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Learning and Instruction: A SERP Research Agenda 4 Science Many young children get off to a good start in acquiring knowledge on a variety of scientific topics. U.S. fourth graders score near the top in science—just behind Korea and Japan—among the nations in the Third International Mathematics and Science Study (TIMSS) (National Center for Education Statistics, 1999). However, since little science is taught in the early elementary grades, it is unlikely that these results can be attributed to school science programs. Instead, the high scores probably reflect the many informal science learning opportunities that abound in the United States, including science and technology museums, youth organizations that support science activities, television (e.g., the Discovery Channel; Magic School Bus; 3-2-1 Contact; Bill Nye, the Science Guy), trade books, and children’s science magazines. When serious science instruction begins, typically in middle school or even later, the advantages of informal learning resources begin to be overtaken by the disadvantages of unfocused curricula and weak teacher knowledge of both science content and pedagogy. At this stage the international comparisons become much less favorable. In fact, the TIMSS results at grade 8 place the United States in 17th place out of 26 nations. By grade 12 the United States scores are lower still, with advanced U.S. students scoring last of the 16 countries compared. Scores on national assessments confirm the bleak TIMSS results. On the 2000 National Assessment of Educational Progress (NAEP), 47 percent of twelfth grade students scored in the lowest category (below basic proficiency), an increase from 43 percent in 1996 (National Center for Education Statistics, 2003). Clearly, science education is not on a path to improvement. As in reading and mathematics, there are pockets of research and development in science education that have pro-
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Learning and Instruction: A SERP Research Agenda duced instructional programs with demonstrated student achievement benefits. In physics, for example, a highly productive tradition of research has produced a deep knowledge base with very important implications for educational practice. In contrast, for other areas in science education the research base is not yet developed fully enough to guide or support decisions about instruction. As with reading comprehension, knowledge of the progression of student understanding is relatively sparse and spotty from topic to topic. Moreover, there is very little evidence about how student understanding can develop with instruction over the school years. The first section of this chapter, as in the chapters on mathematics and reading, addresses an area that has potential for wide impact in the relatively near term: physics. Unlike the other two disciplines, however, this downstream case falls late in the K-12 curriculum. The second section of this chapter addresses science education across the school years, since we are still far upstream in developing a principled organization of science instruction, particularly in the years before high school. THE TEACHING AND LEARNING OF PHYSICS The number of students who take courses in physics is relatively small in comparison to the number who take biology or chemistry, as is the number of credentialed high school physics teachers in comparison to other science teachers. Perhaps because the community of educators working on physics is small, it has been possible to pursue a cumulative research agenda on major issues in physics teaching and learning. STUDENT KNOWLEDGE The Destination: What Should Students Know and Be Able to Do? Until relatively recently there was substantial overall agreement regarding what students should know and be able to do in the typical high school or college physics course (the content of the two overlaps substantially). In general, students were ex
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Learning and Instruction: A SERP Research Agenda pected to understand a range of concepts and laws organized around such domains as force and motion, electricity and magnetism, waves and optics, etc. Typically, understanding was demonstrated by the solution of problem types using quantitative methods that minimally demanded algebra. However, over the past several decades, research on student understanding has called into question whether the goals of instruction were being achieved. The Route: Progression of Understanding Historically, the implicit assumption in physics instruction has been that novice students could come to understand physics by receiving classroom presentations of what physics experts know. Research, however, has uncovered problems with that assumption. Students’ naïve ideas and conceptions about the physical world are not easily changed and in fact often remain substantially unaffected by typical classroom instruction. In the 1970s and 1980s, research conducted by John Clement (1982), Andrea diSessa (1982), Lillian McDermott (1984), and others revealed that even those students who can recall physics laws and use them to solve textbook problems may not understand much about the implications of these ideas in the world around them. For example, in diSessa’s research, college physics students performed no better than elementary students when asked to strike a moving object so that it will hit a target with minimum force at impact. Students relied on their untrained ideas in this task, ignoring the role of momentum, even when they could precisely reproduce the relevant laws of momentum on a test. Similarly, a study of student solutions to a problem with simple electrical circuits confirmed that students can reproduce scientific knowledge for a test, but revert to everyday ways of thinking when that knowledge is tapped outside the classroom (see Box 4.1). Additional work over many years has led to the conclusion that students bring to physics a substantial set of persistent conceptions that are significantly different from those needed to understand aspects of the physics curriculum. By far, the largest amount of work on student conceptions has been in the area of Newtonian mechanics (McDermott and Redish, 1999). Both before and after passing high school and even college physics courses, students often behave as if their conceptual under-
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Learning and Instruction: A SERP Research Agenda standings of force and motion are more in line with pre-Newtonian, even Aristotelian conceptions. Although these ideas are misconceptions from a scientific perspective, they are sensible interpretations people construct from their everyday experience with objects and events in the world. Because these intuitions serve quite well to explain and predict many features of everyday phenomena, they are often unexamined and may be difficult to change. Yet instruction often proceeds as if students have no ideas at all—as if the job of teaching is simply to provide the ideas that are scientifically correct. Students’ well-learned and practically useful mental representations for making sense of the world around them need to be actively engaged and built on if instruction is to be successful. Thinking like a scientist is partly a matter of understanding how scientific principles are embodied in familiar events around us. This is a challenge for students. Like novices in any area, they are often too reliant on surface features when they attempt to interpret and solve physics problems. Students tend to look for clues in the objects featured in the problem. For example, Larkin (1983) found that novices often rely on the objects mentioned in the problem statement, like blocks, inclined planes, and pulleys, to try to construct a basic representation that consists of relations among these explicit objects. From this basic representation, they then seek directly to identify a set of equations that they can use to plug in the values mentioned in the problem. In contrast, experts first construct an intermediate interpretation that represents the elements of the problem in constructs of the discipline, such as forces, acceleration, mass, momenta, etc. Chi and Bassok (1989) refer to this level of interpretation as a physics representation. They point out that the entities in a physics representation are not directly described but must be inferred. Perhaps because students tend not to identify problems as being members of categories defined by common scientific principles, they often fail to transfer what they “know” in the context of one problem to novel or even analogous problems. Researchers have focused considerable effort on mapping out what students do understand about a variety of physical phenomena and how that understanding progresses as a consequence of instruction. This work has probed the conceptual understandings of learners from preschool onward. Minstrell’s
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Learning and Instruction: A SERP Research Agenda BOX 4.1 Understanding Electrical Circuits Eric Mazur gave two questions very similar to the following two problems to students in his Harvard algebra-based physics class. Problem 1. Find the current through the 2 ohm resistor and the potential difference between points A and B. FIGURE 4.1a Diagram of a resistor. SOURCE: Mazur, 1997. The average score on the first (quantitative) question was 75 percent, while the average score on the second (qualitative question) was 40 percent. Physicists consider the second question to be much simpler; in fact, they would consider parts of it to be so trivial and easy that many would not bother to give such a question on an examination. The correct reasoning is that closing the switch causes a short circuit across the third light bulb, reducing the total resistance in the circuit. With no potential difference across the third bulb, it has no current and goes out. With the same voltage applied by the battery and less total resistance, the voltage drop across each of bulbs (1) and (2) increases, the current through the battery increases, the brightness of bulbs (1) and (2) increases, and the power dissipated in the circuit increases. work with high school students (e.g., Minstrell, 1989; Minstrell and Simpson, 1996), studies pursued by the Physics Education Group at the University of Washington with college students, and the research of many other investigators provide a wealth of information about how students typically think about a range of physical situations and concepts. The question in Box 4.2 regarding the relative weight of an
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Learning and Instruction: A SERP Research Agenda Problem 2. In the circuit shown below, explain what will happen to the following variables when the switch is closed: the current through the battery the brightness of each of the bulbs the voltage drop across each of the bulbs the total power dissipated FIGURE 4.1b Diagram of a circuit. SOURCE: Mazur, 1997. The techniques that students applied to quantitatively solve the first problem could be easily applied to the second problem by assuming values for the various quantities and solving the problem quantitatively by comparing calculations for the circuit with the switch open with those for the circuit with the switch closed. Instead, many students give answers that are consistent with naive conceptions of how electric circuits work. Similar results have been found with thousands of students after traditional instruction in research done by the Physics Education Group at the University of Washington. object when it is surrounded by air and submerged at two different depths of water produces a predictable range of responses from students when asked before, during, and even after instruction. Those responses can be evaluated for consistency with the various forms of student understanding shown in the box. The different answers, reflections of what Minstrell (1992) refers to as “facets” of thought, can be sequenced with
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Learning and Instruction: A SERP Research Agenda BOX 4.2 Understanding Fluid/Medium Effects and Gravitational Effects A solid cylinder is hung by a long string from a spring scale. The reading on the scale shows that the cylinder weighs 1.0 lb. FIGURE 4.2 Sample constructed-response item: separating fluid/medium effects from gravitational effects. About how much will the scale read if the cylinder which weighs 1.0 lbs. is submerged just below the surface of the water? What will it read when the cylinder is much deeper in the water? Briefly explain how you decided. respect to scientific sophistication. They range from acceptable understandings in introductory physics (310) to those representing partial understanding (e.g., 315), to those representing more serious misunderstandings (e.g., 319). Minstrell (1992) has argued that partially correct understandings frequently arise from formal instruction and may represent over- or undergeneralizations or misapplications of a student’s knowledge. These can result if the set of examples
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Learning and Instruction: A SERP Research Agenda Forms of Student Understanding 310—pushes from above and below by a surrounding fluid medium lend a slight support (pretest—3 percent). 311—a mathematical formulaic approach (e.g., rho × g × h1 rho × g × h2 = net buoyant pressure). 314—surrounding fluids don’t exert any forces or pushes on objects. 315—surrounding fluids exert equal pushes all around an object (pretest—35 percent). 316—whichever surface has greater amount of fluid above or below the object has the greater push by the fluid on the surface. 317—fluid mediums exert an upward push only (pretest—13 percent). 318—surrounding fluid mediums exert a net downward push (pretest—29 percent). 319—weight of an object is directly proportional to medium pressure on it (pretest—20 percent). presented to students is too limited or if an appropriate set of contrasting cases is not included to help clarify the conditions under which a concept applies. The task for a student is to come to recognize similar situations and problems as members of a category. Part of the challenge, then, is to understand the range of conditions under which concepts apply. It is important for both the instructor and the student to become aware of the form of the student’s conceptual understanding when instruction be
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Learning and Instruction: A SERP Research Agenda gins and to monitor changes in the student’s knowledge as instruction progresses. The goal is to build on what students do know and to help them understand the conditions under which it applies, rather than ignoring students’ current concepts and trying to replace them immediately with scientific reasoning. The Vehicle: Pedagogy and Curriculum Along with the research on student understanding have come new approaches to teaching physics that clearly demonstrate the accessibility of the subject for all students, if it is taught in ways that acknowledge what is known about student understanding. First, instruction needs to be based on the acknowledgment that students are being asked to reformulate category systems that have served them quite well in the past. This entails coming to recognize apparently familiar objects and events as members of novel classes, an accomplishment that develops slowly and only if students receive multiple well-chosen opportunities to experience the relevant range of situations in which a concept applies or does not apply. Second, teachers need to be aware of the range of ways in which students interpret situations and problems and to develop a repertoire of proven strategies for helping them question their assumptions, tune their partly correct conceptions, and understand the boundary conditions for important principles. The goal is to help students understand, which requires knowing how to capitalize on the forms of sense-making that they have available to work with. Third, effective physics instruction is designed to make more transparent what the practice of physics is all about. As Hestenes (1987) has cogently argued, physics is a “modeling game,” but this is far from apparent to students. The emphasis in much physics instruction is on using the products of physics—laws and principles—with little attention to why or how physicists generate and work with these concepts. Students rarely are taught physics as the enterprise of constructing, testing, and revising models of the world, and therefore its primary goals and epistemology are typically invisible. As we explain below, however, new approaches to instruction are emphasizing this aspect, inviting students into the modeling game and making evident the goal of what otherwise may seem a rather mysterious enterprise. To summarize, we emphasize three characteristics of new
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Learning and Instruction: A SERP Research Agenda approaches to physics instruction that follow from contemporary learning research: helping students develop new schemas for recognizing objects and events in the world as members of a category system more like the one used by scientists; continually monitoring changes in students’ evolving knowledge to inform choices of just the right experiences, countercases, and challenges to support their next step in knowledge development; and introducing students to physics as a modeling game, so that they grasp its epistemology and central goals. Most of the more fully developed curricula inspired by this research have been targeted at the college level. McDermott and Redish (1999) have identified nine such curricula and more are under development, including a research-based version of the widely used college text by Halliday and Resnick (Cummings et al., 2001). However, the substantial overlap of introductory college and high school physics courses suggests that much in these curricula may also be appropriate for high school use. Two programs designed specifically for students in middle school and high school have demonstrated improvements in student achievement, particularly with respect to conceptual understanding. In the first of these, the “modeling method” of instruction, students work to develop, evaluate, and apply their own models of the physical behavior of objects (see Box 4.3). The key to this instructional intervention is a series of professional development workshops with teachers, who are supported in effecting a radical shift of their pedagogy. Teachers are encouraged to become modeling coaches, helping students to observe, model, and explain interesting and puzzling phenomena. A 6-year project that provided extensive training and support for 200 teachers in this instructional approach resulted in nearly all of them demonstrating significant improvements in their own understanding, in their teaching, and in their students’ achievement (Hestenes, 2000; for more information, see http://modeling.la.asu.edu/modeling.html) on a highly regarded measure of physics conceptual understanding, the Force Concept Inventory (see below). These studies, conducted with large numbers of students in matched comparison groups, were carried out in multiple sites across several years. The research
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Learning and Instruction: A SERP Research Agenda included students in regular and introductory physics classes, honors-level physics, and advanced placement physics. Results repeatedly showed greater pretest to posttest gains in physics content knowledge when students taught by the modeling method were compared with (a) physics students of the same teachers in the year before the teachers implemented the program and (b) students in traditional physics classes and alternative reform programs. Students taught with the modeling method exceeded the performance of comparison groups by BOX 4.3 Modeling Instruction in High School Physics The modeling method has been developed to address problems with the fragmentation of knowledge in traditional physics instruction and the persistence of naive beliefs about the physical world. It is an approach to high school physics instruction that organizes course content around a small number of basic scientific models as units of coherently structured knowledge. David Hestenes and colleages at the University of Arizona have developed the approach to both instruction and teacher preparation over the past two decades. The program is grounded on the thesis that scientific activity is centered on modeling: the construction, validation, and application of conceptual models to understand and organize the physical world. Instructional activities give students experience in constructing and using models to make sense of a variety of physical problems. A critical feature of the program is the role played by the teacher: “The teacher cultivates student understanding of models and modeling in science by engaging students continually in ‘model-centered discourse’ and presentations.” The program developers argue that “the most important factor in student learning by the modeling method (partly measured by Force Concept Inventory scores) is the teacher’s skill in managing classroom discourse” (Hestenes, 2000, p. 2). The teacher is prepared with a definite agenda for student progress and guides student inquiry and discussion in that direction with Socratic questioning and remarks. The program uses computer models and modeling to develop the content and pedagogical knowledge of high school physics teachers, and relying heavily on professional development workshops to equip teachers with a teaching methodology. Teachers are trained to develop student abilities to make sense of physical experience, understand scientific claims, articulate coherent opinions of their own, and evaluate evidence in support of justified belief. Teachers are also equipped with a taxonomy of typical student misconceptions in order to prepare them to identify and work with them as they surface. In a sample of 20,000 high school students, gains on the Force Concept Inventory under modeling instruction are reported to be on average double those under traditional instruction, with teachers who implement the program more fully showing higher gains in their students scores. All students gained significantly from modeling instruction, but students with the lowest scores before instruction gained most. More information on the modeling method is available on the projects web site: http://modeling.la.asu.edu/modeling.html.
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Learning and Instruction: A SERP Research Agenda Theory Building An instructional approach designed by Sister Mary Gertrude Hennessey emphasizes theory building (see Box 4.7). Across content domains through the elementary years, students repeatedly consider the criteria by which scientific theories are formulated, used, tested, and revised. Sister Hennessey has generated longitudinal data concerning changes in her students’ grasp and application of these criteria, and she has also tracked changes in students’ propensities to reflect about their own thinking. Researchers external to the project have documented impressive performances by these students on standardized interviews concerning the nature of science. Modeling A number of investigators are examining the potential of organizing science instruction around the practice of modeling. This kind of instruction emphasizes developing models of phenomena in the world, testing and revising models to bring them into better accord with observations and data, and, over time, developing a repertoire of powerful models that can BOX 4.7 Science as Theory Building Until recently, Sister Mary Gertrude Hennessey, who has Ph.D.s in both science and science education, served as the sole science teacher for students in Grades 1-6 at St. Ann School in Stoughton, Wisconsin (she is now serving as principal). “Hennessey’s curricular approach stands out as an extensive and sustained attempt to teach elementary science from a coherent, constructivist perspective” (Smith et al., 2000:359). Hennessey’s instruction emphasized theory-building, both as the process by which students build their own science understanding and as an object of explicit reflection. Across content domains, students repeatedly considered the criteria by which scientific theories are formulated, used, tested, and revised. This emphasis was consistently maintained across grades of study. In early grades, the focus was on identifying and explicitly stating one’s own beliefs and the alternative beliefs held by classmates. In later grades, Hennessey “raised the ante” by urging students to consider the advantages of adopting additional criteria, such as the intelligibility, plausibility, and extensibility of their beliefs and the beliefs of others. In every case, these issues were explored in the context of sustained investigations of phenomena. Students applied these criteria as they worked toward building deep explanations based on theoretical entities, investigating the implications of their own explanations and alternative explanations proposed by the class. Sixth graders who spent six years under Hennessey’s tutelage showed impressive epistemological development on the nature of science interview developed by Carey and colleagues (Carey et al., 1989; Smith et al., 2000).
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Learning and Instruction: A SERP Research Agenda be brought to bear on novel problems. Modeling approaches have the advantage of avoiding the content-process debates that have plagued science education over the years. One cannot model without modeling something, so when students are engaged in modeling, reasoning processes and scientific concepts are always deployed together. Most existing research on modeling has been conducted with units or courses that do not span more than one school grade. (For example, Stewart and colleagues have developed high school courses in evolutionary biology and genetics; Reiser et al., 2001; White and Frederikson, 1998; Raghavan et al., 1995; and Wiser, 1995 have developed units for middle school grade students.) On a longer time scale, Lehrer and Schauble (2000) have initiated and studied a school-based program in which science teaching and learning is organized over grades 1-6 around modeling approaches to science (see Box 4.8). Data from this project include paper-and-pencil “booklet” items administered to intact classes of students, yearly three-hour detailed student interviews, and “modeling tasks” completed by small groups of students. Producing these items was itself a challenging task, since students were learning forms of mathematics not routinely taught in elementary grades. The items that were developed were based on evolving data about children’s understanding of ideas in geometry, measurement, data, and statistics. The student achievement data showed strong student gains; for example, from the first to the second year of the project, effect sizes by grade were 0.56 (Grade 1), 0.94 (Grade 2), 0.43 (Grade 3), 0.54 (Grade 4), and 0.72 (Grade 5). Argumentation Bazerman (1988), Lemke (1990), Kuhn (1989), and others have pointed out that science entails mastering and participating in a particular form of argument, including relationships between theories, facts, assertions, and evidence. This characterization of science explicitly acknowledges that science is not just the mastery of knowledge, skills, and reasoning but also participation in a social process that includes values, history, and personal goals. This view of science informs the ongoing work of Warren and Rosebery (1996), for example, who focus on classroom discourse organized around argumentation in science (see Box 4.9). Once again, researchers are supplementing their reports of teachers’ professional development with careful measures of student learning. These measures are
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Learning and Instruction: A SERP Research Agenda specific to both the content that students are studying in their classrooms (e.g., interviews of students’ grasp of ideas about motion) and in general (e.g., noting changes in the rates of certain patterns of discourse in classroom discussions of science). BOX 4.8 Science as Modeling In Lehrer and Schauble’s (2000) program, researchers work with teachers to reform instruction and, in coordination, to study the development of model-based reasoning in students. Early emphasis is on developing young children’s representational resources (drawings, writing, maps, three-dimensional scale models) as they conduct inquiry about aspects of the world that they find theoretically interesting. For example, first graders studied ripening and rot by using drawings to record changes in the color and squishiness of fruit, compost columns to investigate rates of decomposition, and maps of the school to investigate the dispersal of fruit flies from the compost columns to classrooms near and far. Teachers typically begin modeling with young students by exploring models that literally resemble the scientific phenomena being modeled. For example, first graders cut green paper strips to record changes over time in the height of amaryllis and paperwhite narcissus that they grew in soil and in water. Then, as investigations proceed, initial models are successively revised to provide increased representational power. As in the history of modern science, these models increasingly incorporate mathematical descriptions of the world. The students investigated concepts about measurement as they investigated which of the plants grew tallest (Lehrer and Schauble, 2000). However, when the teacher shifted the question to “Which plant grew fastest?” attention turned to recording and representing changes in height over time. In subsequent grades, questions about plants expanded to include comparison of growth rates (with attention to logistic curves as a general model of growth), the volume of their canopies (investigations about whether canopies grow in geometrically similar proportions), and shapes and other qualities of distributions of plants grown under different conditions (including sampling investigations). Researchers are investigating the potential of a range of central science themes (growth and diversity, animal and human behavior, structure) that can support this kind of cumulative modeling approach. The objective is to develop a cumulative approach to science that permits steady growth in students’ modeling repertoires across the elementary and middle school grades. One focus of research is to identify themes that are central to later science instruction and that provide early entry to young students and smooth “lift” (increased challenge) as students graduate from grade to grade. The primary form of professional development in this program is teachers’ collective investigation of the development of student thinking and study of the implications of those findings for teaching. The research also tracks the professional development of participating teachers and documents the institutional conditions required to support these forms of teaching and learning.
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Learning and Instruction: A SERP Research Agenda BOX 4.9 Science as Argumentation The Cheche Konnen project developed by Warren and Rosebery (1996) turns the attention of practicing teachers toward student meaning-making in science, especially those students whose first language is not English. Instruction capitalizes on students’ linguistic and cultural resources developed outside the school. In addition, teachers are encouraged to emphasize that the work of practicing scientists is also “populated by intentions, those of the speaker and those of others, both past and present” (p.101). Teachers seek to find points of contact between their students’ talk and reasoning and the forms of communication observed in communities of professional scientists. By conducting their own extended scientific inquiries, teachers in the Cheche Konnen project come to better understand the social and human basis of the scientific enterprise. Together, teachers conduct close study of student language by analyzing and investigating videotapes of classroom discourse. The assumption in this work is that student talk is sensible, and that the teacher’s job is to become increasingly skilled at identifying that sense and using it as the foundation for instructional moves. Checkpoints: Assessment As in other subjects, quality assessment in science requires, as a starting point, an understanding of what students should know and be able to do. It is perhaps not surprising, then, that the current situation in science assessment outside physics is dire. The broad but shallow coverage of science topics in current texts is mirrored in standardized assessments (including those administered for accountability purposes by the states) that touch briefly on a very wide array of concepts and topics without deeply probing student understanding of any of them. Some assessments include items designed to tap common student misconceptions, but they do not diagnose the developmental level of a student’s thinking about the topic. The diagnosis of student understanding that would render an assessment of greater use for instruction would be difficult to achieve without narrowing the range of topics. In-depth assessment, like that done in the Force Concept Inventory (discussed above) of so many topics, would not be practical in a single assessment. The current practice of devoting no more than a few items to each of several topics means that the assessments do not capture information that teachers can use. Even worse, they may serve to reify bad practice by encouraging an instructional
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Learning and Instruction: A SERP Research Agenda emphasis on coverage over conceptual understanding. There have been recent attempts to develop alternative performance-based assessments in science to address these problems, but these have not yet overcome the psychometric and logistical challenges (Ruiz-Primo and Shavelson, 1996; Solano-Flores and Shavelson, 1997; Ruiz-Primo et al., 2001; Stecher et al., 2000). Moreover, attempts to change the form of assessment are hampered by the more fundamental problem of forging consensus about what is worth assessing. TEACHER KNOWLEDGE Relatively few teachers at the K-8 level feel well qualified to teach life, earth, or physical science. The percentages range from 18 for physical science to 29 for life science. K-8 teachers generally lack a deep knowledge of the subject matter of science. Few have an undergraduate major in a science discipline, although most have done some science coursework while in college. Undergraduate courses in science are not particularly helpful for understanding the rich conceptual repertoires that children typically bring to understanding scientific situations. There is little in teacher preparation programs that provides the foundations of pedagogical content knowledge for teaching science. Elementary school teachers are less likely than middle or high school teachers to indicate that they are prepared to support the development of students’ conceptual understanding of science, provide deep coverage of fewer science concepts, or manage a class of students engaged in an extended inquiry project (Weiss et al., 2001). The available evidence does suggest, however, that “teachers who participate in standards-based professional development often report increased preparedness and increased use of standards-based practices, such as taking students’ prior conceptions into account when planning and implementing science instruction. However, classroom observations reveal a wide range of quality of implementation among those teachers” (Horizon Research, 2002:168-169). RESEARCH AGENDA International and national test scores highlight the weakness of K-12 science education in the United States. That students in so many other countries perform considerably better suggests that the problems are tractable. And there are some
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Learning and Instruction: A SERP Research Agenda indicators of the path toward improvement: we need to be more thoughtful about supporting a deeper understanding of the big ideas in science curricula. This implies principled choice of fewer topics to be treated in greater depth and with greater coherence. These must then be the ultimate targets of a SERP agenda that holds promise for improving student learning outcomes. Promising work, examples of which are described, has begun to build the knowledge base for a more coherent approach to science education. Teams of researchers working closely with teachers and other educational practitioners are systematically exploring the long-term learning potential and technical feasibility of pursuing systematic, cumulative approaches to science that treat topics in depth. All of these efforts include thoughtful consideration of the appropriate goals of early science education, investigations of the development of student knowledge, and research on the professional development and institutional supports required to implement them. Finally, each of these efforts relies on practitioner-researcher partnerships that extend over a number of years. Such long-term relationships are essential because the targets of the research (forms of student thinking) must first be reliably generated before they can be systematically studied. In these many respects, these are the types of efforts we have argued carry potential to improve practice. So far, each of these efforts has been patched together with the short-term grant awards that are typical in education funding. They have not had the support required for evaluating long-term student outcomes rigorously and independently, with a broad range of students in a range of settings. But they provide a very promising point of departure for a SERP research program. With its longer time scale and capability to plan comparative studies of the trade-offs of different approaches, SERP could assume a critical role in the development, study, and comparison of these models of teaching and learning that build systematically across the grades of schooling. Some of the programs we have mentioned are already yielding longitudinal findings about student learning. Some are investigating the forms of professional development and institutional support that are required to help similar programs flourish more widely. For this work to contribute to the quality of K-12 science education on a large scale, however, will require a sustained effort to learn from the range of experiments and to use what is learned to
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Learning and Instruction: A SERP Research Agenda inform both the next stages of research and development and the goals and standards set for science learning. To this end, the research agenda we propose involves initiatives that we spell out in general terms, and that will look in their specifics much like the initiatives in reading and mathematics: Development and evaluation of integrated learning-instruction models, with component efforts that include curriculum, assessment, and teacher knowledge requirements; Evaluating standards for science achievement. Initiative 1: Development and Evaluation of Integrated Learning-Instruction Models Identifying a productive organizing core for school science across the grades is an important element in providing science education that builds from one year to the next. This does not suggest that there is a single, right vision about what is worth teaching and learning. But alternative visions should be formulated, articulated, and carefully justified, so that instruction in all cases can be oriented around valued goals. However, the challenges and possibilities of alternative commitments become clear only when the details of instruction have been worked out, conjectures about fruitful paths for learning have been developed and pursued, and longitudinal research has been conducted as instruction plays out in classrooms. While there have been several efforts to establish standards (the core), these have had minimal impact because they are promulgated without the details of instruction that are required to attain the goals that are envisioned. This will require work on curriculum and on assessment that is closely linked. Curriculum development and evaluation Existing promising programs like those described above should be further developed and evaluated. The work we propose is not the typical process in which curricula are first invented and then evaluated. Rather, it is one in which design and research are intimately inter-leaved, so that initial design decisions take the status of conjectures. Evidence regarding the conjectures and their consequences for learning would then contribute to the ongoing shaping and
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Learning and Instruction: A SERP Research Agenda revision of the design. Such an approach is particularly important for a field like science education, in which there is not yet an organized research base to undergird conjectures about optimal sequences of topics and tasks. The key role to be played by SERP is in evaluating the range of programs to consolidate an understanding of differences across programs and their implications for student learning outcomes. The nature of the work to be done here parallels several of the research and development efforts described in previous chapters. The evaluation of curricula for science would be much like the evaluation of curricula in mathematics. The desired outcome here, as there, is not a stamp of success or failure, but a deeper understanding of the learning process and effective avenues to support it, with a goal of continuous learning and improvement. The work should be designed to collect outcomes data longitudinally. Different instructional commitments necessarily produce different results, but it is difficult to evaluate those results unless we can see what they generate over the long term. Excellent science instruction achieves more than the development of relevant concepts; it also fosters habits of mind that are consistent with scientific ways of knowing. These forms of thinking are acquired only over years of systematic support and assistance. For this reason, we cannot understand the potential payoff of the varying approaches to science education unless the contexts permit sober estimation of what they deliver over the long term. Initiative 2: Assessment An essential limitation on the new experiments in science education is that they lack a widely shared set of assessment instruments (like the Force Concept Inventory in physics) that can anchor meaningful comparisons across different approaches. One potential source for such a set of assessments might be the instruments and items recently designed to assess the development of students’ understanding of scientific epistemology. These include interviews about the nature of science and the nature of models and their uses in science, both developed by Carey and her colleagues (Carey et al., 1989; Grosslight et al., 1991) and by Rosalind Driver’s research group (Driver et al.,
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Learning and Instruction: A SERP Research Agenda 1996). In each case, these interviews take a long-term developmental focus and have generated baseline data on students in a wide variety of classrooms. These existing evaluations, while promising for the purposes for which they were designed, focus primarily on the nature of science rather than science content. Some work has been done that could support assessment development on the latter, however. Studies assessing students’ conceptual development have reported a variety of tasks and items designed to measure conceptual development within particular subject-matter areas. An example is the interview developed by Vosniadou and Brewer to diagnose children’s conceptual models of the earth-moon-sun (Vosniadou and Brewer, 1994). Obviously, the utility of these assessments depends on their specific relevance to the material being taught in the classroom, but they do serve as a potential source of both items and approaches to assessment development. One potential role for SERP would be to convene researchers and curriculum developers in science who would agree to develop and commit to the use of a common set of assessments. The programs of group members would need to demonstrate at least partial overlap in both conceptual content and epistemological focus. This could be done, for example, with several of the elementary school programs described earlier that emphasize some common approaches to the study of animal and human behavior, adaptation, and evolution and that share some common commitments about the nature of science. The idea would be not to identify a set of assessments that would serve once and for all to measure learning in science, but to serve as a test case for the possibility of developing and refining at least one powerful science assessment that takes a developmental approach to measuring the evolution of student knowledge and understanding. Moreover, such assessments would be fundamentally important in pursuing the study of trade-offs of different commitments to an organizing core for science education. The SERP network would be a natural site for such research because SERP can support the kind of long-term effort needed to develop and test assessments and can also bring to bear the multiple student data sets and forms of professional expertise (e.g., psychometricians, content experts) required.
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Learning and Instruction: A SERP Research Agenda Initiative 3: Teacher Knowledge Requirements As in reading and mathematics, little attention has been given to the knowledge requirements to effectively teach science at any grade level or to effectively connect what is learned at one level with what has come before and what will come after. The avenue that we propose for exploring these questions is to investigate the knowledge requirements to effectively work with the curricula under study in a program of instruction. The research and development programs discussed above that are currently operating in schools provide a rich resource in the form of teachers who can be studied. Each of these programs has made commitments to forms of professional development, and it would be highly informative to compare the different approaches. For example, some of them work with volunteer teachers from a wide geographical area, for example, across large school districts. Others work with every teacher in a participating school. It would be important to understand the relative advantages of working with a selective, presumably very committed group versus the potential synergies to be gained from working with an intact school staff. A variety of other professional development strategies are being used and studied in these programs, including teacher authoring, science learning workshops, study of student work, reading of articles and texts about science and science education, and analysis of discourse on classroom videotapes. Little serious comparative study has been conducted of the relative costs and benefits of such strategies in spite of the obvious importance of such information for policy makers and administrators. As in the other domains, the work must provide an evidence base on the knowledge required and the knowledge that is typical of science teachers at different grade levels. The distinction between what teachers themselves know about science and what they know about how to teach science to a student will be as critical, as it is in mathematics. (The descriptions of research on teacher knowledge in the mathematics and reading chapters, as well as the physics section of this chapter, provide more detail regarding the nature of the questions to be examined and the approaches to teacher education that should be compared.)
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Learning and Instruction: A SERP Research Agenda Initiative 4: Evaluating Standards for Science Achievement The practitioners and researchers engaged in the study of science instruction and student learning will be well placed to inform the ongoing efforts by various stakeholders to set standards for student achievement in science at various grade levels. The standards themselves are, and should be, based on more than research. Much depends on society’s educational goals for its children and the relative importance it places on competing goals. But goal setting can be more rational if it is well informed. One strand of the SERP science work we propose is the consistent attention to, and articulation of, what is possible and with what commitments (investment in teacher education, instructional time, etc.). This should be done through careful data collection and regular stock-taking of results across studies.
Representative terms from entire chapter: