Supporting research

Model-based inquiry comes out of a number of lines of research in science education. While there is much left to learn, MBI draws from a strong research base as described here.

A shift Toward Scientific Practice

With the recent publication of A Framework for K-12 Science Education (National Research Council [NRC], 2011) and the Next Generation Science Standards (NGSS) (NGSS Lead States, 2013), the ways in which science teachers are being called upon to engage their students in authentic representations of science has shifted. Starting in the 1960s, we moved from a focus on the methods of science to the processes of science (e.g., observing, inferring, and predicting). These processes gave us inquiry as an approach to science teaching emphasizing the skills and abilities of inquiry in order to learn scientific concepts as described in the previous national science standards documents (American Association for the Advancement of Science, 1990; 1993; NRC, 1996; 2000). Since the release of these documents, our understanding of how students learn science (Donovan and Bransford, 2005) and the way science functions (Duschl and Grandy, 2012) has progressed. A new focus on ‘science as practice’ emerged which brought the doing of science and the learning of science content together (Lehrer & Schauble, 2006). As described in Ready, Set, Science!, “science practice involves doing something and learning something in such a way that the doing and learning cannot really be separated” (NRC, 2008, p. 34). 

The new Framework and subsequent standards highlight eight scientific and engineering practices informed by the science studies literature (NGSS Lead States, 2013; NRC, 2011). Taken together, they present an active view of scientific knowledge construction and critique (Ford, 2008), both in science and in the science classroom. They also represent a shift from a linear scientific methodology toward a more realistic view of the epistemic practices of the discipline. They are to be thought of as both learning outcomes and instructional strategies. While many of the scientific practices were present in the previous national standards documents (e.g., planning an investigation, analyzing data), one stands out as a new addition to the lexicon of science teaching: developing and using models. It is the practice of modeling that we highlight as especially productive in engaging students in representations of scientific activity. 

Modeling as an epistemic anchor

Modeling has been slowly gaining traction within the science studies and, recently, the science education communities. Historically, philosophers of science have been more concerned with the creation of scientific theories. Work by science study scholars, however, has illustrated the central role of models, seen as intermediaries between large theories and the phenomenon under study, in the daily work of scientists (Giere, 1988). According to this view, the primary work of scientists is the construction, revision, and testing of hypothetical models (Nersessian, 2008). This new understanding has been taken up in recent years by science education researchers who view the epistemic practice of modeling as central to classroom science with the potential to support authentic scientific inquiry (Duschl & Grandy, 2008; Matthews, 2007; Windschitl, Thompson, & Braaten, 2008). 

This work has culminated in the inclusion of modeling as one of eight key scientific practices highlighted in the NGSS. The standards are based on the assumption that “engaging in the practices of science helps students understand how scientific knowledge develops” while also helping students to “form an understanding of the crosscutting concepts and disciplinary ideas of science and engineering” (NRC, 2012, p. 42). As recently described by Duschl and Grandy (2012), this is a measurable shift from a more traditional view of the nature of science as a set of general principles to be taught as a separate content area. 

While the inclusion of modeling in the standards is an important step forward in engaging science students in authentic experiences, we believe modeling has a larger role to play than indicated with its inclusion as one of eight practices. We, like others, believe modeling can be used as a cognitive and epistemic anchor from which work with the other seven practices can occur (Schwarz & Passmore, 2012; Windschitl, 2012). Put more succinctly, we think of modeling as a reasoning practice that teachers and students can use as an anchor for the complex work of understanding and implementing scientific practices in the classroom to explain phenomena and solve problems. This view is in line with other researchers who have begun examining modeling in a similar fashion. Svodoba and Passmore (2011), for example, developed a framework for model-based instruction that divides modeling into three stages: model construction, model use, and model evaluation. Accordingly, moving between these three categories relies on the use of the other practices. Taken together, the complex task of modeling in classrooms provides the opportunities for teachers to engage students in the scientific practices outlined in the NGSS in an authentic way to authentically represent scientific activity (Manz, 2014).

Ambitious science teaching

As classrooms become more diverse and the demands of learning are accelerated by technological advances educators are being asked to shift teaching to support the learning of all students engaged in cognitively demanding tasks authentic to the discipline and experientially real (Jackson & Cobb, 2010). Enacting these ambitious notions of teaching has been shown to improve diverse students’ knowledge, skills and dispositions toward the STEM disciplines (Boaler, 2002; Franke, Web, Chan, et al., 2009; Thompson, Windschitl and Braaten, 2013). This kind of instruction has been called ambitious teaching because of its attention to elicit and support all students’ thinking and to use this thinking in students’ sense making as they participate in rigorous learning activities (Lampert et al., 2010). Ambitious teaching demands educators provide equitable access to rigorous learning for all students. Windschitl, Thompson, and Braaten (2011; 2012) and Stroupe and Windschitl (2015) have taken on the work of situating ambitious teaching in science education. They have proposed the ambitious science teaching (AST) framework that “deliberately aims to support students of all backgrounds to deeply understand science ideas, participate in the activities of the discipline, and solve authentic problems” (www.ambitiousscienceteaching.org). The AST framework consists of “1) planning a unit around a “big science idea”, 2) eliciting and activating students’ ideas about a puzzling phenomenon (for the purpose of adapting instruction), 3) helping students make sense of science activities, and 4) pressing students to construct evidence-based explanations” (p. 1). 

The details of AST’s four core practices are informed by multiple literatures, including: classroom discourse, using students’ out-of-school knowledge and experiences as resources, science-as-practice, meta-cognition, scaffolding, formative assessment, individual and collective reasoning in science settings, the use of representations, and equity. AST seeks to incorporate these ideas to articulate a coherent and comprehensive vision of instruction grounded in a set of practices that work together to achieve learning and participation goals for students. While these all represent sophisticated ideas about instruction, they are not represented as models for teaching, nor do they speak to the curricular components necessary to enable such instruction. AST is designed to be relevant across curricular models (e.g., problem-based instruction, the 5E instructional model).

Model-based inquiry as a promising model

As modeling is central to doing science, it should also be central to learning about science (NRC, 2008). The inclusion of the complex practice of modeling in the classroom, however, can be a daunting task (Kahn, 2011). Over the past decade, multiple research teams in science education have begun to tackle the work of providing a structure for modeling in the classroom. This has culminated in what can loosely be described as model-based inquiry (MBI), that encompasses various related but distinct sequences of instructional activities and lessons that provide structure for teachers to integrate modeling into their classrooms (Askew & Gray, 2017; Campbell, Oh, & Neilson, 2012, Campbell, Zhang, & Neilson, 2011; Gray, Rogan-Klyve, & Clark-Huyck, 2016; Lehrer & Schauble, 2012; Passmore, Stewart & Cartier, 2009; Windschitl, Thompson, & Braaten, 2008). For example, in their earlier work as a precursor to their current focus on Ambitious Science Teaching Windschitl, Thompson, and Braaten (2008) began to conceptualize MBI as an alternative vision of scientific investigation and as a replacement for the scientific method. They describe MBI as a “system of activity and discourse that engages learners more deeply with content” (p. 1) in which the goal is to “develop defensible explanations of the way the natural world works” (p. 15). From this earlier work and others like it across the literature in science education, a number of essential elements of MBI appear. However, little in the way of connecting MBI to theoretically rich cycles of learning and planning connected to just-in-time instructional strategies for easing teachers’ cognitive load during decision-making within instructional planning and facilitation has occurred to date. Therefore, we believe that the MBI template presented here will provide effective and needed supports for explicating a theoretical framework and that will be broadly useful in supporting NGSS implementation, especially at a time when “a lack of high-quality, NGSS-aligned materials” exist (Nextgenscience.org, 2014, n.p.). 

References

Ambitious Science Teaching. (2015). Models and modeling: An introduction. http://uwcoeast.wpengine.com/wp-content/uploads/2014/09/Models-and-Modeling-An-Introduction1.pdf.

American Association for the Advancement of Science [AAAS]. (1990). Science for all Americans. New York: Oxford University Press.

American Association for the Advancement of Science [AAAS]. (1993). Benchmarks for Science Literacy. New York: Oxford University Press.

Askew, J.  & Gray, R.E. (2017). The science of Little Boy: Investigating the chemistry behind the first use of a nuclear weapon in warfare. The Science Teacher, 84(8), 45-51.

Boaler, J. (2002). Experiencing school mathematics: Traditional and reform approaches to teaching and their impact on student learning. Mahwah, New Jersey: Lawrence Erlbaum Associates.

Campbell, T. & Neilson, D. (2016). Explaining ramps with models:  Design strategies and a unit for engaging students in developing and using models. The Science Teacher, 83(5), 33-39.

Campbell, T., Oh, P.S., & Neilson, D. (2012). Discursive modes and their pedagogical functions in model-based inquiry (MBI) classrooms. International Journal of Science Education. 34(15), 2393-2419. DOI:10.1080/09500693.2012.704552

Campbell, T., Zhang, D., & Neilson, D. (2011). Model based inquiry in the high school physics classroom: An exploratory study of implementation and outcomes. Journal of Science Education and Technology, 20(3), 258-269. DOI 10.1007/s10956-010-9251-6.

Cartier, J. L., Smith, M. S., Stein, M. K., & Ross, D. (2013). Five Practices for Orchestrating TaskBased Discussions in Science. Reston, VA: National Council of Teachers of Mathematics.

Donovan, S., & Bransford, J. (2005). Scientific Inquiry and How People Learn. In S. Donovan & J. Bransford (Eds.), (pp. 397–491). Washington, D.C.: National Academies Press.

Duschl, R. A., & Grandy, R. E. (2008). Reconsidering the character and role of inquiry in school science: Framing the debates. In Teaching scientific inquiry: Recommendations for research and implementation, 1-37.

Duschl, R., & Grandy, R. (2012). Two Views About Explicitly Teaching Nature of Science. Science & Education, 23–25. doi:10.1007/s11191-012-9539-4

Ford, M. (2008). ‘Grasp of Practice’ as a Reasoning Resource for Inquiry and Nature of Science Understanding. Science & Education, 17:147–177.

Franke, M. L., Webb, N. M., Chan, A. G., Ing, M., Freund, D., & Batty, D. (2009). Teacher questioning to elicit students' mathematical thinking in elementary school classrooms. Journal of Teacher Education, 60(4), 380-392. 

Giere, R. N. (1988). Explaining Science: A Cognitive Approach. Chicago: University Of Chicago Press.

Gray, R.E., Rogan-Klyve, A., & Clark-Huyck, B. (2016). Using Student-Generated Models to Understand Plate Tectonics. Science Scope, 40(1), 26–34.

Gray, R.E. & Rogan-Klyve, A.M. (2017a). Talking modeling: Examining science teachers' modeling-related talk during a model-based inquiry unit. Manuscript submitted for publication.

Gray, R.E. & Rogan-Klyve, A.M. (2017b). Examining teacher responsiveness to student ideas in model-based learning classrooms. Manuscript in preparation.

Jackson, K., & Cobb, P. (2010). Refining a vision of ambitious mathematics instruction to address issues of equity. Paper presented at the National Council of Teachers of Mathematics Research Annual Conference, San Diego.

Keys, C.W., Hand, B., Prain, V., & Collins, S. (1999). Using the Science Writing Heuristic as a Tool for Learning from Laboratory Investigations in Secondary Science, Journal of Research In Science Teaching, 36(10), 1065-1084.

Khan, S. (2011). What’s missing in model-based teaching. Journal of Science Teacher Education, 22, 535–560.

Lampert, M., Beasley, H., Ghoursseini, H., Kazemi, E., & Franke, M. L. (2010). Using designed instructional activities to enable novices to manage ambitious mathematics teaching. In M. K. Stein & L. Kucan (Eds.), Instructional explanations in the disciplines (pp. 129-141). New York: Springer.

Lehrer, R., & Schauble, L. (2006). Scientific thinking and science literacy. In W. Damon. (Ed.), Handbook of child psychology: Child psychology in practice (6th ed., Vol. 4, pp. 153 – 196). Hoboken, NJ: Wiley.

Lehrer, R., & Schauble, L. (2012). Seeding evolutionary thinking by engaging children in modeling its foundations. Science Education, 96(4), 701–724. doi:10.1002/sce.20475

Manz, E. (2014). Representing student argumentation as functionally emergent from scientific activity.  Review of Educational Research. Advanced online publication, doi 10.3102/0034654314558490 

Matthews, M. R. (2007). Models in science and in science education: an introduction. Science & Education, 16(7-8), 647–652. doi:10.1007/s11191-007-9089-3.

Michaels, S., & O'Conner, C. (2012). Talk science primer. Cambridge, MA: TERC

National Research Council [NRC]. (2000). Inquiry and the National Science Education Standards: A Guide for Teaching and Learning. Washington, D.C.: National Academy Press.

National Research Council. (1996). National science education standards. Washington, DC: National Academy Press.

National Research Council. (2008). Ready, set, science: Putting research to work in K-8 science classrooms. Washington, DC: National Academies Press.

National Research Council. (2011). A framework for K-12 science education: Practices, crosscutting concepts, and core ideas. Committee on a Conceptual Framework for New K-12 Science Education Standards. Board on Science Education, Division of Behavioral and Social Sciences and Education. Washington, DC: National Academies Press.

Nersessian, N. J. (2008). Model-based reasoning in scientific practice. In R. A. Duschl & R. E. Grandy (Eds.), Teaching scientific inquiry: Recommendations for research and implementation (pp. 57–79). Rotterdam, The Netherlands: Sense Publishers.

NGSS Lead States. 2013. Next Generation Science Standards: For States, By States. Washington, DC: The National Academies Press.

Passmore, C. M., Stewart, J. H., & Cartier, J. L. (2009). Model-Based Inquiry and School Science: Creating Connections. School Science and Mathematics, 109(7), 394–402.

Schwarz, C., & Passmore, C. (2012). Preparing for the next generation science standards—developing and using models. National Science Teachers Association Webinar. http://learningcenter.nsta.org/products/symposia_seminars/Ngss/ webseminar6.aspx

Stroupe, D., & Windschitl, M. (2015). Supporting Ambitious Instruction by Beginning Teachers with Specialized Tools and Practices. In J. A. Luft & S. L. Dubois (Eds.), Newly Hired Teachers of Science (pp. 181–196). Rotterdam, The Netherlands: Sense Publishers.

Svoboda, J., & Passmore, C. M. (2011). Models as epistemic anchors: A framework for model-based instruction. Annual Meeting of the American Educational Research Association. New Orleans, LA.

Thompson, J., Hagenah, S., Kang, H., Stroupe, D. Braaten, M., Colley, C., & Windschitl, M. (2016). Rigor and Responsiveness in Classroom Activity. Teachers College Record 118(5), 1-58.

Thompson, J., Hagenah, S., Lohwasser, K., & Laxton, K. (2015). Problems Without Ceilings How Mentors and Novices Frame and Work on Problems-of-Practice. Journal of Teacher Education, 66(4), 363-381.

Thompson, J., Windschitl, M., & Braaten, M. (2013). Developing a theory of ambitious early-career teacher practice. American Educational Research Journal, 50(3), 574-615.

Windschitl, M. (2012). Ambitious teaching as the “new normal” in American science classrooms: How will we prepare the next generation of professional educators? Lecture, Pennsylvania State University.

Windschitl, M., & Thompson, J. (2011). Ambitious Pedagogy by Novice Teachers: Who Benefits From Tool-Supported Collaborative Inquiry into Practice and Why? Teachers College Record, 113(7), 1311–1360.

Windschitl, M., Thompson, J., & Braaten, M. (2008). How Novice Science Teachers Appropriate Epistemic Discourses Around Model-Based Inquiry for Use in Classrooms. Cognition and Instruction, 26(3), 310–378. doi:10.1080/07370000802177193.

Windschitl, M., Thompson, J., Braaten, M., & Stroupe, D. (2012). Proposing a core set of instructional practices and tools for teachers of science. Science Education, 96(5), 878–903. doi:10.1002/sce.21027

A shift toward scientific practice

With the recent publication of A Framework for K-12 Science Education (National Research Council [NRC], 2011) and the Next Generation Science Standards (NGSS) (NGSS Lead States, 2013), the ways in which science teachers are being called upon to engage their students in authentic representations of science has shifted. Starting in the 1960s, we moved from a focus on the methods of science to the processes of science (e.g., observing, inferring, and predicting). These processes gave us inquiry as an approach to science teaching emphasizing the skills and abilities of inquiry in order to learn scientific concepts as described in the previous national science standards documents (American Association for the Advancement of Science, 1990; 1993; NRC, 1996; 2000). Since the release of these documents, our understanding of how students learn science (Donovan and Bransford, 2005) and the way science functions (Duschl and Grandy, 2012) has progressed. A new focus on ‘science as practice’ emerged which brought the doing of science and the learning of science content together (Lehrer & Schauble, 2006). As described in Ready, Set, Science!, “science practice involves doing something and learning something in such a way that the doing and learning cannot really be separated” (NRC, 2008, p. 34). 

The new Framework and subsequent standards highlight eight scientific and engineering practices informed by the science studies literature (NGSS Lead States, 2013; NRC, 2011). Taken together, they present an active view of scientific knowledge construction and critique (Ford, 2008), both in science and in the science classroom. They also represent a shift from a linear scientific methodology toward a more realistic view of the epistemic practices of the discipline. They are to be thought of as both learning outcomes and instructional strategies. While many of the scientific practices were present in the previous national standards documents (e.g., planning an investigation, analyzing data), one stands out as a new addition to the lexicon of science teaching: developing and using models. It is the practice of modeling that we highlight as especially productive in engaging students in representations of scientific activity. 

Modeling as an epistemic anchor

Modeling has been slowly gaining traction within the science studies and, recently, the science education communities. Historically, philosophers of science have been more concerned with the creation of scientific theories. Work by science study scholars, however, has illustrated the central role of models, seen as intermediaries between large theories and the phenomenon under study, in the daily work of scientists (Giere, 1988). According to this view, the primary work of scientists is the construction, revision, and testing of hypothetical models (Nersessian, 2008). This new understanding has been taken up in recent years by science education researchers who view the epistemic practice of modeling as central to classroom science with the potential to support authentic scientific inquiry (Duschl & Grandy, 2008; Matthews, 2007; Windschitl, Thompson, & Braaten, 2008). 

This work has culminated in the inclusion of modeling as one of eight key scientific practices highlighted in the NGSS. The standards are based on the assumption that “engaging in the practices of science helps students understand how scientific knowledge develops” while also helping students to “form an understanding of the crosscutting concepts and disciplinary ideas of science and engineering” (NRC, 2012, p. 42). As recently described by Duschl and Grandy (2012), this is a measurable shift from a more traditional view of the nature of science as a set of general principles to be taught as a separate content area. 

While the inclusion of modeling in the standards is an important step forward in engaging science students in authentic experiences, we believe modeling has a larger role to play than indicated with its inclusion as one of eight practices. We, like others, believe modeling can be used as a cognitive and epistemic anchor from which work with the other seven practices can occur (Schwarz & Passmore, 2012; Windschitl, 2012). Put more succinctly, we think of modeling as a reasoning practice that teachers and students can use as an anchor for the complex work of understanding and implementing scientific practices in the classroom to explain phenomena and solve problems. This view is in line with other researchers who have begun examining modeling in a similar fashion. Svodoba and Passmore (2011), for example, developed a framework for model-based instruction that divides modeling into three stages: model construction, model use, and model evaluation. Accordingly, moving between these three categories relies on the use of the other practices. Taken together, the complex task of modeling in classrooms provides the opportunities for teachers to engage students in the scientific practices outlined in the NGSS in an authentic way to authentically represent scientific activity (Manz, 2014).

Ambitious science teaching

As classrooms become more diverse and the demands of learning are accelerated by technological advances educators are being asked to shift teaching to support the learning of all students engaged in cognitively demanding tasks authentic to the discipline and experientially real (Jackson & Cobb, 2010). Enacting these ambitious notions of teaching has been shown to improve diverse students’ knowledge, skills and dispositions toward the STEM disciplines (Boaler, 2002; Franke, Web, Chan, et al., 2009; Thompson, Windschitl and Braaten, 2013). This kind of instruction has been called ambitious teaching because of its attention to elicit and support all students’ thinking and to use this thinking in students’ sense making as they participate in rigorous learning activities (Lampert et al., 2010). Ambitious teaching demands educators provide equitable access to rigorous learning for all students. Windschitl, Thompson, and Braaten (2011; 2012) and Stroupe and Windschitl (2015) have taken on the work of situating ambitious teaching in science education. They have proposed the ambitious science teaching (AST) framework that “deliberately aims to support students of all backgrounds to deeply understand science ideas, participate in the activities of the discipline, and solve authentic problems” (www.ambitiousscienceteaching.org). The AST framework consists of “1) planning a unit around a “big science idea”, 2) eliciting and activating students’ ideas about a puzzling phenomenon (for the purpose of adapting instruction), 3) helping students make sense of science activities, and 4) pressing students to construct evidence-based explanations” (p. 1). 

The details of AST’s four core practices are informed by multiple literatures, including: classroom discourse, using students’ out-of-school knowledge and experiences as resources, science-as-practice, meta-cognition, scaffolding, formative assessment, individual and collective reasoning in science settings, the use of representations, and equity. AST seeks to incorporate these ideas to articulate a coherent and comprehensive vision of instruction grounded in a set of practices that work together to achieve learning and participation goals for students. While these all represent sophisticated ideas about instruction, they are not represented as models for teaching, nor do they speak to the curricular components necessary to enable such instruction. AST is designed to be relevant across curricular models (e.g., problem-based instruction, the 5E instructional model).

Model-based inquiry as a promising model

As modeling is central to doing science, it should also be central to learning about science (NRC, 2008). The inclusion of the complex practice of modeling in the classroom, however, can be a daunting task (Kahn, 2011). Over the past decade, multiple research teams in science education have begun to tackle the work of providing a structure for modeling in the classroom. This has culminated in what can loosely be described as model-based inquiry (MBI), that encompasses various related but distinct sequences of instructional activities and lessons that provide structure for teachers to integrate modeling into their classrooms (Askew & Gray, 2017; Campbell, Oh, & Neilson, 2012, Campbell, Zhang, & Neilson, 2011; Gray, Rogan-Klyve, & Clark-Huyck, 2016; Lehrer & Schauble, 2012; Passmore, Stewart & Cartier, 2009; Windschitl, Thompson, & Braaten, 2008). For example, in their earlier work as a precursor to their current focus on Ambitious Science Teaching Windschitl, Thompson, and Braaten (2008) began to conceptualize MBI as an alternative vision of scientific investigation and as a replacement for the scientific method. They describe MBI as a “system of activity and discourse that engages learners more deeply with content” (p. 1) in which the goal is to “develop defensible explanations of the way the natural world works” (p. 15). From this earlier work and others like it across the literature in science education, a number of essential elements of MBI appear. However, little in the way of connecting MBI to theoretically rich cycles of learning and planning connected to just-in-time instructional strategies for easing teachers’ cognitive load during decision-making within instructional planning and facilitation has occurred to date. Therefore, we believe that the MBI template presented here will provide effective and needed supports for explicating a theoretical framework and that will be broadly useful in supporting NGSS implementation, especially at a time when “a lack of high-quality, NGSS-aligned materials” exist (Nextgenscience.org, 2014, n.p.). 

References

Ambitious Science Teaching. (2015). Models and modeling: An introduction. http://uwcoeast.wpengine.com/wp-content/uploads/2014/09/Models-and-Modeling-An-Introduction1.pdf.

American Association for the Advancement of Science [AAAS]. (1990). Science for all Americans. New York: Oxford University Press.

American Association for the Advancement of Science [AAAS]. (1993). Benchmarks for Science Literacy. New York: Oxford University Press.

Askew, J.  & Gray, R.E. (2017). The science of Little Boy: Investigating the chemistry behind the first use of a nuclear weapon in warfare. The Science Teacher, 84(8), 45-51.

Boaler, J. (2002). Experiencing school mathematics: Traditional and reform approaches to teaching and their impact on student learning. Mahwah, New Jersey: Lawrence Erlbaum Associates.

Campbell, T. & Neilson, D. (2016). Explaining ramps with models:  Design strategies and a unit for engaging students in developing and using models. The Science Teacher, 83(5), 33-39.

Campbell, T., Oh, P.S., & Neilson, D. (2012). Discursive modes and their pedagogical functions in model-based inquiry (MBI) classrooms. International Journal of Science Education. 34(15), 2393-2419. DOI:10.1080/09500693.2012.704552

Campbell, T., Zhang, D., & Neilson, D. (2011). Model based inquiry in the high school physics classroom: An exploratory study of implementation and outcomes. Journal of Science Education and Technology, 20(3), 258-269. DOI 10.1007/s10956-010-9251-6.

Cartier, J. L., Smith, M. S., Stein, M. K., & Ross, D. (2013). Five Practices for Orchestrating TaskBased Discussions in Science. Reston, VA: National Council of Teachers of Mathematics.

Donovan, S., & Bransford, J. (2005). Scientific Inquiry and How People Learn. In S. Donovan & J. Bransford (Eds.), (pp. 397–491). Washington, D.C.: National Academies Press.

Duschl, R. A., & Grandy, R. E. (2008). Reconsidering the character and role of inquiry in school science: Framing the debates. In Teaching scientific inquiry: Recommendations for research and implementation, 1-37.

Duschl, R., & Grandy, R. (2012). Two Views About Explicitly Teaching Nature of Science. Science & Education, 23–25. doi:10.1007/s11191-012-9539-4

Ford, M. (2008). ‘Grasp of Practice’ as a Reasoning Resource for Inquiry and Nature of Science Understanding. Science & Education, 17:147–177.

Franke, M. L., Webb, N. M., Chan, A. G., Ing, M., Freund, D., & Batty, D. (2009). Teacher questioning to elicit students' mathematical thinking in elementary school classrooms. Journal of Teacher Education, 60(4), 380-392. 

Giere, R. N. (1988). Explaining Science: A Cognitive Approach. Chicago: University Of Chicago Press.

Gray, R.E., Rogan-Klyve, A., & Clark-Huyck, B. (2016). Using Student-Generated Models to Understand Plate Tectonics. Science Scope, 40(1), 26–34.

Gray, R.E. & Rogan-Klyve, A.M. (2017a). Talking modeling: Examining science teachers' modeling-related talk during a model-based inquiry unit. Manuscript submitted for publication.

Gray, R.E. & Rogan-Klyve, A.M. (2017b). Examining teacher responsiveness to student ideas in model-based learning classrooms. Manuscript in preparation.

Jackson, K., & Cobb, P. (2010). Refining a vision of ambitious mathematics instruction to address issues of equity. Paper presented at the National Council of Teachers of Mathematics Research Annual Conference, San Diego.

Keys, C.W., Hand, B., Prain, V., & Collins, S. (1999). Using the Science Writing Heuristic as a Tool for Learning from Laboratory Investigations in Secondary Science, Journal of Research In Science Teaching, 36(10), 1065-1084.

Khan, S. (2011). What’s missing in model-based teaching. Journal of Science Teacher Education, 22, 535–560.

Lampert, M., Beasley, H., Ghoursseini, H., Kazemi, E., & Franke, M. L. (2010). Using designed instructional activities to enable novices to manage ambitious mathematics teaching. In M. K. Stein & L. Kucan (Eds.), Instructional explanations in the disciplines (pp. 129-141). New York: Springer.

Lehrer, R., & Schauble, L. (2006). Scientific thinking and science literacy. In W. Damon. (Ed.), Handbook of child psychology: Child psychology in practice (6th ed., Vol. 4, pp. 153 – 196). Hoboken, NJ: Wiley.

Lehrer, R., & Schauble, L. (2012). Seeding evolutionary thinking by engaging children in modeling its foundations. Science Education, 96(4), 701–724. doi:10.1002/sce.20475

Manz, E. (2014). Representing student argumentation as functionally emergent from scientific activity.  Review of Educational Research. Advanced online publication, doi 10.3102/0034654314558490 

Matthews, M. R. (2007). Models in science and in science education: an introduction. Science & Education, 16(7-8), 647–652. doi:10.1007/s11191-007-9089-3.

Michaels, S., & O'Conner, C. (2012). Talk science primer. Cambridge, MA: TERC

National Research Council [NRC]. (2000). Inquiry and the National Science Education Standards: A Guide for Teaching and Learning. Washington, D.C.: National Academy Press.

National Research Council. (1996). National science education standards. Washington, DC: National Academy Press.

National Research Council. (2008). Ready, set, science: Putting research to work in K-8 science classrooms. Washington, DC: National Academies Press.

National Research Council. (2011). A framework for K-12 science education: Practices, crosscutting concepts, and core ideas. Committee on a Conceptual Framework for New K-12 Science Education Standards. Board on Science Education, Division of Behavioral and Social Sciences and Education. Washington, DC: National Academies Press.

Nersessian, N. J. (2008). Model-based reasoning in scientific practice. In R. A. Duschl & R. E. Grandy (Eds.), Teaching scientific inquiry: Recommendations for research and implementation (pp. 57–79). Rotterdam, The Netherlands: Sense Publishers.

NGSS Lead States. 2013. Next Generation Science Standards: For States, By States. Washington, DC: The National Academies Press.

Passmore, C. M., Stewart, J. H., & Cartier, J. L. (2009). Model-Based Inquiry and School Science: Creating Connections. School Science and Mathematics, 109(7), 394–402.

Schwarz, C., & Passmore, C. (2012). Preparing for the next generation science standards—developing and using models. National Science Teachers Association Webinar. http://learningcenter.nsta.org/products/symposia_seminars/Ngss/ webseminar6.aspx

Stroupe, D., & Windschitl, M. (2015). Supporting Ambitious Instruction by Beginning Teachers with Specialized Tools and Practices. In J. A. Luft & S. L. Dubois (Eds.), Newly Hired Teachers of Science (pp. 181–196). Rotterdam, The Netherlands: Sense Publishers.

Svoboda, J., & Passmore, C. M. (2011). Models as epistemic anchors: A framework for model-based instruction. Annual Meeting of the American Educational Research Association. New Orleans, LA.

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