7

Implications for Learning in School

What does the research we have discussed mean for learning in school? Our charge was to build on HPL I¹ with a synthesis of research on learning from birth through adulthood, in both formal and informal settings. This body of work has implications for the work of educators in schools, particularly those who teach at the kindergarten to twelfth grade (K-12) levels.

In previous chapters, we discussed the cultural nature of learning and the growing recognition that culture fundamentally shapes all aspects of learning, from the wiring of the brain to the way that communities and societies organize learning opportunities. We saw that there are many types of learning, which are supported by a suite of cognitive processes that the learner needs to coordinate and organize. We examined research on knowledge and reasoning, which indicates that developing expert knowledge brings both advantages and biases and that simple accumulation of knowledge is insufficient for tackling sophisticated learning tasks and approaching novel problems and situations. Finally, we described how an individual’s beliefs, values, interests, and identities play an integral role in learning and are themselves shaped by the learner’s experiences at home and in their communities.

All of these insights have implications for the way schools and classrooms are organized. In this chapter, we draw on findings from previous chapters to consider four implications for K-12 educators. First, we consider why attention to the cultural nature of learning is critical to the quality of every learner’s educational experience and examine research that illustrates specific impli-

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¹ As noted in Chapter 1, this report uses the abbreviation “HPL I” for How People Learn: Brain, Mind, Experience, and School: Expanded Edition (National Research Council, 2000).

cations for instruction. Second, we briefly describe current thinking about how learning in different academic content areas requires approaches that take into account both general findings about learning and subject-specific differences. Third, we discuss instructional approaches that both engage and empower learners. Finally, we consider how understanding of the processes of learning has been brought to bear on the design of educational assessment.

CULTURE AND LEARNING IN SCHOOL

The findings in HPL I remain valid today. However, as we discussed in Chapter 2, work from a variety of fields has contributed to a more nuanced understanding of the cultural nature of learning. The authors of HPL I recognized the importance of considering how culture influences knowledge transfer, noting, for example, that “school failure may be partly explained by the mismatch between what students have learned in their home cultures and what is required of them in school” (National Research Council, 2000, p. 72). What has since emerged from synthesis of work in fields including anthropology, cultural psychology, cognitive science, and neuropsychology is recognition of the cultural nature of learning and development for all learners and throughout life. For educators, this is important because the influences of environment and culture, from the molecular level to that of the broadest social and historical trends, affect what takes place in every classroom and every student. The characteristics of the learning environment, of educators, and of the students themselves are all shaped by their cultural context.

In Chapter 2, we explained that taking a sociocultural view of learning means taking into account the social, emotional, motivational, cognitive, developmental, biological, and temporal contexts in which learning occurs. In short, the study of learning is the study of the relationships between learners and their environments. If taken seriously, these ideas can influence education practice in very specific ways. Ideally, educators play a key role in determining the nature of the learning experiences available to their students, and they can also shape their students’ inclination and capacity to take advantage of their learning environments.

A thorough review of the theoretical and research literature on the role of culture in education would require at least another book-length report. We note here that for some students the culture and practices of school are not markedly different from those they experience outside of school, while for others going to school is a cross-cultural experience that can bring challenges. Thus, we highlight a few points about school and classroom contexts that illustrate the fundamental importance of attention to culture in providing all students an equitable opportunity to learn and for redressing opportunity gaps (Ladson-Billings, 2006).

When learners tackle a new task, they bring a wealth of previous knowl-

BOX 7-1 Do Students Have a Dominant Learning Style?

edge and personal experience to the learning context. They often seek an entry point into the new material by attempting to connect to what they already know and to leverage existing strengths (e.g., knowledge and experience). Because learners share some experiences, knowledge, and goals but also bring unique perspectives, experiences, strengths, and skills, there will be variation in how learners engage with new tasks and demonstrate their learning (see Box 7-1). Learning happens as people move in and across the practices of everyday life (including home, school, and neighborhood), and people apply all sorts of learning as they navigate new situations and problems.

Optimal learning environments support this productive variation among learners in part by providing room for learners to interpret tasks and assessments in ways that broadly leverage their individual strengths, experiences, and goals. A theoretical framework for this idea was put forward in a landmark 1995 paper (Ladson-Billings, 1995). Since that time, educators and researchers have explored what it means to make teaching and learning relevant and responsive to the languages, literacies, and cultural practices of all students (see, e.g., discussion of culturally sustaining pedagogy in Paris [2012]).

School and Classroom Contexts

Culture shapes every learning environment and the experience of each learner within that environment: learners who find the classroom environment unfamiliar, confusing, unwelcoming, or unsupportive will be at a disadvantage. It has been well established elsewhere that attention to children’s and adolescents’ opportunity to learn—which is in large part determined by their

educational environments—is critical to addressing disparities among population subgroups (see, e.g., Boykin and Noguera, 2011; Duncan and Murnane, 2011; Reardon, 2011; Tate, 2001). Opportunity to learn is a multidimensional construct that encompasses not only the content available to students but also what teachers do in the classroom, the activities in which students engage, and the materials and other resources that are used to support instruction. These features of the learning environment are shaped by the broader culture in which educators are prepared and policy decisions are made—and those factors, in turn, are shaped by even broader cultural influences.

Learning Environments

A learning environment is structured to promote particular ways of engaging in a specific set of activities, and the features of every learning environment reflect the cultural context in which it is situated. A classroom’s culture is reflected in, for example, its physical features; the placement of chairs and desks or tables, the materials on the walls, and the resources available for use and reference all send signals about what is expected. Activities are structured to facilitate learning in a particular way in specific knowledge domains. The artifacts present in the room reinforce values, and researchers have suggested that cultural artifacts can have powerful cumulative effects on both adults and children (Azevedo and Aleven, 2013; Bell et al., 2012; Delpit, 1995).

One small example of this can be seen in the displays of the alphabet illustrated with animals (aardvark to zebra) that are ubiquitous in preschool and elementary classrooms. These educational resources, which are likely to show the animals as stylized representations or human-like characters—rather than in their natural habitats—reflect a particular cultural orientation. If the animals were shown in their typical habitats and engaged in natural behaviors, these kinds of representations might well encourage children to think “ecologically.” These sorts of subtle factors may affect how children organize their knowledge about animals (Medin and Bang, 2013; Winkler-Rhoades et al., 2010).

As another example, Bang and colleagues (in press), examined cultural differences in the illustrations in children’s books that either were or were not written and illustrated by Native Americans. They analyzed several features of the illustrations: the subjective distance from the reader to the illustrated object, established by the framing of the illustration (standard voyeur versus up-close or panoramic); perspective angle (straight-on view versus viewed from above or below); and the use of devices to encourage perspective taking, such as an “over-the shoulder” view (see Libby et al., 2009, for evidence that these devices are effective). The Native American–constructed illustrations were more likely to have up-close views, included a greater range of angles and distances, and were more likely to encourage perspective-taking (often from the perspective of an animal actor). The illustrations not created by Na-

tive Americans predominantly took a voyeur perspective, placing the reader outside of the scene and looking in.

These differences in illustrations parallel cultural differences some have observed between Native Americans and European Americans in whether experience of nature is foregrounded (e.g., a walk in the woods) or back-grounded (e.g., playing baseball outdoors) (Bang et al., 2007). They also parallel differences some have observed between the two cultures in typical goals for children or grandchildren in relation to the biological world. A European American goal might be, “I want my children to know they must respect nature and have a responsibility to take care of it,” whereas a Native American goal might be, “I want my children to realize that they are a part of nature.” Cultural differences like these can have consequences for students who do not come from European American backgrounds and encounter a classroom that implicitly endorses European American perspectives.

There are also rules, explicit and implicit, to be followed in classrooms. They guide students’ sense about who can speak, when they can speak, and what are acceptable or valued forms of speech, as well as what it is appropriate to say (Lee, 2001). Students and teachers also bring to a culturally defined classroom context their own individual cultural meaning system, derived from their out-of-school experiences in homes, neighborhoods, and communities. Students not already familiar with the rules inherent in the classroom culture are at a distinct disadvantage, compared with those who are (Rogoff, 2003; Serpell and Boykin, 1994; Tyler et al., 2006).

Some research has explored the larger context of schooling and the structures and practices that characterize classroom and school environments. Researchers have proposed, for example, that the structures of rules, assignment of classes, and grading in secondary schools match poorly with adolescents’ needs for more space in which to make and take responsibility for decisions about actions and to practice self-regulation (Eccles and Midgley, 1989; Eccles et al., 1991, 1993a, 1993b; MacIver and Epstein, 1993). Research covering a broader age range suggests that ability grouping and other related practices may have negative effects on resilience and self-regulation (Blumenfeld et al., 1987; Guthrie et al., 1996; Urdan et al., 1998; Wilkinson and Fung, 2002).

Moreover, students who appear to be unmotivated may see themselves for various reasons as marginalized in a community (e.g., MacLeod, 1987, 1995; Willis, 1977). More recent work has examined three school phenomena that are related to delinquency (academic failure, suspension, and drop-out) at the elementary, middle, and high school levels (Christle et al., 2005). The researchers found that school characteristics, such as supportive leadership, dedicated and collegial staff, schoolwide behavior management, and effective academic instruction, helped to minimize the risk of delinquency. Furthermore, students who reported a sense of belonging and connection with school were less likely to fail, be suspended, or be expelled.

Negative Consequences of Bias

Much has been written in the past two decades about the subtle ways that unrecognized assumptions about cultural differences affect learning (see, e.g., Banks and McGee, 2010; Erickson, 2010). This effect of cultural differences may be extremely negative. For example, teachers’ unexamined biases regarding gender and race may influence their expectations and interpretations of even very young children’s behavior, as research on disparities in the use of serious disciplinary measures such as suspension and expulsion in preschool settings suggests (Gilliam et al., 2016). Variation in the application of such serious disciplinary actions across racial groups is well documented among older students and has been associated with teachers’ mindsets (Okonofua et al., 2016). As Erickson (2010, p. 34) noted, the way teachers “choose to frame cultural difference has a profound influence on students’ understanding of what is being asked of them instructionally and their motivation to learn.”

The effects of culturally based expectations may be even more subtle and potentially harmful. We have discussed in Chapter 2 and 3 evidence that observed differences in many cognitive processes and functions, such as attention and memory, have a cultural basis. Recent work by Heidi Keller (2017) has highlighted the extent to which expectations about learners’ development reflect unexamined assumptions that the pathways typical in middle-class western populations are the normal healthy ones, the benchmark against which children from other cultures should be assessed. This work suggests that “evaluating the development in one pathway with the principles and standards of the other is unscientific and unethical” (Keller, 2017, p. 833).

The effects of such expectations is illustrated by controversy over the relationship between the richness of a mother’s speech and her child’s vocabulary development and academic outcomes such as grades, a relationship known as the word gap (Huttenlocher et al., 2002). Efforts to encourage parents to talk more with their children (e.g., the Thirty Million Words Initiative²) have been based on this finding. However, it is important to recognize that speaking continuously to one’s child—which is typical among middle-class parents in the United States—is just one of many ways to foster learning (see Avineri et al., 2015). Children also learn through engaging in creative play on their own, interacting with others, and observing cultural norms (e.g., Lareau, 2011; Rogoff, 2003).

Shifting from “Deficit” to “Asset” Models

Learning in school may be facilitated if the out-of-school cultural practices of students are viewed as resources, tools, or assets. If the cultural

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² See http://thirtymillionwords.org [November 2017].

practices recognized and accepted in one context are recognized and accepted in another, that consonance will facilitate engagement and learning. This idea has sometimes been associated with a “deficit” model of cultural difference, in which consideration of cultural differences among students is conceived as a way to compensate for academic disadvantages that some groups may share. We want to highlight the importance of shifting away from this model to a view that each student brings a unique combination of assets to the classroom and that every student’s learning is fostered in an environment that takes those assets into account.

A key dimension of creating equitable classrooms involves building a classroom environment where all students’ ideas are valued. In such classrooms, teachers support students as they explicate their ideas, make their thinking public and accessible to the group, use evidence, coordinate claims and evidence, and build on and critique one another’s ideas (Michaels and O’Connor, 2012). Group norms of participation, respect for others, a willingness to revise one’s ideas, and equity are all critical elements of this kind of classroom environment (Calabrese Barton and Tan, 2009; Duschl and Osborne, 2002; Osborne et al., 2004; Radinsky et al., 2010; Sandoval and Reiser, 2004).

One way to integrate culture as a resource is the cultural modeling approach to classroom instruction (Lee et al., 2003). This model is designed to engage students from nondominant backgrounds by guiding them to see connections between their own cultural experiences and the disciplinary ideas and ways of thinking being taught.

In one study of cultural modeling, Lee (2006) investigated how African American students can be encouraged to apply their understanding of everyday narratives with which they were familiar (e.g., rap lyrics) to their reading of material being taught in class. Teachers who were able to explicitly make these links guided their students to focus on how readers figure out what texts mean. The students’ knowledge about the meaning of the everyday texts allowed them to act as interpretive authorities and then apply that experience in approaching other material. By making familiar home- or community-based practices visible in the classroom, this approach helps students feel comfortable with learning objectives and view them as accessible.

There is also evidence that when cultural practices are regarded as assets in the classroom, students’ motivation and achievement may increase (Boykin and Noguera, 2011). For example, researchers have found that many African American students prefer communal learning contexts (Dill and Boykin, 2000; Hurley et al., 2005), and when school instruction incorporates opportunities for students to work together, their learning can show striking improvements (Boykin et al., 2004; Hurley et al., 2005, 2009; Serpell et al., 2006).

The Funds of Knowledge framework, originally developed in the 1990s, has been an influential example of using detailed analysis of skills and knowledge students are familiar with to link their unique experiences to instruction

(Moll et al., 1992). This framework emerged out of collaborations between teacher-researchers and families of students living on the United States–Mexico border. Funds of knowledge, as described by Moll and colleagues (1992), are the valuable understandings, skills, and tools that students maintain as a part of their identity. Families have funds of knowledge from aspects of everyday life, such as fixing cars, working in a business, or building homes. Though often overlooked by teachers and the school community, students’ funds of knowledge can be used as valuable resources in the classroom if the teacher solicits and incorporates them in the classroom. More recent work has built on this idea, exploring how this practice can capture students’ imaginations and foster deeper understanding of domain knowledge (Lee, 2001; Rogoff, 2003) and how the skills, abilities, and ideas students have developed outside of school can be applied in a range of school contexts.

Another way to capitalize on the connections between cultural life and the classroom is to create third spaces: social environments that emerge through genuine dialogue between teachers and students. These environments are co-constructed by teachers and students and provide a space for students to elaborate on and incorporate their own personal narratives and experiences into the larger classroom space (Gutiérrez, 2008; Gutiérrez et al., 1995). These kinds of shared spaces can establish links between the types of knowledge and discourse (funds of knowledge) students experience outside of school and the conventional knowledge and discourses valued by schools (Moje et al., 2004). An ethnographic study of students in a middle school science classroom showed not only that students’ funds of knowledge can be valuable resources for making sense of school texts but also how often students needed to be prompted and encouraged to draw on these funds in classroom contexts (Moje et al., 2004). Another ethnographic study, of critical literacy among male African American high school students, illustrates this point (Kirland, 2008). In this study, students who explored themes of revenge, racism, xenophobia, and the social consequences of difference and intolerance through close reading of scenes from the Iliad and comic strips such as Batman and X-Men demonstrated rich and sophisticated understanding.

Research in out-of-school contexts has the potential to expand educators’ understanding of students’ repertoires of knowledge and skill. For example, Morrell (2008) documents how youth in under-resourced communities gained academic and other skills through research projects related to educational equity and youth empowerment. Gutiérrez (2008) describes a long-term project with youth from migrant farmworker backgrounds, which was designed to build their academic and personal goals. Pinkard and colleagues (2017) found similar benefits in a study of Digital Youth Divas,³ an out-of-school program

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³ See http://digitalyouthnetwork.org/project/digital-divas [November 2017].

that supports middle school girls’ interests in science, technology, engineering, and mathematics activities through virtual and real-world communities.

DISCIPLINE-SPECIFIC LEARNING

Academic disciplines each involve characteristic ways of thinking and intellectual challenges, and an important goal in both K-12 and postsecondary education is to develop students’ facility with the modes of thought in the subjects they study. Without becoming conversant with the academic language used within and across content areas, students cannot readily engage in the type of deep learning that will enable them to go beyond the memorization of facts (Gee, 2004). For example, scholars have identified what it means to “talk science” (Lemke, 1990) or to participate in “the discourse of mathematics” (Cobb and Bauersfeld, 1995; also see, e.g., National Research Council, 2005, 2007).

Goldman and colleagues (2016) conducted a “conceptual meta-analysis” in which they identified the reading, reasoning, and inquiry practices associated with the disciplines of literature, science, and history. They used the following five core constructs to characterize knowledge across disciplines:

1. Epistemology, that is, beliefs about the nature of knowledge and the nature of knowing
2. Inquiry practices and strategies of reasoning
3. Overarching concepts, themes, and frameworks
4. Forms of information representation, including different types of texts
5. Discourse practices, including the oral and written language used to convey information

Whereas each of these five constructs can be found across disciplines, the particular forms of a construct typical of a discipline—that is, the paradigms of the construct used in that discipline—differ from one to another. Therefore, knowing which forms of a construct are essential to the way a discipline organizes and conveys information helps educators teach in discipline-specific ways.

To illustrate, when learning history in a discipline-specific manner, students are supported in experiencing history as a process of investigation. Students might construct interpretations of historical events as they read primary and secondary texts, attending to the perspectives of the texts’ authors, the contexts in which the texts were generated, and the ways in which the texts corroborate, or fail to corroborate, one another (see Bain, 2006). Similarly, when learning science in a discipline-specific manner, students might generate and test explanations for scientific phenomena through investigations in which they collect and analyze data or interpret data collected by others

(Chin and Osborne, 2012). In literary reasoning, readers draw on a repertoire of beliefs, experiences, rhetorical knowledge, and knowledge of literature to engage in argumentation about the meanings of literary texts (Lee et al., 2016).

These variations across subject areas in the structure of knowledge, epistemologies, and disciplinary practices are as important to the design of effective learning experiences for students as the general principles of learning discussed in previous chapters. Indeed, the growing bodies of evidence related to learning in specific disciplines are supporting current efforts to improve K-12 education. These accounts of disciplinary learning are informed by insights from the learning sciences that becoming more proficient in a domain is not simply a matter of acquiring knowledge. Rather, learning in a content area involves a process of engaging in disciplinary practices that require learners to use knowledge in the context of discipline-specific activities and tasks.

A summary of promising approaches in each of the subjects taught in school is beyond the scope of this chapter. Several reports by National Academies study committees have summarized some of the major findings related to learning in the disciplines. These include a follow-on volume to HPL I titled How Students Learn (National Research Council, 2005) that explored learning in history, mathematics, and science; 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), Adding It Up: Helping Children Learn Mathematics (National Research Council, 2001b), and Mathematics Learning in Early Childhood: Paths Toward Excellence and Equity (National Research Council, 2011b). In the section below, we give a broad overview of learning in the disciplines of mathematics, science, and history drawing on these resources.

Mathematics

The components that constitute proficiency in mathematics were articulated in the National Academies report Adding It Up (2001b, p. 107). The five strands of mathematical proficiency are

1. Conceptual understanding, which refers to the student’s comprehension of mathematical concepts, operations, and relations
2. Procedural fluency, or the student’s skill in carrying out mathematical procedures flexibly, accurately, efficiently, and appropriately
3. Strategic competence, the student’s ability to formulate, represent, and solve mathematical problems
4. Adaptive reasoning, the capacity for logical thought and for reflection on, explanation of, and justification of mathematical arguments
5. Productive disposition, which includes the student’s habitual inclination to see mathematics as a sensible, useful, and worthwhile subject

These five strands are interwoven and interdependent in the development of proficiency in mathematics. This means that instruction in mathematics needs to address all five strands. Traditional instruction in mathematics, however, has typically focused on procedural fluency (National Research Council, 2001b). In order to develop mathematical proficiency as described above, significant instructional time needs to be devoted to developing concepts and strategies, engaging in discussions, and practicing with feedback (National Research Council, 2001b). Discussions in the classroom need to build on students’ thinking, and attend to relationships between problems and solutions and to the nature of justification and mathematical argument (National Research Council, 2001b).

Science

Similarly, a report from the National Research Council on learning science in kindergarten through eighth grade (National Research Council, 2007) described four strands of scientific proficiency.

1. Know, use, and interpret scientific explanations of the natural world
2. Generate and evaluate scientific evidence and explanations
3. Understand the nature and development of scientific knowledge
4. Participate productively in scientific practices and discourse

The four strands work together in the process of learning such that advances in one strand support and advance those in another. The strands are not independent or separable in the practice of science or in the teaching and learning of science (National Research Council, 2007).

In contrast to these four strands, traditional views of science learning focused on individual learners’ mastery of factual knowledge. As a result, lecture, reading, and carrying out pre-planned laboratory exercises to confirm already established findings were common instructional strategies (National Research Council, 2007, 2012a). Contemporary views of science learning and teaching instead emphasize engaging students in the practices of a science framework including asking questions, developing and using models, carrying out investigations, analyzing and interpreting data, constructing explanations, and engaging in argumentation (National Research Council, 2012a).

This kind of approach is reflected in the “Guided Inquiry Supporting Multiple Literacies” model, which engages early elementary school students in scientific inquiry and the use of scientific practices (Hapgood et al., 2004). In a classroom-based study, the researchers designed a scientist’s notebook

that was used to introduce children to the ways in which a scientist formulates research activities that could answer questions about a real-world phenomenon, models the phenomenon, systematically gathers and interprets data, tests his ideas with scientific colleagues, and revises claims based on challenges from peers and new data (Magnusson and Palincsar, 2005; Palincsar and Magnusson, 2001). They found that second-grade students taught with this approach improved their ability to use data as evidence, to interpret multiple representations, and to model scientific phenomena (e.g., the relationship between mass and momentum).

History

As noted in HPL I, learning history requires students to learn about the assumptions historians make when connecting events into a narrative. Students must learn to determine why particular events were singled out from among all possible ones as being significant; in doing so they understand not only the interpretive nature of history, but also that history is an evidentiary form of knowledge.

De La Paz and colleagues (2017) explored the use of an apprenticeship model to support eighth-grade students in historical writing, which they define as “an interpretation based on evidence that makes an argument about another place and time” (p. 2). They enlisted teachers in a large urban district to participate in the treatment condition and identified another group who participated in a comparison condition. The intervention began with teachers modeling and thinking aloud about the ways historians engage in historical thinking and writing. Students then engaged in such disciplinary practices as identifying and contextualizing primary sources, discussing and evaluating evidence, examining and developing historical claims and arguments, and writing narrative accounts of their work. The students’ writing products were evaluated for their general quality and for specific attributes of historical writing. On all writing measures, students in the treatment group outperformed students in the comparison condition; this finding applied to both higher-proficiency-level readers and those who struggled academically.

Stoel and colleagues (2015) developed a pedagogical framework to foster students’ ability to reason causally about history. The framework was designed to include five pedagogical strategies: (1) inquiry tasks, (2) social interaction, (3) situational interest, (4) teaching domain-specific strategies for history, and (5) epistemological reflections on history knowledge and reasoning. In this quasi-experimental study, students were taught explicit disciplinary practices through strategy instruction, concept instruction, and introduction to the epistemological underpinnings of history. For a control group of students, there was no explicit attention to historical thinking.

Both sets of students worked cooperatively in groups of three on an inquiry task in which they investigated the outbreak of World War I. The researchers found that both the students who were taught using the pedagogical framework and the control students gained first-order knowledge, defined as concrete and abstract knowledge about the past and the event being studied (VanSledright and Limón, 2006). However, only the students taught using the disciplinary strategies gained second-order knowledge: knowledge of the concepts historians use to construct narratives and arguments about the past.

Reisman (2012) designed a quasi-experimental study to measure the impact of a curriculum intervention for juniors and seniors in secondary school on historical reading, content knowledge, and reasoning. The students in the study, from five urban high schools, were taught using a curriculum called “Reading Like a Historian,” in which document-based lessons on a historical problem are the basis for student investigations. Each lesson followed a repeated sequence that included development of background knowledge on the topic, independent or small group reading and analysis of historical documents, and whole-class discussion of the documents and their meaning. As in other history-specific interventions, the study teachers explicitly taught corroboration, contextualization, and sourcing. Students in the treatment condition repeatedly applied these strategies in reading historical documents. They outperformed their control-group peers on several outcome measures, including measures of generic reasoning, reading comprehension, and historical reading (Reisman, 2012).

Nokes and colleagues (2007) tested the effect on students’ historical content learning and disciplinary approaches to reading in history of four interventions, which used (1) traditional textbooks and content instruction, (2) traditional textbooks with heuristics (teaching of strategies) for reading historical documents, (3) multiple texts and content instruction, or (4) multiple texts with heuristic instruction. The heuristic instruction used in interventions 2 and 4 explicitly guided students in the use of sources, corroboration, and contextualization. More than 200 students from eight classrooms in two high schools were distributed across the four treatment groups. After 3 weeks, students were assessed on their content knowledge and ability to apply discipline-specific approaches to reading in history.

The researchers found that students using multiple documents (interventions 3 and 4) made the greatest gains in content knowledge and the greatest gains in knowledge in the use of the heuristic while reading. Those who learned from and interacted with multiple texts learned more content, had higher reading-comprehension scores, and sourced and corroborated more often that the other two treatment groups in the study. The researchers emphasized that their study “highlights the importance of reading multiple texts to deepen content knowledge and facilitate the use of heuristics that historians typically use” (Nokes et al., 2007, p. 11).

As highlighted throughout this section, the different academic disciplines have characteristic ways of thinking and intellectual challenges that reflect the disciplinary differences in epistemology, discourse, representations, and practices. Acknowledging these distinctions is crucial for disciplinary-specific teaching.

ENGAGING AND EMPOWERING LEARNERS

A part of what is accomplished when educators attend to the culture of the classroom environment and the cultural perspectives students bring to their learning is that learners are better supported in taking charge of their own learning. The authors of HPL I touched on the importance of empowering learners. For example, they recommended using a metacognitive approach to instruction to help students take control of their own learning. They advocated that schools and classrooms be “learner-centered” places, where educators pay attention to learners’ attitudes and expectations about learning (National Research Council, 2000, p. 24). Many of the topics we have discussed in this report build on these ideas. Strategies we have discussed for fostering specific types and functions of learning are primarily ways of supporting the learner in actively making progress and improvements for herself.

In the committee’s discussions of learning types and the developing brain (Chapter 3), processes supporting learning (Chapter 4), knowledge and reasoning (Chapter 5), and motivation to learn (Chapter 6), we identified a number of specific implications of learning research for learners. A theme in these findings is that people learn better when they are aware of and direct their own learning and when they engage in learning activities that pose a challenge:

• In Chapters 3 and 4, we noted that teachers can guide learners in developing sound academic habits by offering rewards, that effective feedback targets the specific stage a learner has reached and offers guidance the learner can immediately apply, and that helping learners establish connections with knowledge they already have assists them in learning new material. We noted that when learners are guided in constructing conceptual models for themselves, such models are particularly useful in helping them understand and organize what they are learning.
• In Chapter 5, we noted that practices such as summarizing and drawing, developing their own explanations, or teaching others, all help learners remember information they are learning. In that chapter, we concluded that what effective memory strategies share is that they encourage learners to go beyond the explicit material, to enrich their mental representation of information, and to create organized and distinctive knowledge structures.

• In Chapter 6, we described ways to foster students’ feelings of autonomy, competence, and academic achievement, such as giving them the opportunity to make meaningful choices during instruction and, more generally, supporting their sense of control and autonomy.

Each of these points contributes to the general finding that educators can foster learning of many kinds and in many situations through strategies that provide enough support so that students can be successful but that also encourage and allow students to take charge in small and large ways of their own learning. In this section, we explore several ways of thinking about how learners become engaged and empowered. We first look briefly at the challenge of regulating one’s own learning. We then examine the evidence regarding some instructional strategies for engaging and guiding learners.

Self-Regulated Learning

HPL I noted that the capacity for self-regulation, like the beginnings of other aspects of metacognition, is evident in very young children and develops gradually with their growing knowledge and experience. As part of developing “strategic competence,” that report noted, children come to understand “how to go about planning, monitoring, revising, and reflecting upon their learning” (National Research Council, 2000, p. 112). The growing body of research in this area has, however, highlighted not only how difficult it is for people to regulate their own learning but also the corresponding value of training to improve this capacity.

Either accurately monitoring or controlling one’s learning poses its own distinct challenges. Learners need effective strategies to accomplish these things, and if metacognitive monitoring is inaccurate, then any decisions or choices the learner makes are likely to be off kilter. Even before HPL I was published, researchers had identified strategies that appear to support students in pursuing learning goals. These are ways in which learners process the content to be learned and the skills associated with learning to learn. Methods for teaching these strategies have been characterized as a learning-to-learn approach.

Recent meta-analyses provide overviews of research on learning strategies, including some that relate to self-regulation and others that do not. Hattie and Donoghue (2016) summarized the findings of 228 meta-analyses of the literature. They identified more than 400 learning strategies; for 302 of those strategies, a relationship could be demonstrated between their use and academic achievement outcomes. They found that the critical elements in the effective strategies were (a) the will to invest in learning, (b) curiosity and a willingness to explore what one does not know, and (c) the skills associated with coming to a deeper understanding of content. We note that these authors

adopted a very broad definition of “strategy” and included ways of managing the environment (e.g., providing student control over learning and lessons in time management), as well as participation structures (e.g., peer tutoring and collaborative/cooperative learning).

This work does not directly answer the question of how learners might be trained specifically to improve their capacity for self-regulated learning in ways that transfer beyond a particular study skill or strategy. A recent review summarized findings from studies that explored approaches to training for self-regulation in general (not just as it applies to learning), based on three different theoretical models of the primary drivers of self-regulation (Berkman, 2016). The three models focus on (1) strength (self-regulation is a strength or ability that can be deployed in any domain), (2) motivation (the key is developing the motivation or will to regulate one’s self), and (3) cognitive processes (the key is mobilizing cognitive functions by, e.g., developing a habit or changing beliefs about self-efficacy). The review found that interventions based on each of these models have shown benefits but only limited indications that they improve self-regulation in general.

The idea of teaching self-regulation is appealing to parents and educators, and numerous sources offer practical tips for doing this.⁴ A review article that examined research on teachers’ roles in teaching self-regulation concluded that active involvement in one’s learning is associated with positive academic outcomes and that teachers can promote this involvement by such measures as guiding students toward meaningful goals and strategies, monitoring their motivation, and providing useful feedback (Moos and Ringdal, 2012). These authors described a slightly different framing of models of self-regulation, reflecting the complexity of this active research domain, but they also highlighted important concepts such as forethought, performance control, self-reflection, cognition, and motivation. Regardless of the model, Moos and Ringdal (2012) suggested, the studies they reviewed support the idea that teachers can foster self-regulation in their students but need training to do so.

The research literature has not yet definitively identified training methods that have been shown to develop learners’ self-regulation capacity in a way that transfers beyond the skills directly trained. It has not thoroughly addressed questions about the role of culture in self-regulation processes, suggested by studies such as a recent one on self-concepts and socialization strategies in preschoolers from Cameroon and Germany (Lamm et al., 2017). However, as the author of the overview of research on training noted, “there is disparate yet tantalizing evidence that self-regulation can be improved with training”

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⁴ Examples can be found at https://www.naeyc.org/files/yc/file/201107/Self-Regulation_Florez_OnlineJuly2011.pdf [October 2017]; http://www.pbs.org/parents/adventures-in-learning/2015/11/games-that-teach-self-regulation [October 2017]; http://teacher.scholastic.com/professional/bruceperry/self_regulation.htm [October 2017]; https://iris.peabody.vanderbilt.edu/module/sr/cresource/q1/p02 [October 2017].

(Berkman, 2016, p. 454). We note some promising areas of research on this topic in Chapter 9.

Instructional Approaches for Engaging the Learner

As we learned in the preceding chapters, humans’ drive to understand is powerful. People have an innate capacity to impose meaning on their experiences. This propensity has the potential to be a powerful engine for learning if it is directed at suitable tasks and activities. On the other hand, if students are asked to engage in artificial, decontextualized tasks, they will develop coping strategies that make sense for those situations, but such strategies will simply amount to “doing school.” In this section, the committee looks briefly at ways to make school activities an “invitation to thinking.” Two instructional approaches intended to engage and challenge learners in the ways we have discussed—problem- and project-based learning and collaborative learning—have received considerable attention from researchers.

Problem- and Project-Based Learning

Problem- and project-based learning are strategies that promote learners’ engagement in learning challenges by focusing on long-term goals (Shah and Kruglanski, 2000). Problem-based learning began with efforts in medical education to support medical students in mastering a broad range of content knowledge and clinical practice. The term refers to a family of instructional approaches that focus less on the learning outcome than on a learning process organized around a question or problem. The challenge should be one that drives students to grapple with central concepts and principles of a discipline and to develop constructive investigations that resemble projects adults might do outside of school (Condliffe et al., 2016).

Research showing benefits of this approach includes work with students in elementary and middle grades and in a variety of settings, though primarily in social science and science classrooms (see, e.g., Ferretti et al., 2001; Halvorsen et al., 2012; Kaldi et al., 2011; Parsons et al., 2011; Rivet and Krajcik, 2004). In general, these researchers designed project-based units for students that engaged them in challenges, such as figuring out how machines make it easier to build big things or building a model aquarium, and involved them in a wide variety of activities. Researchers used a variety of methods to assess learning outcomes and identify features that were effective and to document positive results. However, Condliffe and colleagues (2016) have noted that while there is a growing research literature, most studies exploring the relationship between project-based learning and student outcomes are not designed in a way that supports causal inferences. They have urged caution in making claims about the efficacy of this approach. We note also that the

theoretical frameworks for problem-based learning are relatively abstract and thus do not easily support firm conclusions about how to design and implement problem-based instruction.

Researchers have also examined questions about implementing this approach. For example, there are questions about how much independence it is optimal for students to have, how much guidance and instruction teachers should provide, and whether a problem-based curriculum designed externally and provided to the teacher can yield the same benefits as one devised by the teacher (Barron and Darling-Hammond, 2008; Halvorsen et al., 2012; Thomas, 2000). This debate highlights the time and effort needed to design and execute this kind of instruction, as well as questions about the challenges of meeting required academic objectives with this approach (Herzog, 2007).

Collaborative Learning

Recognition that learning is not an isolated process that occurs solely in the individual learner’s mind has focused a number of researchers’ attention on the classroom environment as a learning community, and on how students’ interactions among themselves and with their teachers influence learning (see, e.g., Brown and Campione, 1995; McCaslin and Burross, 2011). One focus of this work has been on collaborative learning, in which peer members of a group each contribute their thinking as the group executes a complex task (e.g., revising and refining a scientific model), having been given the authority to divide the labor, develop relations of power and authority, and otherwise navigate the task demands (Roschelle, 1992). Many of the features associated with instruction based on collaborative learning align with the findings from earlier chapters we highlighted above. For example, students take responsibility for learning and are encouraged to reflect on their own assumptions and thought processes, facilitated by the teacher (Kirschner and Paas, 2001).

Several meta-analyses have examined the benefits of group learning across content areas (see Slavin et al., 2008, for studies specific to reading, and Slavin and Lake, 2008, for studies specific to mathematics; also see Johnson et al., 2000). Benefits that have been associated with cooperative learning, when contrasted with competitive or individualistic experiences, include positive social acceptance among group members, greater task orientation, greater psychological health, higher self-esteem, and increased perspective taking. These studies indicate that these benefits occur when the group members have mutual learning goals and each member feels responsible for the learning of every member (Johnson et al., 2000).

One particular form of cooperative learning, complex instruction, was designed to promote equity (Cohen and Lotan, 1997; Cohen et al., 1999). In this approach, the groups must be engaged in an open-ended task that is structured such that the participants are interdependent in completing the

task. The structure of the task positions students to serve as academic and linguistic resources to one another. An example of such a task would be pursuing the question “Why do people move?” by studying the experiences of various immigrant groups from Central and South America. This question is complex, and addressing it adequately requires assessing a broad range of potential explanatory factors, including relief from economic hardship, seeking political asylum, and the desire for a better life for oneself and/or one’s family.

Drawing on multiple resources (e.g., diaries, photographs, journals, news stories, texts), students construct an understanding of the multiple factors that influence immigrants’ choices. There is no one right answer; the task is both inherently uncertain and open-ended, both with respect to the responses the students will arrive at regarding the question and the processes they will use to generate their responses. Teachers are guided to pay particular attention to unequal participation of students. For example, the teacher can emphasize that the issues the group is considering are open to interpretation, that there is no one right answer, and that the work group must work to consensus regarding their group product. Furthermore, the activities call on multiple abilities, so that all students can contribute their respective strengths (e.g., in writing, graphics, or information gathering). Teachers also encourage students to explore alternative solutions and examine issues from a variety of perspectives.

Technology, particularly Internet-based resources, has opened up new avenues for collaborative learning and has provided new tools that have given rise to a research focus on computer-supported collaborative learning (Goodyear et al., 2014; Graesser, 2013). Research on collaborative learning that takes place through mediated Internet networks has pointed to the importance of the design of the learning experience and has suggested that successful tasks are those that (a) allow learners to take control of elements of the lesson (Kershner et al., 2010), (b) provide supports and multiple resources for making sense of and connecting complex ideas (Means et al., 2015), and (c) provide learners the means to share multiple representations of their learning (Scardamalia and Bereiter, 2006).

ASSESSING LEARNING

Assessment can drive the process of learning and motivation in a positive direction by providing feedback that identifies possible improvements and marks progress. It is most effective when the design of assessment reflects understanding of how people learn.

Assessments in K-12 education are directed to a range of audiences. Students need information about whether they are learning intended subject matter and skills. Teachers want to know whether their pedagogical approaches are helping individual students learn and helping their classes progress. Parents want to know whether their children are learning important

material. Stakeholders—from school, district, and state officials to leaders in postsecondary education, business, and the federal government—need this information to make policy decisions about areas of success, improvement, and needed actions. Assessments provide essential feedback for the improvement of learning and schooling.

Pellegrino (2014) found that assessments in K-12 educational settings are used for the following purposes:

• To assist learning in the classroom (also known as formative assessment). These assessments provide specific information about what an individual student has or has not learned about the material that has been taught. This information provides feedback to students about progress and helps teachers shape instruction to meet the needs of individual students.
• To assess individual achievement or level of competency after completion of a period of schooling such as at the end of a school year or end of course. These are also known as summative assessments.
• To evaluate programs and institutions and monitor learning at the school, district, state, or national level. These assessments are usually more removed from the classroom. They may reflect content of state standards, for example, rather than material covered in any particular classroom.

No one test or assessment can serve all purposes for all audiences. Although tests used for differing purposes can look quite different, they need to be aligned with each other in order to support learning. Systems of assessment need to be carefully designed using a broad range of assessment strategies tailored to these different purposes (National Research Council, 2001a, 2006, 2014).

Providing Feedback to Learners

Formative assessment conducted in classrooms can generate meaningful feedback about learning to guide choices about next steps in learning and instruction (Bennett, 2011; Black and Wiliam, 2009; Valle, 2015). When grounded in well-defined models of learning, assessment information can be used to identify and subsequently narrow the gap between current and desired levels of students’ learning and performance. It does so by providing teachers with diagnostic information about student misunderstandings and thus guiding teachers’ decisions about how to adjust instruction and students’ decisions about how to revise their work and adjust their learning processes.

An overall positive association between formative assessment and student learning has been found in both early influential reviews (Bangert-Drowns et

al., 1991; Black and Wiliam, 1998) and more recent meta-analyses (Graham et al., 2015; Kingston and Nash, 2011). The positive effects hold across different age groups, core school subjects, and countries (Chen, 2015).

However, not all kinds of feedback are equally effective (Ruiz-Primo and Li, 2013; Shute, 2008; Van der Kleij et al., 2015; Wiliam, 2010, 2013). Effective formative assessment articulates the learning targets, provides feedback to teachers and students about where they are in relation to those targets, and prompts adjustments to instruction by teachers, as well as changes to learning processes and revision of work products by students (Andrade, 2016). Research suggests that feedback is most effective when it is

• focused on the task and learning targets; that is, detailed and narrative, not evaluative and graded;
• delivered in a way that is supportive and aligned with the learner’s progress;
• delivered at a time when the learner can benefit from it; and
• delivered to a receptive learner who has the self-efficacy needed to respond.

Recent studies are contributing to a more nuanced understanding of the features of effective feedback. Feedback may address how tasks are understood and performed. It may address the self-monitoring, regulating, and directing of actions needed to accomplish the tasks, or provide personal evaluations of the learner (Hattie and Timperley, 2007). Because learners’ judgments about and capacity to manage their own learning are often imperfect, researchers have explored ways to use accurate feedback to help them learn (Andrade, 2016; Zimmerman, 2002). Examples include strategies for developing students’ self-evaluation skills in the context of mathematics and geography (Ross and Starling, 2008; Ross et al., 2002), and for guiding students in using peer- and self-evaluation together (Andrade, 2016; Topping, 2013).

Connecting Assessment to Evidence about How Students Learn

The National Research Council report Knowing What Students Know described three necessary components of a valid assessment system: “a model of student cognition and learning in the domain, a set of beliefs about the kinds of observations that will provide evidence of students’ competencies, and an interpretation process for making sense of the evidence” (National Research Council, 2001, p. 44). The model of student learning should be consistent with the research about how learners represent knowledge and develop expertise; it serves as the unifying basis for assessment design. The observations consist of identified assessment tasks or situations that will allow students to provide

evidence about their learning. The interpretation method provides a way to make sense of the observations and can range from statistical models to intuitive or qualitative judgements. “These three elements—cognition, observation, interpretation—must be explicitly connected and designed as a coordinated whole” (National Research Council, 2001, p. 2).

Ten years later, Brown and Wilson noted that most assessments still lacked an explicit model of cognition, or a theory about how students represent knowledge and develop competence in a subject domain. They argued that without a model of cognition, assessment designers, presumably including classroom teachers, are handicapped by largely implicit knowledge of how understanding develops, with no clear guidance on how to create meaningful assessments. However, recent promising developments have suggested ways that effective assessments can be designed to align with the growing body of evidence about how students learn.

Assessments Based on Learning Progressions

Also known as a learning trajectory, construct map, or construct model, a learning progression is a model of successively more sophisticated ways of thinking about a topic, typically demonstrated by children as they learn, from naïve to expert (National Research Council, 2007). Based on research and conceptual analysis, learning progressions describe development over an extended period of time (Heritage, 2009). For example, if the learning target is to understand that it gets colder at night because part of Earth is facing away from the sun, the students must first understand that Earth both orbits around the sun and rotates on its own axis. Box 7-2 shows a learning progression for this key concept, which positions the learners at levels 1 through 4.

Although learning progressions are often designed with state and federal standards in mind, they are more detailed than most standards, which do not include the significant intermediate steps within and across grade levels that lead to attainment of the standards (Heritage, 2011). Detailed descriptions of typical learning serve as representations of models of cognition that can guide instruction as well as the design and interpretation of the results of assessment. As shown in Box 7-3, learning progressions can also indicate common misconceptions students have about a topic.

Learning progressions provide a blueprint for instruction and assessment because they represent a goal for summative assessment, indicate a sequence of activities for instruction, and can guide the design of formative assessment processes that provide indicators of students’ understanding (Corcoran et al., 2009; Songer et al., 2009). Teachers and districts can design summative assessments with a learning progression in mind, as well as formative assessments that move learning ahead (e.g., Furtak and Heredia, 2014). Questions that target common misconceptions can be designed in advance and delivered

BOX 7-2 Scoring Rubric from Construct Map for Student Understanding of Earth in the Solar System

BOX 7-3 Diagnostic Item Based on Construct Map for Student Understanding of Earth in the Solar System

verbally or in writing, to individuals or to groups. For example, at a particular point in a unit on the Earth and the solar system, a teacher can ask questions designed to reveal student thinking in relation to a specific learning goal in a progression, such as “How long does it take the Earth to go around the sun, and how do you know?” The students’ responses to the questions provide insight into their learning and can guide the teacher’s next pedagogical steps.

Diagnostic questions can also be implemented in the form of multiple-choice items (Wylie et al., 2010). Briggs and colleagues (2006) demonstrated that well-designed multiple-choice items can provide teachers with diagnostic information about student understanding. When each of the possible answer choices in an item is linked to developmental levels of student understanding, as in the example in Box 7-3, an item-level analysis of student responses can

reveal what individual students and the class as a whole understand. For example, if one-quarter of the students in a class choose option D, which suggests that they believe that darkness is caused by the Earth moving around the sun once a day, the teacher might decide to provide opportunities for structured small group discussions between students who do and do not understand the day-night cycle. More intensive interventions can be implemented for the portion of the class who scored at level 2 or below by selecting options A, C, or E.

According to Pellegrino (2014, p. 70), “research on cognition and learning has produced a rich set of descriptions of domain-specific learning and performance that can serve to guide assessment design, particularly for certain areas of reading, mathematics, and science. . . . That said, there is much left to do in mapping out learning progressions for multiple areas of the curriculum in ways that can effectively guide the design of instruction and assessment.”

Evidence-Centered Design Approach to Assessments

Another widely respected contemporary model of assessment is evidence-centered design (Mislevy et al., 2003, 2006), which grounds assessments in empirical evidence of cognition and learning. In this model, assessment is considered to be a process of reasoning from evidence to evaluate student learning. The design process begins with examination of research evidence about both expert thinking and novice learning in a given subject area. All the elements associated with learning a subject are analyzed and documented and then used in refining the test during the design process. Assessment experts believe “tests based on such learning science research can better flag when students are successful in engaging in such learning processes, and when they are engaging in counterproductive practices”(Yarnall and Haertel, 2016, p. 3).

In the second, “observation,” step of this design process, items or tasks are chosen to try to elicit evidence of the desired knowledge and skills. The observations (based on student responses to these tasks) provide the data that developers need to make inferences about student performance. Unlike conventional test development methods, evidence-centered design starts with evidence about how learning happens in a domain and builds the test from that base. Figure 7-1 illustrates the three essential components of the overall design process. The first step in the process is “defining as precisely as possible the claims that one wants to be able to make about students’ knowledge and the ways in which students are supposed to know and understand some particular aspect of a content domain” (National Research Council, 2012a, pp. 52–53). (For more on learning progressions and evidence-centered design, as well as ways of ensuring the reliability and validity of assessments, see National Research Council, 2005, 2012a, 2014; Pellegrino, 2014.)

CONCLUSIONS

Our synthesis of research on learning supports five conclusions for learning in school.

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