Developmental Cognitive Science Goes to School

Nancy L. Stein, Stephen Raudenbush

• Publisher: Routledge
• Year: 2013
• ISBN:
  9781136871221
• Edition: 1
• Topic: Education
• Subtopic: Education General

This book addresses core issues related to school learning and the use of developmental/cognitive science models to improve school-based instruction. The contributors comprise a veritable "who's who" of leading researchers and scientists who are broadly trained in developmental psychology, cognitive science, economics, sociology, statistics, and physical science, and who are using basic learning theories from their respective disciplines to create better learning environments in school settings.

Developmental Cognitive Science Goes to School:

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• presents evidence-based studies that describe models of complex learning within specific subject-area disciplines
• focuses on domain knowledge and how this knowledge is structured in different domains across the curriculum
• gives critical attention to the topic of the ability to overcome errors and misconceptions
• addresses models that should be used to begin instruction for populations of children who normally fail at schooling.

This is a must-read volume for all researchers, students, and professionals interested in evidence-based educational practices and issues related to domain-specific teaching and learning.

1 Developmental and Learning Sciences Go to School

An Overview

Nancy L. Stein

Theories of Learning for School- and Domain-based Achievement

The chapters in this volume resulted from a conference held in the fall of 2007, in Chicago, supported by the Spencer Foundation. The purpose was to bring together scientists from different disciplines in order to address issues of learning across three domains: reading, science, and mathematics. Although government committees, books, and publications have attempted to address some of the issues related to learning in school, many of the issues, especially those related to science and mathematics, have not been addressed fully, especially in terms of obstacles that block successful school learning.

The same holds for advances to be made in reading (National Reading Panel Final Report, 2000; Trabass & Bouchard, 2000). Although we have made good progress in understanding the different components of reading, we have made less progress in understanding that success in reading, when decoding skills have been acquired, is a function of domain-specific knowledge. What works in one domain does not necessarily transfer to another domain. Learning is situated, and we need domain-specific models of the important concepts and ideas in each domain (Pitt, 1976).

In order to address learning issues across domains, we invited researchers from several different disciplines: psychology, sociology, computer science, cognitive science, education, and science. Although all contributors study learning, the ways in which learning was defined and studied differed dramatically as a function of the discipline. The communication across disciplinary boundaries was almost non-existent. Many of the reading researchers knew each other but did not know the contributors from math and science. The same held for researchers in math and science. Integrating approaches across disciplinary boundaries was essential.

The lack of interdisciplinary work is a major stumbling block for research on successful learning. We can teach reading by teaching science and math. We can teach core principles in science at much earlier ages if we understand and can teach specific mathematical concepts earlier than previously taught. If we are successful at using interdisciplinary approaches to school learning, we will be able to reconsider the way we teach the disciplines of reading, science, and mathematics. What is taught at each grade level, and how it is taught, need reconsideration.

The goals of the chapters in this book, then, were to address issues in learning and development that impact school-based instruction and public policy research. We focused on theories that advocate and produce evidence about learning and schooling in science, mathematics, and reading. As a result, six issues were approached and discussed throughout the volume:

1 ways in which children can engage in science and math learning earlier than currently taught;

2 successful strategies used in mathematics and science that also increase skill in reading and writing comprehension;

3 ways in which reading skills can be increased above the existing level of skill;

4 obstacles that prevent developmental and learning scientists from successfully carrying out innovative research in school settings;

5 myths that abort or stop learning attempts, especially in the scientific and mathematical domains;

6 ways in which ethnicity and culture impact children and their ability to carry out school learning.

Making Learning and Understanding Accessible to Young Children

A major theme throughout the book is centered on ways in which relatively complex concepts that underlie learning, especially in science and math, can be made accessible to young children and to the novice. The transitions from home to school in kindergarten, from second to third grade in elementary school, and from elementary to middle school are particularly important because new task demands and expectations are introduced at each of these stages, and children must master these task demands if they are to succeed in school. We focus on children from preschool through 14 years of age, some of whom experience failure at critical transition points, especially when their earlier development has been devoid of any real preparatory training. We ask questions about the types of learning that would better prepare children to succeed and advance in different disciplines, and when these types of learning should start.

The thinking and reasoning skills children bring to school learning are especially important. In general, successful children ask more why questions, seek explanations, express dissatisfaction when their questions are not answered, become more autonomous in their learning, monitor ways in which they learn, and accomplish learning outside of the classroom, with tutorial help from parents, grandparents, siblings, friends, and professionals. All of these factors play a critical role in determining how much and how fast children advance intellectually in school.

A content and conceptual coherence issue is germane, however, in addition to focusing on the acquisition of successful strategic skills. The concepts that children are taught, the order and depth with which they are taught, and the ways in which these concepts are embedded in specific content domains account for a significant part of the variance, almost 50 percent, in predicting successful learning (Stein, Anggoro, & Hernandez, 2010a). These content issues are especially important for science, mathematics, history, and social studies. We can teach children all of the sophisticated instructional strategies that we deem appropriate. If the relevant content is not present, and if the content is not organized in an “accessible” fashion, however, critical concepts will not be learned, despite all of our efforts to encourage and support learning. In other words, we can use all of the mapping activities possible, all of the questioning strategies, and all of the memory and retrieval strategies that are known to result in a deeper understanding of the materials (Newcombe et al., 2009; chapters 4 and 6). However, if critical concepts are left out, or if critical causal information and content are deleted, children will not learn the relevant concepts, no matter how well the instructional sessions are organized and no matter how bright and smart the children are (chapter 6).

Schmidt (Schmidt, Wang, & McKnight, 2005) has begun to show the importance of content in mathematical learning, but the truth is that content and its organization are as important in every other domain that exists. The content and organization overpower and control the success of teaching strategies. Trabasso and Bouchard (2000; 2001) showed that many different reading comprehension strategies work, as long as the instructor keeps an eye on the mastery of content. As Trabasso and Bouchard pointed out, however, the content of a lesson is rarely discussed, so we rarely get a glance at what is being learned by students and whether or not they can use their new knowledge in novel situations to understand complex ideas that require building on previous concepts. Brown (1990) also points out the relevance of specific knowledge and contexts in determining the power of a strategy. The omission of content and domain-specific knowledge, however, continues to be a problem for psychologists (e.g., Newcombe et al., 2009) who focus primarily on the power of generalized instructional strategies rather than on an awareness of the interaction between specific content and successful strategies.

Studying the role of conceptual content in a domain, such as math or science, is seriously constrained by the fact that public school science and math learning programs focus on content covered in standard-based state achievement tests. For example, each state decides what students should learn and be exposed to at each grade level. A yearly exam is then carried out for each specific discipline, where the items in the test supposedly correspond to the standards set by the state. The problem for researchers is that states disagree on what concepts and content should be taught at each grade level (Cutting & Scarborough, 2006), and not all of the state and the national exams are theory based (Klahr & Nigam, 2004). The most frequent strategy used to determine state standards is the use of an integrative meta-analysis of existing studies in each disciplinary area. The average age at which each concept is learned then becomes the criterion for assigning mastery of the content to a particular age.

Although empirical generalizations are always helpful, using a meta-analysis strategy can be disastrous for setting policy and improving skills in a domain. The derivation of age norms is always contingent on the types of tasks and data that currently exist. What the meta-analysis can never tell us is whether the chosen concepts are the appropriate ones or whether children can learn concepts earlier than thought, if other disciplinary knowledge is introduced. This issue is especially germane for science and mathematics (chapter 7), but it is also true for literacy, reading, and writing (Morphy & Graham, 2010). Critical learning tasks and content are often deleted or skipped over when school district personnel deem children to be slow learners, especially if they have a disability, such as dyslexia, or when they come from impoverished backgrounds (chapter 20).

A problem that compounds the introduction of new and more complex school content is that teachers are rarely trained in the new content or discipline. Many of the researchers studying science and math are also not trained in the disciplines, except at the very beginning levels on par with content introduced in elementary grades 1 through 3. Thus, a strong constraint on introducing innovative curricula in different disciplines is that both teachers and researchers need more training (chapter 13). Neither the instructors nor the researchers collecting data have the requisite content knowledge to either propose or judge innovative research.

The ways in which we deal with this lack of knowledge will prove critical to the success of future research in this area. Although disciplinary experts can act as collaborators, very few understand or have used theories of learning to motivate their contributions to curriculum development, especially at the elementary school level. And yet, the creation and innovation of curricular content is one of the most necessary outcomes in many different disciplines. Learning about certain topics and core concepts determines whether or not children will be able to take advantage of opportunities that require more difficult and complex learning. If children have not been exposed to the topics and themes that scientists consider essential, they cannot benefit from more advanced training.

Further, the issue of when concepts are introduced becomes another concern. Although adults learn new materials with success, the reality is that often they do not learn as well as children who have been introduced to a topic very early in development. The fields of mathematics and music, certain types of science, different types of language learning, both oral and sign, and the development of expertise in sports and dance are particularly prone to early development effects (Bloom, 1985; Feldman, 1993). Older children and adults can learn new domains, but the majority do not reach the levels of expertise that early learners reach. This phenomenon has been documented broadly (e.g. Bloom, 1980; Feldman, 2003), but has been ignored by the educational community, especially in math and science.

School learning is further complicated by the fact that we live in a multicultural society, and a significant and growing proportion of public school students possess widely varying levels of English proficiency. Anyone who has had sustained contact with education, teaching, and learning, especially in large urban centers, must consider the impact of education on children from different cultural and language environments. The presence of children from different cultural backgrounds impacts school policy, the choice of topics, and the school instruction that get carried out on a daily basis. In a growing number of public schools, government policy requires that children be given initial instruction in their native language. The focus, however, is on learning to read and speak English as a second language, so that successful transitions can be made to school environments where only English is spoken.

Learning to use a second language, however, is just one of the many hurdles that children must overcome when they enter school. The demands placed on children today, even those at the preschool and elementary school levels, are quite daunting. The new goal of teaching science in the elementary school years involves a new domain for teachers to master, even those teaching in private schools or in gifted programs. The necessity for ensuring that children receive a better science education has resulted from several factors: shifts in the job market toward technology and energy-related occupations, cognizance of the climate changes occurring on earth, and the awareness that the United States may not have a leading edge in the production and creation of scientists and scientific agendas to address problems of energy production and climate change. Introducing children to science and math as early as possible and finding ways to facilitate learning with technology must be considered. All of these concerns serve as the motivational force for this book.

Our focus on school learning is not a new endeavor. The educational centers created by the United States Department of Education in the mid-1970s (e.g., the Center for the Study of Reading at the University of Illinois, the Learning Research and Development Center at the University of Pittsburgh, Wisconsin Research & Development Center for Cognitive Learning) are good examples of the successes that educational scientists can accomplish when they turn their attention to instructional issues and the necessity of creating better learning environments. Each of the five Research and Development (R&D) centers established by the U.S. Office of Education had a major impact on schooling and learning and, in turn, each exerted a significant influence on the ways in which researchers carried out instructional studies. The impact of these R&D centers on the broader educational community can still be seen in conferences and volumes supported and published by the National Academy of Science.

In 1999, a book edited by John Bransford, Ann Brown, and Rodney Cocking, entitled How People Learn: Brain, Mind, Experience, and School, tried to summarize and address many issues relevant to this volume. One such issue focused on making different types of subject matter accessible to young children. Bransford et al. (1999) stated:

Learning research suggests that there are new ways to introduce students to traditional subjects, such as mathematics, science, history and literature, and that these new approaches make it possible for the majority of individuals to develop a deep understanding of important subject matter. This committee is especially interested in theories and data that are relevant to the development of new ways to introduce students to such traditional subjects as mathematics, science, history, and literature. (p. 6)

The agenda for this volume focused on this goal and attempted to make even deeper connections between domain-specific knowledge, basic learning, developmental and cognitive science, and classroom learning. Although many issues discussed in the last 30 years remain the same, new concerns and new technology have forced a reconsideration of how we go about designing learning environments in the early years. The changes and advances made with young children will affect all other decisions that get made, and they will have a profound impact on whether programs designed for older children succeed at the level that we desire. Sequences of instru...

Table of contents

• Cover
• Half Title
• Title Page
• Copyright Page
• Dedication
• Table of Contents
• Preface
• Acknowledgments
• 1 Developmental and Learning Sciences z to School: An Overview
• PART I Reading, Learning, and Teaching
• PART II Science and Learning
• PART III Mathematical Learning
• PART IV Theoretical and Methodological Concerns
• Volume Contributors
• Index