Science and Education Research Paper

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Science education deals with the learning and teaching of science knowledge, practices, habits of mind, discourse patterns, and their relation to natural and man-made environments. Because of the importance of science to nations’ economic, environmental, and general well-being, much attention has been devoted to helping the public develop awareness and understanding of science and the role it plays in their lives and preparing the next generation of scientists. Science knowledge is typically one of the subjects assessed in large-scale national and international tests such as the National Assessment for Educational Progress (NAEP; Grigg, Lauko, & Brockway, 2006) and the Trends in International Math and Science Study (TIMSS; Martin, Mullis, Gonzalez, & Chrostowski, 2004), underscoring the importance that is attributed to it.

Broadly speaking, the goal of science education is the development of science literacy. There are two different perspectives on science literacy: as conceptual understanding and as participation in a community of practice. The following section presents these two perspectives.

Science Literacy

Science Literacy as Conceptual Understanding

In 1990, Project 2061 of the American Association for the Advancement of Science published Science for All Americans (1990), which presented the conceptual understanding perspective of science literacy and made the case why it was important that all people, not just scientists, become literate in science. Project 2061 defined science literacy as a thorough knowledge of the key concepts and principles in science; an understanding of the inter-dependency of mathematics, science, and technology; a recognition of the strengths and limitations of science; and the ability to use this knowledge for personal and social purposes. The same organization published Benchmarks for Science Literacy (AAAS, 1993), which specifies what students should know and be able to do at the end of certain grades to attain science literacy by the end of high school. The National Research Council published the National Science Education Standards (National Research Council, 1996), which specifies not only science content standards, but also science teaching standards, standards for the professional development of science teachers, and standards for assessment in science education. Many countries have followed a similar process in developing their own science education standards. In the United States, the education department of each state then developed their own standards that often, but not always, draw on the national standards and benchmarks. These standards then guide or dictate, depending on the state, which science curricula can be used at various grade levels. Since the standards of individual states often conflict with those of other states and do not prioritize the various science topics, it becomes very difficult to develop curriculum that can be used in multiple states without expanding the scope of textbooks to cover everything required by every state at every grade (Roseman & Koppal, in press). As a result, U.S. science curriculum has often been criticized for being a mile wide and an inch deep.

This conceptual understanding perspective treats science learning as a process of building on students’ prior ideas about the natural world. These ideas are often at odds with each other, contradict accepted scientific ideas, and are not coherent in the way that scientific theories are expected to be consistent and parsimonious (Driver, Guesne, & Tiberghien, 1985). For example, students may think that if a body is not moving then there is no force acting on it, while at the same time recognizing that a body resting on a table is subjected to the force of gravity. Interestingly, students across countries and cultures hold many of the same ideas. Finally, these ideas also tend to be stable and difficult to change, even when students are confronted with evidence to the contrary, and thus greatly influence future learning. Since the 1980s, research has documented students’ typical ideas on a wide range of scientific topics; Duit (2007) has compiled many of these studies.

Science is learned through a process of conceptual change by which prior ideas are modified, exchanged, or added to. Posner, Strike, Hewson, and Gertzog (1982) identified four rational conditions needed to bring about conceptual change: (1) dissatisfaction with existing ideas, (2) intelligibility, (3) plausibility, and (4) fruitfulness of new ideas. In addition to these rational conditions, there are also other cognitive, affective, and contextual factors that influence conceptual change (Pintrich, Marx, & Boyle, 1993).

According to this perspective of science literacy, the teacher’s role is to engage students with phenomena that are incompatible with their prior ideas and to present new ideas that can explain these phenomena. This perspective has been critiqued for conceiving of scientific literacy as the property of an individual rather than of social activity, which is the focus taken by the next perspective.

Science Literacy as Participation in a Community of Practice

This perspective focuses primarily on how students learn from social interactions rather than from their interactions with the material world. It builds on the work of Vygotsky (1986), anthropologists, and linguists. It views science literacy as the “ways of knowing, doing, talking, reading, and writing [about the natural world], which are constructed and reproduced in social and cultural practice and interaction” (Gee, 1996, p. 470). It views scientists as members of communities of practice rather than individuals interacting rationally with nature, and it draws on analyses of the norms and discourse patterns of scientific communities rather than on conceptual understanding of individuals (Anderson, 2007). Although the sociocultural tradition has been around for many years, science educators began to adopt this perspective only in the 1990s.

This perspective builds on students’ prior experiences in their home communities. Some of these communities use language and have norms that are very different from those used by scientists. In contrast to the conceptual understanding perspective, in which teachers need to help students bridge the conceptual gap between their prior ideas and scientific ideas, the role of the teacher from this perspective is to help students bridge the cultural gap separating their home-based communities and the scientific community. Science learning is viewed as a process of apprenticeship in which one learns to adopt scientific language and norms for the purpose of participating in a community engaged in science.

Proponents of this perspective argue that the U.S. National Science Education Standards (National Research Council, 1996) overly emphasize facts and concepts and assume that knowing these ideas will naturally lead to the ability to participate in scientific communities. This perspective has been critiqued for not generating reproducible prescriptions for teaching or methods for assessing outcomes.

Scientific Inquiry

To support the development of science literacy that builds on both perspectives, many science educators recommend engaging students in authentic scientific inquiry that draws on a variety of scientific practices. Scientific inquiry is the various ways in which scientists study the world, use evidence to develop models and construct explanations, and communicate their ideas to their peers. A large number of pedagogies have been developed with the aim of incorporating inquiry into school science. Many of these pedagogies have several common features (Blumenfeld, Marx, Patrick, Krajcik, & Soloway, 1997) that I will discuss here:

  • They are structured around authentic tasks for prolonged periods of time.
  • They place high importance on the incorporation of phenomena, whether they are experienced first-hand or vicariously.
  • They integrate the leaning of science concepts with engagement in scientific practices and the discourse that accompanies these practices.
  • They encourage the use of alternative and formative assessments.
  • They make use of computer-based technology.
  • They build upon student collaboration.
  • They view the teacher as a facilitator and a learner along with the students rather than as a source of knowledge.

Authentic Tasks

Since all learning is situational, it must be constructed in contexts that are significant and authentic to the students for it to be meaningful and useful outside the walls of school. One of the main ways to achieve this is to use driving questions, which are the hallmark of project-based science (Krajcik, Czerniak, & Berger, 2003). A driving question is a rich, open-ended question that connects with students’ interests and curiosities, such as, Can I believe what I see? or How can I use trash to power my stereo? A successful driving question needs to meet six criteria:

  1. Feasibility—It must be feasible for students to design and perform investigations to answer the question.
  2. Worth—It must deal with the science content and practices that are aligned with national or state standards.
  3. Contextualization—It should be anchored in the lives of learners.
  4. Interest—It should be interesting and exciting to learners.
  5. Ethics—Investigating it should not harm living organisms or the environment.
  6. Sustainability—It should be able to sustain students’ interest for a prolonged time.

Driving questions need to be tied to anchoring events (CTGV, 1992) that provide students with common experiences that can be returned to throughout the unit. For example, the anchoring event that accompanies the driving question, Can I believe my eyes? consists of the following sequence: In a darkened room, a black poster is illuminated with red light generated by an overhead projector covered with a red filter. The following message becomes visible:

a I e ie e      y e e

The red filter is replaced with a green filter and the following message appears:

C  n  b  l  v  m     y s?

The green filter is removed and the poster is illuminated with white light, revealing the following message:

Can I believe my eyes?

Phenomena

Since science deals with the understanding of natural and man-made environments, it would seem obvious that phenomena drawn from these environments should play a central role in science education. Unfortunately, this has not always been the case, as review of many middle school physical science textbooks showed (Kesidou & Roseman, 2002). Phenomena can play a central role in introducing, clarifying, and evaluating ideas. Students can interact with phenomena directly or vicariously. A teacher can demonstrate a phenomenon as when holding a pin-wheel over burning trash to make it spin. Students can observe a phenomenon without the teacher’s mediation as in witnessing that air bubbles are released when water is heated. Phenomena can be investigated in controlled laboratory settings, such as when studying heliotropism, or in uncontrolled settings, as during a field trip. Often it is impossible to give students direct access to certain phenomena, either because they are too big, small, fast, slow, far, or too dangerous. For example, most students have seen the moon rise above earth’s horizon, but how many have seen earth rise above the moon’s horizon? In many of these cases it is possible to interact with these phenomena vicariously, by watching videoclips, computer simulations, looking at photos, or by reading descriptions of the phenomena.

The science laboratory has been the traditional place where students get to investigate phenomena. Without diminishing the importance of the laboratory, which is often the only environment in which certain phenomena can be investigated, it is important that the laboratory is not the only place where students interact with phenomena; otherwise students may view science as something that is relevant and important only in laboratories rather than something that can be relevant and meaningful in many parts of their lives.

Scientific Practices

Scientific practices represent the disciplinary norms of scientists as they construct, evaluate, reason, and communicate (Lehrer & Schauble, 2006). When adapted for learners, scientific practices characterize how students use scientific knowledge to make sense of and explain the world. Examples of scientific practices that have been introduced into K-12 science curriculum are designing investigations and controlled experiments; developing evidence-based explanations; and constructing, evaluating, revising, and using models to explain, predict, and communicate. Practices are important because they help develop both types of science literacy. First, engaging in scientific practices supports learners in developing and using conceptual understanding because they involve understanding that is more meaningful than just describing and recalling phenomena. Second, scientific practices define an important aspect of what it means to partake in the norms and discourse patterns of the scientific community (Duschl, Schweingruber, & Shouse, 2007).

Alternative and Formative Assessment

Unlike summative assessment, which comes after instruction to determine what students have learned, formative assessment provides feedback to teachers and students about their progress while they are learning. Formative assessments are often embedded into instruction so that the students may be unaware that their learning is being assessed. These assessments usually make use of nontraditional data sources, such as student artifacts that are developed in the course of instruction. Student-produced artifacts, such as models, written explanations, and presentations, help them learn concepts, apply information, and represent their knowledge, but also allow for ongoing and contextualized assessment of learning through “understanding performances” (Perkins, 1992). Embedded assessments can allow teachers to make realtime adjustments to instruction so that it best fits the needs of their students.

Computer-Based Technology

Computer-based technology use is another core element of many inquiry-based curricula (Linn, 1997). These technologies come in many forms, for example microcomputer based laboratories (MBLs), visualizations and simulations, and data analysis programs. MBLs, which are data collection probes connected to a computer through an interface, allow students to record data that may not have been available to them otherwise, thus extending their observational capacity. Visualizations and simulations provide students with visual images of phenomena that might have been otherwise inaccessible. Data analysis programs and other digital environments can help clarify the problem space and allow students to focus on the most salient aspects of the problem at hand. By slowing or speeding up time, magnifying or compressing distances, computers can allow students to notice and make sense of relationships that would have otherwise gone unnoticed.

Student Collaboration

According to Webb and Palincsar (1996), “collaboration is convergence—the construction of shared meaning for conversations, concepts, experiences.” Student collaboration is essential for constructing the second kind of science literacy, which focuses on social norms and disciplinary discourse. Students’ understanding of the nature of science develops as they collaborate and engage in scientific discourse with others (Blumenfeld et al., 1997). By collaborating, students can learn from others’ knowledge, reflect on their own ideas, appropriate scientific norms, and reach sophisticated performance. Students can collaborate with members of the same classroom or with people located elsewhere by using the Internet.

The Teacher As Facilitator

In all inquiry-based curricula, the teacher is seen as a facilitator to student learning, a guide rather than an imparter of knowledge. Driver, Asoko, Leach, Mortimer, and Scott (1994) describe the teacher as a tour guide who mediates between the students’ prior knowledge, home cultures and norms, and scientific ideas, practices, and discourse patterns. Collins, Brown, and Newman (1989) used the analogy of a cognitive apprenticeship to describe the relationship between the teacher and students. By breaking down complex tasks into simpler ones, modeling scientific attitudes, and providing feedback, the teacher scaffolds the learning process.

Learning Progressions

As mentioned earlier, traditional science textbooks often cover many topics with little depth because they try to cover conflicting standards from multiple states. This can lead to shallow and disconnected knowledge. Learning progressions offer a remedy to this situation by providing descriptions of successively sophisticated ways of thinking about key scientific concepts and practices across multiple grades. They provide coherence across grades and better alignment between standards, curriculum, and assessments.

Learning progressions are not developmentally inevitable; they entail targeted instruction and curriculum. They present learning more as an ecological succession than a series of discrete and sequential steps. Learning progressions are based on what is known about student learning, but are conjectural and need to be empirically tested. They are anchored at one end by what is known of students’ prior ideas and at the other end by societal expectations of what students’ should know and be able to do at the end of high school (Duschl et al., 2007). The development of learning progressions is iterative and cycles between theoretical refinement and empirical testing.

Learning progressions can guide the design of instruction, the specification of learning performances, and the development of tasks that allow us to infer students’ competence. The following sections will elaborate on some of the characteristics of learning progressions.

Core Ideas

Recognizing that national and state science standards list more topics than any student could be expected to learn in depth within the typical time allotted to science classes and that science understanding is organized around conceptual frameworks that have great explanatory power, such as laws of conservation, learning progressions identify those core science ideas and practices that serve as the backbones for these conceptual frameworks and promote their learning in depth, even at the expense of other ideas that are not so central. The following criteria determine whether an idea or practice is pivotal to scientific thinking:

  1. Explanatory power within and across disciplines or scales: The core ideas help one understand a variety of different ideas within or between science disciplines.
  2. Powerful way of thinking about the world: The core ideas and practices provide insight into the development of the field or have had key influence on the domain.
  3. Accessibility: The representations of core ideas and practices must be comprehensible to learners through their cognitive abilities (age-appropriateness) and experiences with phenomena.
  4. Key to scientific discourse: The core ideas and practices must be central to students’ understanding of and engagement with scientific discourse and culture.
  5. Building blocks for future learning: The core ideas are vital for future development for other concepts and lay the foundation for continual learning.
  6. Support informed decision making: The core ideas help the individual participate intellectually in making individual, social, and political decisions regarding science and technology.

While these criteria are strongly aligned with the definitions given earlier for science literacy, they go further and provide additional measures for evaluating the centrality of different ideas.

Age Appropriateness

Learning progressions recognize that even very young children are capable of sophisticated and abstract thinking, of generalizing and making inferences, and of designing and using experiments to test their ideas (Metz, 1995). Upon beginning school, young children already have a wide repertoire of experience with and knowledge about the natural world, which can serve as an excellent starting point and foundation for instruction (Driver et al., 1985). Children’s knowledge does not develop linearly across grades. Sometimes it occurs naturally as the result of maturation and everyday experiences. Other times it requires guided instruction and intentional effort on the child’s behalf. For some children, a certain instructional sequence will lead to significant growth; for others, a different sequence is needed. Learning progressions do not dictate what needs to be or can be learned at different ages; they suggest possible paths through a web of possible connections, some of which may be more efficient than others (Duschl et al., 2007).

Curricular Coherence and Integrated Knowledge

Science knowledge can be disconnected, composed of bits and pieces with little relation to each other, or integrated, a rich network that considers how different things are connected and related to each other. Integrated knowledge allows chunking of ideas, identification of organizing themes, and relatively easy incorporation of new ideas into the network (Bransford, Brown, Cocking, Donovan, & Pellegrino, 2000; Clark & Linn, 2003). Integrated knowledge is one of the hallmarks of content experts. For knowledge to become integrated, one has to engage in a deliberate process of connecting, organizing, and structuring ideas (Ericsson, Krampe, & Tesch-Romer, 1993).

Curriculum is one of the primary resources teachers have for guiding instruction (Ball & Cohen, 1992) and has significant influence on the nature of the science knowledge that students construct (Roth, Anderson, & Smith, 1987), whether it will be integrated or disconnected. For curriculum materials to support the construction of integrated knowledge, they must be coherent (Roseman & Linn, in press; Shwartz, Weizman, Fortus, & Krajcik, in press). Coherent curriculum materials have two main characteristics: (1) they present content in a connected way that focuses on core ideas, and (2) they guide instruction in ways that are pedagogically sound, such as providing a sense of purpose, building on students’ prior ideas, providing students with multiple opportunities to externalize their ideas, and including embedded formative assessments (Kesidou & Roseman, 2002). Since learning progressions take into account how the various aspects of science expertise interact while emphasizing the core ideas, they have the potential to serve as guides in developing curriculum that can foster knowledge integration.

Science Teachers

Teachers are probably the single most important factor in determining the quality of science education. In addition to having mastery of content they teach, science teachers must also understand what it means to be scientifically literate, how students learn science, how to design and implement supportive learning environments, and how to adapt curriculum to best meet the needs of their students, among many things (Duschl et al., 2007). Teachers need to be life-long learners that can model scientific ways of thinking, communicating, and engaging with phenomena.

Science Content Knowledge

Science is not a monolithic field, but comprises different disciplines, each having its own characteristic discourse patterns, internal logic, investigative tools, and so forth. For example, inquiry in physics is much more mathematical than it is in biology. Inquiry in Earth science is less laboratory-based than chemistry. Some schools offer classes in interdisciplinary science or in environmental science, which require teachers to have broad content knowledge in multiple disciplines and to understand the relationships between the various disciplines. Not surprisingly, students’ science achievement improves when they have teachers with higher content knowledge in the discipline they teach. Unfortunately, many science teachers teach outside of their field of expertise, and this can affect their ability to clarify and explicate content as well as orchestrate classroom activities, such as engaging students in discussions (Sanders, Borko, & Lockard, 1993). Many teachers have a limited conception of science literacy as knowledge of a collection of facts and may be unaware of the role of scientific practices. This may be due to narrow and limited undergraduate education that typically focuses on content mastery and in turn is influenced by minimal credential requirements in many states, especially at the K-8 level.

Knowledge Of Students And Student Learning

The development of science literacy is not a simple goal. For teachers to be able to support and guide their students in this endeavor, they need to have in-depth knowledge of how people construct science understanding, how they come to adopt the norms and practices of the scientific community, how to engage students with phenomena that will lead to intellectual growth, how to assess students’ progress, how to adapt curriculum to meet their students’ needs, and how to foster student collaboration.

Every teacher has been a learner, so they often generalize from their personal learning experiences to their students. Since many learned through rote memory, they envision the learning of science as getting the students’ attention, breaking down content knowledge into small chunks and transferring this knowledge to the students’ minds, then hoping that it sticks where it lands (Strauss, 2001). This model of teaching and learning is in stark contrast with what research indicates is the way people actually learn science, which is by engaging in scientific practices in authentic situations over time.

Shulman (1987) distinguished between content knowledge, pedagogical knowledge that is domain-insensitive, and pedagogical knowledge that is particular to a domain, often called pedagogical content knowledge (PCK). PCK in science involves knowing how to make science knowledge and culture plausible, meaningful, and useful to nonexperts and recognizing the typical stumbling blocks that learners face in constructing this knowledge (Zembal-Saul, Starr, & Krajcik, 2002). Little is known about the relationship between PCK and student learning in science, but a few case studies and expert to novice comparisons seem to indicate that it is a central factor in influencing student learning (Duschl et al., 2007).

Teachers are consumers of published curricula but designers of enacted curricula. The general quality of much of the available science curriculum materials in unsatisfactory (Kesidou & Roseman, 2002). Until abundant high-quality science materials are available, teachers need to select, evaluate, and modify existing curriculum materials to effectively meet the needs of their students and the expectations of their districts. Even when high-quality materials are available, their use can be challenging. High-stakes testing and overload force teachers to be concerned about the time and risks involved in adopting new high-quality materials that may require them to change their teaching practices. Knowing how to adapt curriculum materials is another important skill science teachers need to develop, yet it is underemphasized in most teacher preparation programs (Davis, 2006).

One of the ways curriculum materials can assist teachers in adopting them, adapting them, and maximizing their effectiveness is by incorporating educative features (Davis & Krajcik, 2005), which are features that are intended to promote teacher learning as the teacher uses the materials to guide student learning. Such features could develop teachers’ content knowledge, demonstrate how to make connections between units and disciplines, provide information about the typical student’s prior conceptions, make the designers’ rationale transparent, and provide guides to making productive adaptations. But educative curriculum materials alone cannot remedy issues related to teachers’ content knowledge, pedagogical knowledge, and pedagogical content knowledge. For them to be effective, they need to be part of a comprehensive teacher education and teacher development program.

Teacher Pre- and Inservice Professional Development

In general, less is known about teacher professional development in science than in mathematics and literacy (Borko, 2004). There are general characteristics of teacher professional development programs that appear to have a positive influence regardless of the field on which they focus. Whether there are additional characteristics that are unique to successful professional development programs in science is less clear.

Teacher inservice professional development programs need to be grounded in teachers’ practice and consider their local expectations, constraint, and resources. These programs are usually provided by external facilitators, such as curriculum publishers. A review by the American Educational Research Association (2005) indicated that such programs should focus on improving student learning of content in the context of the particular curricula being used, draw on student artifacts, inform the teachers of the various connections between the various components of the curriculum, local standards, and assessments, and be ongoing—that is, provide teachers with multiple recurring opportunities to reflect on their practice rather than being one-shot, short-term workshops.

In many ways, the good science teacher professional development programs have much in common with high-quality science curriculum: (a) they are structured around authentic tasks (instructional practice in the context of a particular curriculum) for prolonged periods of time, (b) they place high importance on the incorporation of phenomena (student learning), and (c) they build on student (teacher) collaboration.

Diversity

Large-scale standardized tests have revealed significant gaps in science achievement among students of different racial, cultural, and socioeconomic backgrounds. Racial, cultural, and economic factors influence students’ prior knowledge of and beliefs about science. Some of the

societal factors that can detrimentally affect students’ attitudes toward science are the lack of a personal connection with someone they identify with who is in a science-related profession, the media’s stereotypical portrayal of scientists, college programs and professions that exclude women and people of color, and contrasts between the culture of science and the home culture (Eisenhart, Finkel, & Marion, 1996).

Most preservice teachers have little cross-cultural experiences and believe that they need to be color-blind and treat all students identically, rather than acknowledging that students are different and ignoring these differences undermines the goal of science literacy for all. Teachers often feel inadequately prepared to deal with the diverse needs of their students, especially those who are not native speakers of the dominant language. The tendency toward color-blindness can be reinforced by accountability policies that seldom make mention of students’ home language and culture, and thereby reinforce the view that minorities are expected to assimilate to the dominant language and culture.

Although there have been attempts to deal with this issue by developing science curriculum materials that are culturally relevant, attempt to avoid gender stereotyping, and acknowledge the special needs of some learners, these materials are usually useful only for the particular linguistic or cultural groups; this makes their development prohibitive. Another approach is to develop design principles that can steer the development of high-quality materials and guides for teachers on how to effectively adapt such materials so that they maintain their relevance for diverse students (Lee & Buxton, in press).

Many states are beginning to incorporate science into their high-stakes tests to meet the science accountability requirements of the No Child Left Behind Act (2002). This policy will undoubtedly lead to major changes in the way science is taught. It remains to be seen whether these changes will lead to the closing of the achievement gap.

Conclusion

Expertise in science education requires mastery of a broad range of knowledge and skills. Teaching science requires more than a deep understanding of general themes in education (such as student learning, teaching, and teacher education), developmental and educational psychology, technology, sociology and culture, and assessment; science teachers must also have a deep understanding of at least a single science discipline, the nature of science, its discourse patterns, practices, and investigative norms, and its relationship to technology and society at large. It is a dynamic and developing field, drawing on knowledge gained from other fields, integrating them, and often leading the way in indicating possible new ways to improve education in general.

References:

  1. American Association for the Advancement of Science. (1990). Science for all Americans. New York: Oxford University Press.
  2. American Association for the Advancement of Science. (1993). Benchmarks for science literacy. New York: Oxford Univer-sity Press.
  3. American Educational Research Association. (2005). Studying teacher education: The report of the AERA panel on research and teacher education. Mahwah, NJ: Lawrence Erlbaum Associates.
  4. Anderson, C. W. (2007). Perspectives on science learning. In S. K. Abell & N. G. Lederman (Eds.), Handbook of research on science education (pp. 3-30). Mahwah, NJ: Lawrence Erlbaum Associates.
  5. Ball, D. L., & Cohen, D. K. (1992). Reform by the book: What is—or might be—the role of curriculum materials in teacher learning and instructional reform? Educational Researcher, 25(9), 6-8, 14.
  6. Blumenfeld, P. C., Marx, R. W., Patrick, H., Krajcik, J. S., & Soloway, E. (1997). Teaching for understanding. In B. J. Biddle, T. L. Good & I. F. Goodson (Eds.), International handbook of teachers and teaching (pp. 819-878). Dordrecht, The Netherlands: Kluwer Academic.
  7. Borko, H. (2004). Professional development and teacher learning: Mapping the terrain. Educational Researcher, 33(8), 3-15.
  8. Bransford, J. D., Brown, A. L., Cocking, R. R., Donovan, M. S., & Pellegrino, J. W. (2000). How people learn: Brain, mind, experience, and school. Washington, DC: National Academies Press.
  9. Clark, D., & Linn, M. C. (2003). Designing for knowledge integration: The impact of instructional time. The Journal of the Learning Sciences, 12(4), 451-494.
  10. Collins, A., Brown, J. S., & Newman, S. E. (1989). Cognitive apprenticeship: Teaching the crafts of reading, writing, and mathematics. In L. B. Resnick (Ed.), Knowing, learning, and instruction: Essays in honor of Robert Glaser (pp. 453494). Hillsdale, NJ: Lawrence Erlbaum Associates.
  11. (1992). The Jasper series as an example of anchored instruction: Theory, program description, and assessment data. Educational Psychologist, 27(3), 291-315.
  12. Davis, E. A. (2006). Preservice elementary teachers’ critique of instructional materials for science. Science Education, 90(2), 348-375.
  13. Davis, E. A., & Krajcik, J. (2005). Designing educative curriculum materials to promote teacher learning. Educational Researcher, 34(3), 3-14.
  14. Driver, R., Asoko, H., Leach, J., Mortimer, E., & Scott, P. (1994). Constructing scientific knowledge in the classroom. Educational Researcher, 23(7), 5-12.
  15. Driver, R., Guesne, E., & Tiberghien, A. (1985). Children’s ideas in science. Philadelphia: Open University Press.
  16. Duit, R. (2007). Bibliography—STCSE: Students’ and teachers’ conceptions and science education. Retrieved September 10, 2007, from http://www.ipn.uni-kiel.de/aktuell/stcse/ download_stcse.html
  17. Duschl, R. A., Schweingruber, H. A., & Shouse, A. W. (2007). Taking science to school: Learning and teaching science in grades K-8. Washington, DC: National Academies Press.
  18. Eisenhart, M., Finkel, E., & Marion, S. F. (1996). Creating the conditions for scientific literacy: A re-examination. American Educational Research Journal, 33, 261-295.
  19. Ericsson, K. A., Krampe, R. T., & Tesch-Romer, C. (1993). The role of deliberate practice in the acquisition of expert performance. Psychological Review, 100(3), 363-406.
  20. Gee, J. (1996). Social linguistics and literacies: Ideology in discourse (2nd ed.). London: Falmer Press.
  21. Grigg, W. S., Lauko, M. A., & Brockway, D. M. (2006). The Nation’s Report Card: Science 2005. Washington, DC: National Center for Education Statistics.
  22. Kesidou, S., & Roseman, J. E. (2002). How well do middle school science programs measure up? Findings from Project 2061’s curriculum review. Journal of Research in Science Teaching, 39(6), 522-549.
  23. Krajcik, J. S., Czerniak, C., & Berger, C. (2003). Teaching children science in elementary and middle school classrooms: A project-based approach. New York: McGraw-Hill College.
  24. Lee, O., & Buxton, C. (in press). Science curriculum and student diversity: A framework for equitable learning opportunities. The Elementary School Journal.
  25. Lehrer, R., & Schauble, L. (2006). Scientific thinking and science literacy: Supporting development in learning in contexts. In W. Damon, R. M. Lerner, K. A. Renninger, & I. E. Sigel (Eds.), Handbook of child psychology (6th ed., Vol. 4, pp. 153-196). Hoboken, NJ: John Wiley & Sons.
  26. Linn, M. C. (1997). The impact of technology on science instruction: Historical trends and current opportunities. In D. Tobin & B. J. Fraser (Eds.), International handbook of science education (pp. 265-293). Dordrecht, The Netherlands: Kluwer Academic.
  27. Martin, M. O., Mullis, I. V. S., Gonzalez, E. J., & Chrostowski, S. J. (2004). Findings from IEA’s Trends in International Mathematics and Science Study at the fourth and eighth grades. Chestnut Hill, MA: TIMSS & PIRLS International Study Center, Boston College.
  28. Metz, K. E. (1995). Reassessment of developmental constraints on children’s science instruction. Review of Educational Research, 65, 93-127.
  29. National Research Council. (1996). National science education standards. Washington, DC: National Academies Press. No Child Left Behind Act. Public Law No. 107-110, 115 Stat. 1425. (2002)
  30. Perkins, D. (1992). Smart schools: Better thinking and learning for every child. New York: The Free Press.
  31. Pintrich, P. R., Marx, R. W., & Boyle, R. (1993). Beyond cold conceptual change: The role of motivational beliefs and classroom contextual factors in the process of conceptual change. Review of Educational Research, 63(2), 167-199.
  32. Posner, G. J., Strike, K. A., Hewson, P. W., & Gertzog, W. A.(1982). Accommodation of a scientific conception: Toward a theory of conceptual change. Science Education, 66(2), 211-227.
  33. Roseman, J. E., & Koppal, M. (in press). Using national standards to improve K-8 science curriculum materials. The Elementary School Journal.
  34. Roseman, J. E., & Linn, M. C. (in press). Characterizing coherence. In M. C. Linn, J. E. Roseman, & Y. Kali (Eds.), Delineating and evaluating coherent instructional design for education. New York: Teachers College Press.
  35. Roth, K. J., Anderson, C. W., & Smith, E. L. (1987). Curriculum materials, teacher talk and student learning: Case studies in fifth grade science teaching. Journal of Curriculum Studies,19(6), 527-548.
  36. Sanders, L. R., Borko, H., & Lockard, J. D. (1993). Secondary science teachers’ knowledge base when teaching science courses in and out of their area of certification. Journal of Research in Science Teaching, 30(7), 723-736.
  37. Shulman, L. S. (1987). Knowledge and teaching: Foundations of the new reform. Harvard Educational Review, 57(1), 1-22.
  38. Shwartz, Y., Weizman, A., Fortus, D., & Krajcik, J. (in press). The IQWST experience: Coherence as a design principle. The Elementary School Journal.
  39. Strauss, S. (2001). Folk psychology, folk pedagogy and their relations to subject matter knowledge. In B. Torff & R. J. Sternberg (Eds.), Understanding and teaching the intuitive mind (pp. 217-242). Mahwah, NJ: Lawrence Erlbaum Associates.
  40. Vygotsky, L. (1986). Thought and language. A. Kozulin (Trans.). Cambridge, MA: The MIT Press.
  41. Webb, N. M., & Palincsar, A. S. (1996). Group processes in the classroom. In R. C. Calfee & D. C. Berliner (Eds.), Hand-book of educational psychology (pp. 841-873). New York: Prentice Hall.
  42. Zembal-Saul, C., Starr, M. L., & Krajcik, J. (2002). Constructing a framework for elementary science teaching using peda-gogical content knowledge. In J. Gess-Newsome & N. G. Lederman (Eds.), Examining pedagogical content knowledge (Vol. 6, pp. 237-256). Amsterdam: Springer.

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