphasized that sophisticated scientific knowledge is characterized by a rich, conceptually organized, well-connected, and fluently integrated set of representations (National Research Council, 2005, 2007). An important hallmark of these integrated webs or networks of knowledge is that the facts, concepts, theories, and procedures that are organized in this way can be meaningfully understood, usefully applied, and productively added to or further developed on an ongoing basis. In this respect there is significant congruence among how scientific knowledge is construed within the discipline, how it is construed within the NRC science framework, and in the committee’s definition of deeper learning as learning that can be successfully transferred and applied in new situations (see Chapter 4).
The development of sophisticated scientific knowledge involves simultaneous and mutually reinforcing learning of both content knowledge and process skills. For example, a review of science learning in grades K-8 proposed that students who are proficient in science (National Research Council, 2007, p. 2) have the following capabilities:
- Know, use, and interpret scientific explanations of the natural world.
- Generate and evaluate scientific evidence and explanations.
- Understand the nature and development of scientific knowledge.
- Participate productively in scientific practices and discourse.
Both of these reviews reflect a view of science as a body of knowledge as well as an ongoing process.
Current Science Instruction
Today’s K-12 science classrooms generally reflect neither the calls for more fully developed inquiry experiences in national science standards nor the research evidence on how students learn science. As in mathematics, the curriculum has been criticized as being “a mile wide and an inch deep.” The authors of Taking Science to School (National Research Council, 2007) offered this summary of K-8 science instruction: “Typical classroom activities convey either a passive and narrow view of science learning or an activity-oriented approach devoid of question-probing and only loosely related to conceptual learning goals” (p. 253). Large science textbooks cover many
topics with little depth, providing little guidance on how to place science in the context of meaningful problems. As teachers try to cover the broad curriculum, they give insufficient attention to students’ understanding and instead focus on superficial recall-level questions (Weiss et al., 2003; Weiss and Pasley, 2004). The patterns are similar to those observed in mathematics classrooms (Stigler and Hiebert, 1999).
Similarly, at the high school level, laboratory activities that typically take up about one science class period each are disconnected from the flow of science instruction. Instead of focusing on clear learning objectives, laboratory manuals and teachers often emphasize procedures, leaving students uncertain about what they are supposed to learn. Furthermore, these activities are rarely designed to integrate learning of science content and processes. During the rest of the week, students spend time listening to lectures, reading textbooks, and preparing for tests that emphasize many different topics (National Research Council, 2006).
Making matters worse, in the past decade time and resources for science education have often been cut back since science test scores have not counted in the formulations for whether schools are making adequate yearly progress under the NCLB legislation. This lack of emphasis has further limited the development of new capacity for high-level science instruction in K-12 schools and has thus also limited the potential impact of deeper learning goals within the state and national standards currently in use.
A limited number of small-scale studies (e.g., Herrenkohl et al., 1999; Kolodner et al., 2003; Klahr and Nigam, 2004; Krajcik et al., 2008; Cobern et al., 2010), reviews and syntheses (e.g., Linn, Davis, and Bell, 2004; Mayer, 2004; Kirschner, Sweller, and Clark, 2006), and meta-analyses (Minner, Levy, and Century, 2010) of thoughtfully implemented science instruction have shed some light on the current debates about the most appropriate pedagogical practices for science teaching and learning. The current synthesis based on available evidence does not dictate a particular pedagogical approach as uniformly superior. Scaffolding, modeling, guided inquiry, explicit instruction, individual study and practice, computer-mediated learning, and group problem solving and discussion have all been shown to be effective in various circumstances. The choice of instructional strategy often depends on the particular goals of a specific lesson or unit (National Research Council, 2000, 2007). As in other domains of learning, the research base indicates that one rarely gets something for nothing: If we want students to be skillful at reading and interpreting scientific materials, engaging in both written and oral scientific discourse, working fluently with quantitative data, constructing models, and problem solving effectively with peers, then we must give them the particular opportunities, models, and guidance needed to develop each of those sets of skills.
The Framework: Relating Scientific Practices and Concepts
The NRC science framework uses the term “practices” (in the plural) instead of process or skills to capture (1) the essential integration of knowledge and skills in action, and (2) the variety of activities, competencies, and dispositions involved in doing science productively, including habits of reasoning, discourse norms of communities and institutions, attitudes, values, epistemological understanding, and recognition of multiple methodologies (e.g., observation, field work, and modeling, in addition to laboratory experiments). The authors contrast this diversity with the thin procedural treatment of a single uniform “scientific method” that is commonly presented in science classrooms. They also note that modeling, communication, critique, and evaluation require particular attention and experiences to cultivate and that these experiences are often lacking in approaches that emphasize the hands-on aspects of inquiry as well as those that focus too narrowly on manipulating and controlling variables.
An overarching goal expressed in the NRC science framework is to ensure that all students—whether they pursue advanced education and careers in STEM fields or not—“possess sufficient knowledge of science and engineering to engage in public discussions on related issues; are careful consumers of scientific and technological information related to their everyday lives; [and] are able to continue to learn about science outside school” (National Research Council, 2012, p. 1). To these ends, they should have sufficiently deep understanding of core concepts in science, such as matter, energy, forces, earth and solar systems, organisms, and ecosystems, to think productively and to avoid common myths and misconceptions. They should also have sufficient experience with and understanding of a spectrum of scientific methods, including experimental, observational, and modeling approaches, to be able to evaluate and critique the quality and completeness of the available evidence and the relative degrees of certainty or uncertainty associated with it.
The NRC science framework is unequivocal in stating that the practices of science are inextricably tied to both learning and doing science. Science practices cannot and should not be taught in isolation, and, as new science standards based on the framework are developed, the practices should be infused throughout the standards for content knowledge. Participating in these practices is intended to simultaneously advance students’ understanding of scientific methods, of the nature of science, of applications of science, and of particular foundational scientific concepts. In comparing the abilities described in the NRC science framework with 21st century skills, a key point to note is that the area of greatest overlap is found in the science and engineering practices. By considering how the framework connects disciplinary content to practices in this area of overlap, we can gain insight
both into the meaning of “deep” in deeper learning and into certain clusters of 21st century skills.
The NRC science framework makes several important assertions about science and engineering education: (1) that disciplinary knowledge and skills (as exemplified in the “practices”) are essentially intertwined and must be simultaneously coordinated in science and engineering education; (2) that engaging in the practices of science and engineering advances students’ understanding of the nature of scientific knowledge, the variety of methodologies used in science and engineering, and areas of meaningful application; and (3) that participating in science or engineering practices also affects disciplinary learning by engaging students’ interest and increasing their motivation.
This argument that engaging in science and engineering practices is necessary and beneficial for learning disciplinary content is noteworthy because such a connection is not made in a strong way within current frameworks of deeper learning and 21st century skills, such as the Hewlett Foundation’s description of deeper learning4 or the Partnership for 21st Century Skills framework.5 These formulations generally note the importance of learning in core academic disciplines but give no guidance as to how or whether the learning of disciplinary content connects to the development of the other 21st century skills. The framework thus provides a rationale for connecting the “deep” learning of disciplinary content in science and engineering with at least some 21st century skills.
Organization of the NRC Science Framework
The NRC science framework includes engineering as well as science and notes that while the two disciplines have distinctly different goals, they share important features, such as reasoning and problem-solving processes, the testing and evaluation of outcomes and products, and the use of cognitive tools, such as analogical reasoning, systems thinking, and mental and physical models. In what follows the comments about science teaching and learning are generally intended to apply to engineering education as well. Where a distinction between science and engineering education seems important, it is noted.
The science framework is laid out in three dimensions, which are conceptually distinct but integrated in practice in the teaching, learning, and doing of science and engineering. The three dimensions are
4See http://www.hewlett.org/programs/education-program/deeper-learning for description [April 2012].
- core disciplinary ideas,
- crosscutting concepts, and
- scientific and engineering practices
Core Disciplinary Ideas
One goal of the revision to the National Science Education Standards was to reduce the long catalog of factual knowledge students are expected to master in order to place a deeper and more sustained focus on a much smaller set of core ideas that have broad importance across scientific disciplines and that are key for developing more complex ideas. Drawing on recent research on cognition, development, and learning in science,6 the new framework adopts a “learning progressions” approach to the core disciplinary ideas. In this approach, the learning standards are organized as integrated, continuous progressions of ideas that increase in sophistication over multiple years, from the early elementary grades through high school. The core ideas are grouped according to life sciences, earth and space sciences, physical sciences, and engineering and technology.
The NRC science framework identifies seven crosscutting concepts, which are important scientific concepts that bridge across multiple disciplines. They include patterns; cause and effect; scale, proportion, and quantity; systems and system models; energy and matter; structure and function; and stability and change.
Scientific and Engineering Practices
The NRC science framework conceptualizes practices as occurring in and connecting across three “spaces”:
- Investigation and empirical inquiry, in which the dominant practices are observing phenomena, planning experiments and data collection, deciding what and how to measure, and identifying sources of uncertainty. This space involves interaction with the natural or physical world.
- Construction of explanations or designs, a conceptual theory-building space, focused on developing hypotheses, models, and solutions.
6A comprehensive list of research references is included in an appendix that accompanies the NRC science framework.
- Evaluation space, focused on analysis, argument, and evaluation, in which the dominant practices are the analysis and construction of arguments and the critique of fit of evidence in relation to predictions (science) or of design outcomes to constraints and goals (engineering).
Eight key practices, which collectively span these spaces, are highlighted in the framework. Each is fairly richly described, so they are perhaps best thought of as complex activities rather than discrete skills. The key practices are as follows (National Research Council, 2012, p. 42):
- Asking questions (for science) and defining problems (for engineering)
- Developing and using models
- Planning and carrying out investigations
- Analyzing and interpreting data
- Using mathematics, information and computer technology, and computational thinking
- Constructing explanations (for science) and designing solutions (for engineering)
- Engaging in argument from evidence
- Obtaining, evaluating, and communicating information
While the three dimensions of the NRC science framework (i.e., core disciplinary ideas, crosscutting concepts, and science and engineering practices) and the way in which they are conceptually organized do not map in a tidy way to 21st century skills, there is significant overlap. Furthermore, the framework allows (indeed, forces) distinct discipline-based interpretations of what some of these skills mean in the context of science education.
In the Taking Science to School report (National Research Council, 2007), an expert committee identified four strands of science proficiency: knowing, using, and interpreting scientific explanations of the natural world; generating and evaluating scientific evidence and explanations; understanding the nature and development of scientific knowledge; and participating productively in scientific practices and discourse. There are significant similarities between these strands for scientific proficiency and the framework’s three-dimensional organization, and the framework authors explicitly cite many of the findings summarized in Taking Science to School as the basis for similar recommendations. The framework is more detailed and specific than the Taking Science to School report in addressing the knowledge and practices students need to develop over the K-12 span.
The framework also makes important connections to other disciplines—most notably English language arts and mathematics. The crosscutting
concepts include a special focus on the mathematical concepts of scale, quantity, and proportion, with the observation that scientific systems and processes span remarkable ranges of magnitudes on dimensions of time (e.g., nanoscale to geologic time) and space (e.g., atoms to galaxies). Students need to be fluent with systems of measurement for different types of quantities, with ratio relationships among different quantities, and with the relative magnitudes associated with various scientific concepts and phenomena. They also need to be able to create, interpret, and manipulate a variety of representations for quantitative data.
Similarly, the framework emphasizes the importance of reading, writing, and speaking skills in science and engineering. It notes that scientists and engineers typically spend half of their working time reading, interpreting,
An Example of Deeper Learning in Science
Many of the elements of the vision for science education outlined in A Framework for K-12 Science Education are currently uncommon in science instruction in U.S. classrooms. These include the sustained development of a smaller set of core disciplinary ideas over longer periods of time, the cultivation of reasoning and problem-solving skills even in earlier grades, attention to scientific communication (both written and oral) that explicitly involves developing explanatory theories and models and using data as evidence to construct and evaluate explanations and arguments, and development of an understanding of the nature of scientific knowledge. What might this look like as realized in the classroom?
One particularly rich illustration comes from the work of Herrenkohl et al. (1999) who conducted a study of an extended unit of science instruction with third through fifth graders investigating sinking and floating. Over a period of 10 weeks, students worked in small groups to carry out a series of investigations based on cognitive research on the conceptual pathway that students follow in coming to understand when and why various objects will sink or float (Smith, Snir, and Grosslight, 1992; Smith et al., 1994). Conceptual development in this domain involves understanding and relating concepts of mass, volume, density, and relative density and is known to be conceptually challenging for many students. Students’ investigations were carefully scaffolded to support reasoning practices in science and were also interspersed with teacher-guided whole-class discussions in which students gained experience communicating, monitoring, and critiquing their own thinking and the thinking of their peers as they developed, tested, and evaluated theoretical explanations for the phenomena they were observing.
The team of researchers, along with the classroom teachers, incorporated a number of instructional tools and practices. As students conducted their investigations, they were introduced to explicit strategies in science, including predicting
and producing text. As noted above, the integration of literacy activities in disciplinary contexts provides students with opportunities to master the particular challenges posed by disciplinary materials. In science, for example, texts often include unfamiliar vocabulary and complex sentence structures and are also often multimodal, incorporating diagrams, tables, graphs, images, and mathematical expressions. Students must also learn discourse norms for discussion and critique in science—discerning, for instance, that a scientific “argument” is not the same thing as an interpersonal disagreement (see Box 5-4). Varying interpretations are adjudicated through reasoning with evidence, and changing one’s mind because of convincing evidence presented by a peer does not mean that one “lost the fight.”
and theorizing, summarizing results, and relating predictions and theories to the results obtained. Through classroom discussions and repeated opportunities to practice these science strategies, students came to be able to distinguish between predictions and theories, to develop theory-based explanations of their observations, and to use evidence to evaluate their theories, rejecting some and refining others. During whole-class discussion, as small groups reported on their work, students also became experienced at taking on several “audience roles,” taking responsibility for checking their peers’ predictions and theories; summarizing results; and assessing the relation between the reporters’ predictions, theories, and results. Public documents in the classroom, such as a theory chart used to help students track the development of their thinking over time, and a questions chart, which they used to catalog good questions for the audience to ask reporters, were used to scaffold students’ awareness of how scientific thinking and knowledge develop and change over time and of the kinds of strategies that lead to progress.
The researchers described their approach as “sociocognitive,” and we note that it requires students to develop and practice strategies from the cognitive, interpersonal, and intrapersonal domains. Students learned to apply explicit reasoning and planning strategies for designing, conducting, and interpreting their investigations. They also became better able to monitor their thinking and to recognize when their ideas were or were not well developed or justified. They also became more comfortable with scientific discourse, learning not to become defensive when questioned by peers and learning the norms and expectations for scientific reasoning and discussion. Results from coded videotapes of classroom activities and discussions and from pretests and posttests indicated that students’ notions of scientific theorizing and their ability to engage in it evolved significantly, as did their conceptual understanding of the phenomena of floating and sinking.
SOURCE: Created by the committee, based on Herrenkohl et al. (1999).
Relating the NRC Science Framework to Deeper Learning and 21st Century Skills
We asked how, from the point of view of the framework, a proposed 21st century skill might be characterized within science and engineering and what degree of support the framework would provide for incorporating such a skill as part of teaching and learning in the discipline. Our findings are shown in Figure 5-3 and discussed below.
Drawing on the framework (as well as other sources mentioned above), we found the strongest correspondence—and hence the strongest support—in the cluster of 21st century skills categorized as “cognitive.” In particular, critical thinking, nonroutine problem solving, constructing and evaluating evidence-based arguments, systems thinking, and complex communication
FIGURE 5-3 Overlap between science standards framework and 21st century skills.
SOURCE: Created by the committee.
were all strongly supported in the framework and were construed as being central and indispensible to the disciplines of science and engineering.
However, each of these abilities tends to be embodied in particular ways in the science and engineering standards. For example, “complex communication” entails mastering the discourse norms for framing and communicating scientific questions and hypotheses or engineering problems and design proposals. The framework emphasizes communicating findings and interpretations clearly and participating constructively in peer critiques and reviews as well as the capacity to engage in critical reading (including quantitative comprehension) of discipline-based texts, data archives, and other scientific information sources.
Similarly, “constructing and evaluating evidence-based arguments” is framed in terms of generating, evaluating, and testing scientific hypotheses or engineering designs. In particular, the framework highlights the importance of distinguishing scientific from nonscientific questions; distinguishing evidence from claims; and evaluating the reliability, completeness, and degree of uncertainty associated with evidence and interpretations.
In some respects, the intrapersonal category is the most difficult domain of skills to evaluate. Metacognitive reasoning about one’s own thinking and working processes and the capacity to engage in self-directed learning throughout one’s lifetime receive explicit support in the framework. However, the degree of support for such factors as motivation and persistence, attitudes, identity and value issues, and self-regulation (if construed as a person being punctual, organized, taking on responsibility, and so forth) is weaker or more indirect. At the same time, though, there is no obvious conflict or lack of compatibility between the vision of science education presented by the framework and these 21st century skills. The NRC science framework is not mute on such topics as valuing diversity, being a conscientious and self-motivated learner, or appreciating the intellectual values of science and engineering. Rather, it seems to situate the issues as something other than disciplinary learning goals for individual students. Issues of diversity and equity, for instance, are treated as goals that are important for the communal enterprise of science and its relation to societal needs and values. Personal qualities, such as engagement and persistence, seem to be viewed as means that can help support successful science learning for more students, rather than as stand-alone end goals or outcomes of science education.
To some degree, the difficulties encountered in aligning intrapersonal and interpersonal skills with disciplinary standards may be ontological in nature: The science and engineering standards are intended to characterize
a set of knowledge and skills that students are expected to master during the K-12 years, while at least some of the deeper learning and 21st century skills are intended to characterize desired qualities of a person as a lifelong learner, as a citizen, and as a member of the workforce (Conley, 2011). In this respect, some of these skills would be expected to be complementary to, rather than overlapping with, disciplinary standards—a view that is compatible with the vision presented in the NRC science framework.
Within the domain of interpersonal skills, the framework provides strong support for collaboration and teamwork. A pervasive theme in the framework is the importance of understanding science and engineering as norm-governed enterprises conducted within a community, requiring well-developed skills for collaborating and communicating. In addition, the framework supports adaptability, construed as the ability and inclination to revise one’s thinking or strategy in response to evidence or peer review.
There is less attention paid to interpersonal social skills and values, such as cultural sensitivity or valuing diversity. While these are not seen as being in conflict with learning about and practicing science and engineering, they are not strongly supported as explicit learning goals for students in the disciplines. Indeed, these almost seem to be emphasized more as important skills for teachers to use in engaging diverse students in science learning than as disciplinary learning goals for the students themselves.
Several important observations emerge from our mapping of science and engineering standards with 21st century skills. First, some of these skills correspond with the disciplinary standards, and standards documents value these skills highly as important for learning and practicing science and engineering. However, the standards documents value specific interpretations of these skills from a disciplinary perspective, and there may be other interpretations of these skills that differ substantially from these disciplinary interpretations. For example, there is very strong support in the framework for “complex communication” when viewed as sophisticated discourse within the discipline or as critical reading and quantitative literacy skills; however, there is considerably less support for complex communication skills if they are construed as involving interpersonal sensitivity, cultural awareness, or negotiation and persuasion skills.
Another key observation is that, aside from the possible divergence of interpretations just mentioned, there is little in statements of 21st century
skills that would be viewed as directly in competition with or incompatible with standards for teaching and learning science and engineering. Of course, there is always room for conflict over relative emphasis and the competition for ever-scarce classroom time, and there would also likely be some potential for conflict depending on certain choices of pedagogical strategies, which are not strictly dictated by the framework. We note, however, that one theme of a recent National Research Council workshop (National Research Council, 2010) was that those science education initiatives that aligned particularly well with 21st century skills tended to emphasize project-based and problem-solving approaches to curriculum and learning. The emphasis on the eight key practices in the Framework would converge in this direction as well.
CONCLUSIONS AND RECOMMENDATIONS
While we found substantial support for deeper learning and 21st century skills in the various standards documents and supporting research literature, we also found a certain degree of unevenness in their prominence and coverage. A cluster of skills, primarily from the cognitive domain, appeared as central in each of the three disciplines, although the particular interpretations of them varied from discipline to discipline. This set included critical reasoning, the ability to construct and evaluate arguments in relation to evidence, nonroutine problem solving, and complex communication (both written and oral) involving the discourse standards of the various disciplinary communities. However, the definitions of argumentation and standards of evidence differed across the three disciplines.
- Conclusion: Some 21st century competencies are found in standards documents, indicating that disciplinary goals have expanded beyond their traditional focus on basic academic content. A cluster of cognitive competencies—including critical thinking, nonroutine problem solving, and constructing and evaluating evidence-based arguments—is strongly supported in standards documents across all three disciplines.
Intrapersonal skills and characteristics, such as persistence, self-efficacy, self-regulation, and one’s identity as a capable learner, were treated more variably across the standards documents, although the research literature on teaching and learning in the disciplines provides some support for their importance. We note that the smaller degree of attention paid to noncognitive dimensions in the standards documents stands in contrast to the evidence discussed in Chapter 3, which indicates that they are important for larger educational and workforce goals, such as staying in school,
completing degrees, and attaining higher levels of education. However, we also observe that they may be less likely to be emphasized in disciplinary standards because they may be crosscutting competencies and thus not unique to or distinctively expressed within a given discipline.
- Conclusion: Coverage of other 21st century competencies—particularly those in the intrapersonal and interpersonal domains—is uneven. For example, standards documents across all three disciplines include cognitive and interpersonal competencies related to discourse structures and argumentation, but the disciplines differ in their view of what counts as evidence and what the rules of argumentation are. This uneven coverage could potentially lead to learning environments for different subjects that do not equally support the development of 21st century competencies.
Our review of the research on how the disciplines have characterized “deeper learning” and sought to foster it indicates that instruction for deeper learning is rare in current English language arts, mathematics, and science classrooms.
- Conclusion: Development of higher-order 21st century competencies within the disciplines will require systematic instruction and sustained practice. It will be necessary to devote additional instructional time and resources to advance these sophisticated disciplinary learning goals over what is common in current practice.
The committee’s review of research on learning goals in the three disciplines indicates that people in each of the disciplines desire to develop skills and knowledge that will transfer beyond the classroom. However, the goals for transfer are specific to each discipline. For example, the NRC science framework envisions that, by the end of twelfth grade, students will be prepared “to engage in public discussions on science-related issues, to be critical consumers of scientific information related to their everyday lives, and to continue to learn about science throughout their lives” (National Research Council, 2012, pp. 1-2). As we discuss further in Chapter 6, attempts to cultivate general problem-solving skills in the absence of substantive disciplinary or topical knowledge have not typically been effective. We speculate that there may be a mismatch between the expectations of employers in this regard and what is known about learning and transfer. It is an open question as to whether a student who becomes an adept problem solver across a variety of academic disciplines would be better able to transfer problem-solving abilities to new areas than a student who was strong in just one discipline, or whether particular kinds of instructional
practices and experiences in the K-12 setting would increase the likelihood of transfer of advanced skills across domains. More research is needed to address these questions.
- Conclusion: Teaching for transfer within each discipline aims to increase transfer within that discipline. Research to date provides little guidance about how to help learners aggregate transferable knowledge and skills across disciplines. This may be a shortcoming in the research or a reflection of the domain-specific nature of transfer.
- Recommendation 2: Foundations and federal agencies should support programs of research designed to illuminate whether, and to what extent, teaching for transfer within an academic discipline can facilitate transfer across disciplines.