proposing a core set of instructional practices and tools for teachers of science

ScienceEducation

SCIENCE EDUCATION POLICY

Proposing a Core Set of InstructionalPractices and Tools for Teachers ofScience

MARK WINDSCHITL,1 JESSICA THOMPSON,1 MELISSA BRAATEN,2

DAVID STROUPE1

1Department of Curriculum and Instruction, University of Washington, Seattle, WA98195, USA; 2Department of Curriculum and Instruction, University of Wisconsin,Madison, WI 53706, USA

Received 15 July 2011; accepted 22 May 2012DOI 10.1002/sce.21027Published online 9 August 2012 in Wiley Online Library (wileyonlinelibrary.com).

ABSTRACT: Recent calls for teacher preparation to become more grounded in practiceprompt the questions: Which practices? and perhaps more fundamentally, what counts as amodel of instruction worth learning for a new professional—i.e., the beginner’s repertoire?In this report, we argue the following: If a defined set of subject-specific high-leveragepractices could be articulated and taught during teacher preparation and induction, thebroader teacher education community could collectively refine these practices as well as thetools and other resources that support their appropriation by novices across various learning-to-teach contexts. To anchor our conversation about these issues, we describe the evolution,in design, and enactment, of a “candidate core” and a suite of tools that supported theapproximation of equitable and rigorous pedagogy for several groups of beginning scienceteachers. Their struggles and successes in taking up ambitious practice informed not onlyour designs for a beginner’s repertoire but also a system of tools and socioprofessionalroutines that could foster such teaching over time. C© 2012 Wiley Periodicals, Inc. Sci Ed

96:878 – 903, 2012

Correspondence to: Mark Windschitl; e-mail: [email protected] grant sponsor: Teachers for a New Era Project by the Carnegie Corporation, Annenberg

Foundation, and the Rockefeller Foundation.Contract grant sponsor: National Science Foundation.Contract grant number: DRL-0822016.Any opinions, findings, and conclusions or recommendations expressed in this material are those of the

authors and do not necessarily reflect the views of the funding organizations.

C© 2012 Wiley Periodicals, Inc.

PROPOSING A CORE 879

INTRODUCTION

Of all factors linked with student achievement in schools, the day-to-day practicesof teachers exert the most powerful influence on learning (Clotfelter, Ladd, & Vigdor,2007; Rivkin, Hanushek, & Kain, 2005; Rockoff, 2004). For the most capable educators,their capacity to mediate learning grows out of a professional repertoire that is complex,relational, grounded in deep understanding of subject matter, and adaptive to learners’ needs.This, however, is not the initial trajectory of practice that most novices are prepared for.There is evidence that typical training experiences for teachers focus more on managing bothmaterial activities and students themselves and less on designing opportunities for studentsto reason about science ideas (Adams & Krockover, 1997; Freese, 2006; Grossman et al.,2009; Levine, 2006). In science teacher preparation, these experiences are often combinedwith broad approaches like “inquiry,” “hands-on work,” or “standards-based teaching”which are so conceptually ill-defined and elastic that they do not help novices understandhow specific kinds of interactions with students facilitate learning (Gess-Newsome &Lederman, 1993; Ingersoll, 1996). More broadly, instruction about instruction in manyteacher-training programs is not informed by the knowledge based on teacher or studentlearning (Rand, 2002; U.S. Department of Education, 2008). Rather, chances for novicesto learn are constrained by the past experiences, skills, and worldviews of their instructorsand cooperating teachers (Ball, Sleep, Boerst, & Bass, 2009; Deussen, Coskie, Robinson,& Autio, 2007; Little, 1990).

These are not merely issues of individual preparation programs, rather this problembelongs to the field of teacher education. Without the field drawing upon a collectiveknowledge base about teaching, there can be no common language across institutionsabout valued classroom practices nor testable theory of how novices learn to design andenact effective instruction (Hiebert, Gallimore, & Stigler, 2002). As a consequence, thereexist no sharable and empirically grounded tools or curricular resources to prepare teachersfor science instruction.

In this essay, we open up a conversation about these problems of preparation by exploringthree interrelated ideas. First, we address how an emphasis on specific and skilled practicesis being used by the larger education community to reconceptualize the work of teachingfrom an individually developed craft to a more knowledge-based and systematic enterprisethat is tied to meaningful forms of student learning. To more clearly articulate what thegoals of such instruction might be for experienced or beginning educators, we borrowthe idea of ambitious teaching from the literature of mathematics and secondary literacyeducation. Ambitious teaching does not specify practices; however, it does represent theidea that rigorous and equitable teaching is within the grasp of most practitioners, eventhose just entering the profession.

Drawing upon the idea of ambitious teaching, we then argue for the development ofa set of research-based core practices for beginning educators that are limited in numberand represent broadly applicable instructional strategies known to foster important kinds ofstudent engagement and learning. These practices would not replace novices’ experienceswith assessment, curriculum planning, use of material resources, etc., but rather they wouldact as an organizational framework into which these other components would be integratedduring preparation. This core would serve as a strong teaching foundation, which novicescould continually build upon and refine during their careers. While there are some cautionaryinterpretations of what this could mean for the design of preparation experiences (e.g., thetechnical reductionism of the work of teaching or promoting industrial models of training),we believe that a principled focus on practice opens up an important opportunity forthe teacher education community, one that is both responsive to current policy pressures

Science Education, Vol. 96, No. 5, pp. 878–903 (2012)

880 WINDSCHITL ET AL.

around accountability and one that allows a leadership role in reforming preparation. Theopportunity is to contribute to an evidence-informed system of learning activities, tools,and formative assessments tailored to the needs of teaching novices that can support theircontinuous progress toward effective and equitable classroom instruction (Bryk, 2009; D.Cohen, 2011; Cobb, Zhao, & Dean, 2009; Raudenbush, 2008). These resources wouldbe “owned” and collectively refined by a community of practitioners and scholars. Thecore practices themselves could be adapted, elaborated upon, and field-tested in differentsituations, but always against evidence of increased student participation and learning. Acore would also furnish a common language to pose and solve problems of practice. Thefoundations for this endeavor include defining a set of practices that are fundamental tosupport K-12 student learning, and that can be taught, learned, and implemented by thoseentering the profession.

The third issue we address is the critical role that tools for teachers could play whena set of practices is shared within a community of novices and teacher educators. Weillustrate, for example, that once a practice is known to support learning—a practice suchas eliciting and building upon students’ science ideas—and can be described in terms ofprototypical activities and discursive interactions between the teacher and students, thentools that prepare teachers to engage in this form of work can be fashioned, tested inclassrooms, and refined over time.

To anchor our conversation about these issues, we describe the evolution, in design, andenactment, of a “candidate core” and a suite of tools that supported the approximation ofequitable and rigorous pedagogy for several groups of beginning science teachers. Theirstruggles and successes in taking up ambitious practice informed not only our designsfor a beginner’s repertoire but also a system of tools and socioprofessional routines thatcould foster such teaching over time. The most unexpected revisions to our developingtheory of practice and tools, in fact, came after observing the inventiveness of our novicesin classrooms as they used the core as a platform to create their own shared set of toolsfor directly scaffolding students’ scientific discourse and activity. What began then as aset of researcher-designed structures for supporting teacher preparation evolved througha socially driven process where the least experienced members of the community wouldcontribute system-altering innovations.

TEACHING AS SKILLED WORK

Recent calls for teacher education to become more grounded in practice (AmericanAssociation of Colleges for Teacher Education, 2010; Grossman & McDonald, 2008;Hammerness, Darling-Hammond, & Bransford, 2005; Levine, 2006) prompt the questions:Which practice(s)? and perhaps more fundamentally, what counts as a model of instructionworth learning for a beginning professional? The lack of focus within and across preparationprograms has prompted some teacher educators (e.g., Franke & Chan, 2007) to proposea rethinking of how novices can begin to learn—through the development of a set ofhigh-leverage instructional practices for use in K-12 classrooms that can be taught to andimplemented by beginning educators. This set of practices would be anchored in importantlearning goals for K-12 students, in the literature of how students learn, and in emerginglongitudinal research about how novices learn to teach.

Our vision is that selected high-leverage practices (HLPs) make up the core repertoireof ambitious teaching. The idea of ambitious teaching is being developed by researchersin multiple subject matter areas including science, mathematics, and secondary literacy.Consensus has emerged as to its aims—to get students of all racial, ethnic, class, andgender categories to engage deeply with science. This involves structuring opportunities



for learners to reason about key subject matter ideas, participate in the discourses of thediscipline, and solve authentic problems (D. K. Cohen, 1989; Lampert & Graziani, 2009;Newmann & Associates, 1996). In the science classroom, this means that students learnto generate coherent explanations of natural phenomena using a variety of intellectual andsocial resources; they understand how claims are justified, how to represent their thinkingto others, critique one another’s ideas in ways that are civil and productive, and revisetheir ideas in response to evidence and argument. The hallmark of this pedagogy is itsadaptiveness to students’ needs and thinking, and examples of this approach have set newstandards for rigor and equity in practice across several subject matter areas (Fennema,Franke, Carpenter, & Carey, 1993; Hill, Rowan, & Ball, 2005; C. Lee, 2007; Rosebery,Warren, & Conant, 1992; Smith, Lee, & Newmann, 2001; Warren & Rosebery, 1996).

These forms of practice are rare, even in the classrooms of experienced teachers. Large-scale observational studies have documented that in American classrooms there is a focuson activity rather than sense making and that questioning in general is among weakestelements of instruction. Only a small fraction of lessons take into account students’ priorknowledge and teachers seldom press for explanations (Alexander, Osborn, & Phillips,2000; Banilower, Smith, Weiss, & Pasley, 2006; Horizon Research International, 2003;Roth & Garnier, 2007; Weiss, Banilower, McMahon, & Smith, 2001). Ambitious teachingis labeled as such in part because there are so few models of it in school settings and becausemany of the tools, norms, rituals, and resources in schools are aimed at maintaining “teacherdominated discourse, textbook based lessons, and coverage as the main curricular principle”(Sykes, Bird, & Kennedy, 2010, p. 465).

A proposal that specifies a core of practices for beginning educators will require a culturalshift in how learning to teach is conceptualized by many stakeholders in the current systemof preparation. Popular images portray classroom instruction as independently creativeand shaped by artisanal efforts that defy prescription (D. Cohen, 2011). In this view,good teaching, rather than being a product of specialized knowledge and skills, appearsto be a set of behaviors “picked up” through the accumulation of on the job experiences(Jackson, 1986; Murray, 1989). This stance reinforces the current “bias against detailedprofessional [teacher] training” (Ball & Forzani, 2009, p. 497), and, when designed intopreparation experiences, reproduces well-intentioned beginners who enact inherited ritualsof classroom activity and routinely underestimate what students are capable of.

To move any core-based agenda forward, folk theories about teachers spontaneously“discovering” elements of sophisticated practice over time (such as how to scaffold differentforms of reasoning in students, how to structure equitable interactions between learnerswith differing abilities, how to use formative assessments, or support student metacognition)have to be replaced with more accurate language and images of teaching as requiring acomplex of skills that must be modeled, taught to, and appropriated by novices, andempirically linked with student learning. This focus on specific and accountable practicealready figures prominently in the school leadership literature. City, Elmore, Fiarman, andTeitel (2009) advocate that K-12 teachers, principals, and district personnel codevelopan instructional core, which can guide institutional efforts at professional improvement.Without it they caution, schools tend to “sanction unacceptably large variations in teachingfrom one classroom to another with rhetoric about instruction as style, art, or craft” (p. 188).Bryk (2009) spells out a similar theory of action around the organization for professionallearning in schools:

[An instructional system] involves some very specific pedagogical practices and socialroutines and expects automaticity in their use. Educators have a shared language aboutgoals for students and understand how these align over time around some larger conception



of student learning. Teachers also share a common evidence base about what constituteslearning. This allows them to analyze and refine the cause-and-effect logic that organizestheir shared work. Finally, tying this all together is an explicit process for socializingnew members into the community and for organizing ongoing social learning among allparticipants. (pp. 599–600)

Both examples above represent new ways of considering the professional responsibili-ties of educators while effectively working against public stereotypes of teaching as aknowledge-weak practice. We note, however, that proposals selecting for particular in-structional practices over others for use in teacher preparation should be examined closely.The research fields contributing to teaching have only roughly sketched out what the con-ditions and characteristic activities are that appear to support different types of studentlearning. How instruction could be parsed into meaningful “practices” that would set up theconditions for learning is equally underdeveloped even after decades of discussion about it(L. S. Shulman, 1992). Despite these limitations, there are fairly robust and agreed-upontheoretical principles for the construction of learning environments/situations, we also havesome understanding of the characteristics of expert teaching. In addition, recent studies ofhow beginning teachers learn to engage in valued classroom practices are providing newinsights into how early career training might be structured. We draw upon these knowledgebases, both theoretical and empirical, to suggest what a core set of practices and theirsupporting tools might look like. It is important to note that “putting a stake in the ground,”as we do here, does not suggest that answers have been found. Rather, we propose a wayof thinking about a significant problem in our system of teacher preparation. Our modelis presented to invite criticism, serve as a basis for alternative strategies, and in general toadvance a conversation about the development of beginning teachers.

RESEARCH INFORMING THE DEVELOPMENT OF A CORE

Using the Literature on High-Leverage Practices

By “practices” we refer to routine activities teachers engage in devoted to planning,enactment, or reflection that are intended to support student learning. There are manyrecognizable teacher behaviors that would not be considered a practice, or at least wouldfall farther away from a teacher’s central instructional mission, such as taking attendance,administering standardized tests, or cleaning up after a lab. There are also forms of teacheractivity that could be defined as practices, but for various reasons students learn very littlefrom them. Examples here would include using curriculum without adapting it to the currentunderstanding of students, having students memorize lists of facts, or providing written ororal feedback to students in the form of “correct” or “incorrect.” In identifying HLPs, webegin with the simple assertion that of all the interactions teachers can have with studentsaround subject matter, some types have greater potential than others to engage younglearners in productive intellectual work. Of these, a smaller number can be selected, basedon four sets of criteria, that are suitable for early career teachers to build their emergingrepertoire upon. The first two of these criteria have been developed within the mathematicseducation community and in particular by Franke and Chan (2007) and Ball and colleagues(we paraphrase from 2009, p. 460).

The first set of criteria selects for practices that are applicable to the everyday work ofteaching. Such practices are used frequently. They apply to different approaches in teachingas well as to different topics within science, and they support student work that is central tothe discipline of the subject matter. In addition, these practices must support the learning



and achievement of all students. One HLP that meets these requirements might be labeled“supporting students in developing scientific explanations.” This is a strategy that could beused at any grade level for any science topic, and in its most effective instantiations, couldhelp teachers build upon the everyday experiences, language, and ideas that students bringto the classroom.

The second set of criteria relates to the work of teacher preparation. Practices must beconceptually accessible to learners of teaching, which means that they have to be able tobe articulated and taught by more knowledgeable others. They then must be able to bepracticed by beginners in their university and field-based settings, and in the process berevisited in increasingly sophisticated and integrated acts of teaching. In addition, theseHLPs should have features that readily allow novices to learn from their own teaching(Hatch & Grossman, 2009). An example here would be instructional routines that makeK-12 students’ thinking visible and creates a record of students’ developing ideas andlanguage across a unit of instruction in forms that allow novices to reconcile these shiftswith instructional decisions they made along the way. The criteria of being accessible,teachable, rehearse-able, and an activity one can learn from are at least partially influencedby the grain size of selected practices. Scholars studying HLPs in various subject mattersdiffer here about “what counts” as a practice and at what grain size novices should beginto approximate teaching activities. Within the context of secondary English instruction,Hatch and Grossman (2009), for example, consider orchestrating class discussions as apractice. They conceptualize smaller scale actions such as modeling features of academicdiscourse as “teaching moves.” In mathematics, Boerst and Sleep (2007) refer to whole-class discussions as a “domain,” which can be broken down into “practices” such as elicitingstudents’ ideas, which are themselves composed of smaller scale “techniques for teaching”such as revoicing or using wait time (examples from Lampert, 2010). These questions ofscale and how levels of practice are conceptualized can reflect different theories of learningto teach, each with its own challenges for rehearsal, feedback, and implementation in theclassroom. We do not intend to address these particular issues here; however, for the sakeof transparency, our preference is to consider core practices at the level of a coordinated setof teacher–student interactions, generally occurring over a class period, for an expressedlearning purpose. This level of practice integrates multiple activity structures within a classperiod (e.g., warm-up, small-group work, whole-class sense making) and the transitionsbetween them. Ideas and discourse from each of these smaller episodes necessarily buildupon one another to support a particular learning goal (e.g., helping students use evidencefrom a lab activity to refine scientific explanations).

Returning now to our criteria for identifying HLPs, the third selects for clusters ofpractices that build upon one another instructionally and play recognizable roles together ina coherent system of teaching. Such a system would explicitly support more comprehensivestudent learning goals and embody a broader theory of action about the relationshipsbetween instruction and learning than would the individual practices. In practical terms,the whole would add up to more than the sum of its parts.

The fourth criterion is disciplined selection. Our belief is that HLPs should be few innumber to reflect priorities of equitable and effective teaching and to allow significant timefor novices to develop and receive feedback on approximations of each of these practices.Furthermore, if the identification of core practices is considered a task that the field engagesin (rather than being selected by an institution or instructor), then making principled choicesabout what is not going to be part of a core set will be a critical consideration. The ideais to collectively select and refine rather than to accumulate practices that comprise aninstructional core.



Using Literature From the Subject Matter Area

Core practices should reflect the disciplinary nature of talk and development of ideaswithin that subject matter area. In science, goals for student learning in K-12 classroomshave been consistent across all recent reform documents (summarized in National ResearchCouncil [NRC], 1996, 2005, 2007, 2011); however, these messages provide only sugges-tions as to what teachers should be able to do and tell us little about the fundamental skillsand understanding required to foster valuable kinds of teacher performance. For example,Science Teaching Standard B in Inquiry and The National Science Education Standards(NRC, 2000, p. 22) states that “Teachers guide and facilitate learning. In doing this, teachersorchestrate discourse among students about science ideas.” After reading this, teachers andteacher educators may well ask, “What does this discourse sound like?”; “Who is sayingwhat to whom?” This document also offers “instructional models” vignettes of masterteachers, but even these do not clearly communicate a structure for interaction amongteacher and students.

Similarly, the recent consensus publication Taking Science To School (NRC, 2007) pointsout elements of classroom activity that have been shown to support student learning goals.Again, however, the purpose of this volume was not to serve as a reference for guidingteacher preparation by articulating details of practice. Nonetheless, it has done an exemplaryjob of summarizing the proficiencies for students and, we believe, for teachers who areresponsible for guiding young science learners. Students and teachers, for example, shouldbe able to

• understand, use, and interpret scientific explanations of the natural world,• generate and evaluate scientific evidence and explanations,• understand the nature and development of scientific knowledge, and• participate productively in scientific practices and discourse (p. 334).

The last of these proficiencies—that students should participate in disciplinary activityand talk—has been highlighted as foundational in the Framework for the Next GenerationScience Standards (NRC, 2011). This document features eight scientific practices thatstudents should engage with, including asking questions, developing and using models,planning and carrying out investigations, analyzing and interpreting data, constructingexplanations, and engaging in argument from evidence. Unfortunately, these intellectuallyrich activities have a history of being proceduralized in classrooms, often to the point ofbeing treated as unrelated science tasks, and unrelated to important science ideas (Alexanderet al., 2000; Banilower et al., 2006; Horizon Research International, 2003; Roth & Garnier,2007; Weiss et al., 2001). So, as the science education community becomes more explicitabout its aims for instruction, even to the point of describing developmental progressionsfor how students can engage with these practices and ideas, the classroom teaching tosupport these valued goals remains underdefined and undertheorized. This presents a clearproblem for teacher training. In the following section, we describe how we used the reformdocuments as well as the literature on instruction and student learning to provide muchneeded specification for how teachers might design productive classroom interactions.

ASSEMBLING A CANDIDATE CORE AND ITS SUPPORTING TOOLS

Model-Based Inquiry as an Organizing Framework

The task of assembling a core required that we simultaneously consider individualpractices along with ways to organize these practices into a coherent framework to guide



teaching. Coherence and face validity for the novices are important because the literature onprofessional performance shows that individuals cannot engage in complex work without aplausible theory of action that guides their problem posing and problem solving (Berliner,1994; Bransford, Brown, & Cocking, 2000; Hogan, Rabinowitz, & Craven, 2003). Thereare several existing frameworks for organizing science instruction; however, we consideredthree features, consistent with contemporary research on rigorous and equitable learning,to be important in making a final selection. First, we sought a systematic approach thatsupported students in deeply understanding science concepts through constructing andrevising causal explanations (“why” explanations) for natural phenomena. Second, partici-pation structures had to be included that were designed to apprentice young learners not justinto the material and data manipulations of science but into the kinds of epistemic languageand disciplinary thinking described in the Framework for the Next Generation ScienceStandards (NRC, 2011; see also Nersessian, 2002, and NRC, 2007). Third—a criterion thatis seldom addressed in current frameworks—students’ everyday language, experiences, andknowledge had to be used as legitimate resources for learning (the teaching done at theCheche Konnen Center is one exception). It is worth noting that procedural schemes like“The Scientific Method” fail all three criteria.

The most promising existing framework to accommodate all three requirements was anadaptation of model-based inquiry (MBI). MBI supports students in developing evidence-based explanations of important phenomena in the natural world. Over the course of anMBI unit, students’ ways of talking about these phenomena, the everyday experiencesthat they relate to this phenomenon, and the partial understandings they bring to theclassroom are elicited and treated as resources for creating these explanations, as arescientific texts, experiments, and canonical ideas of the discipline. The visible anchorsfor the developing explanations are public inscriptions of ideas (i.e., models) that cantake the form of student-produced diagrams, pictorial drawings, and lists of potentialhypotheses. These representations are the stimulus for and products of conversations bystudents. Ideas embodied in students’ models are iteratively tested and refined, based onmultiple investigations, readings, and discussions. Students then explore how their models,and scientific models in general, are held to standards of predictive power or explanatorycoherence, and they apply their models to new situations (see Lesh et al., 2000; Metcalf,Krajcik, & Soloway, 2000; Stewart et al., 2005; Windschitl, Thompson, & Braaten, 2008).Making meaning of science in these ways is demanding for students; however, there areaccounts of elementary-age learners readily engaging in this kind of reasoning (Lehrer &Schauble, 2006; Magnusson & Palincsar, 2005); these forms of inquiry can also narrowgaps in achievement between underrepresented groups and majority students (White &Fredericksen, 1998; Wilson, Taylor, Kowalski, & Carlson, 2010).

The Components of Ambitious Teaching—Four Core Practices andTheir Associated Tools

As we considered MBI for an organizing frame for the design of effective instruction, wealso had to coordinate a set of individual practices that were essential to the project’s aims ofrigor and equity. We eventually identified four HLPs. The first of these is a planning practicecalled constructing the Big Idea. The remaining three are enactment practices that we referto as “Discourses.” These are eliciting students’ ideas to adapt instruction, helping studentsmake sense of material activity, and pressing students for evidence-based explanations.

Our emphasis on classroom talk reflects a growing body of contemporary researchwhich has demonstrated clear ties between students’ opportunities to reason dialogicallywith others and the development of durable forms of understanding. Using a discourse lens,



classrooms are now being viewed as working communities in which the teacher’s principaltask is to mediate increasingly sophisticated forms of academic conversation and activityby the students, rather than have students memorize and reproduce textbook explanations ormerely expose them to activities (Engle, 2011; Leinhardt & Steele, 2005; Minstrell & Kraus,2005; Mortimer & Scott, 2003; Sfard & McClain, 2002). This mediation, in turn, promotesrobust forms of reasoning about complex concepts (Michaels, O’Connor, & Resnick, 2008)and engages learners in the characteristic practices of the discipline—that is, “to formulatequestions about phenomena that interest [students], to build and critique theories, to collect,analyze and interpret data, to evaluate hypotheses through experimentation, observation,measurement, and to communicate findings” (Rosebery et al., 1992, p. 65). From an equityperspective, teacher moves such as eliciting students’ ideas, asking students to explain theirreasoning, and asking students to reflect on their current state of understanding lead todeeper engagement in the content (Duschl & Duncan, 2009) and to sophisticated reasoningby learners who do not typically participate in the academic life of the classroom (Chapin &O’Connor, 2004; Cobb, Boufi, McClain, & Whitenack, 1997; Herrenkohl & Guerra, 1998;Lampert, 2001; C. D. Lee, 2001).

This type of discourse is not characteristic of American classrooms. Even experiencedscience educators are not adept at generating student talk or using it as a social resource forlearning (Horizon Research International, 2003; Roth & Garnier, 2007). Our own researchexperiences with novice teachers allowed us to see more specific ways that beginnersstruggle with organizing classroom talk (Thompson, Windschitl, & Braaten, 2009). Wefollowed a group of teacher candidates through their preservice program, into secondaryclassrooms as they began their internships, then into their first year of teaching. Ourparticipants often knew how to get student conversations started (with a puzzling questionor demonstration) but would report to us that they “didn’t know where they were headed”in the ensuing discussion and perhaps more importantly they were unclear about whatthe purposes of the discussion should be. This was due in part because they had noguiding framework for engaging students in talk that was productive in terms of developingscience ideas and equitable in terms of opportunities for participation by all students. Whendebriefing with participants after observing their classes, even we as instructors were unableto rely on a shared language and set of expectations with them about the classroom talk,and there was little to anchor productive reflection together.

Opportunities to participate in classroom discourse appear to be crucial for student learn-ing. But clearly, beginning teachers have difficulty initiating and maintaining meaningfultalk. In response, we created discourse-based practices (referred to as “Discourses”), mean-ing patterns of instructional moves in which specific interactions (such as offering targetedfeedback to students, asking a student to explain her/his thinking to others, or presentingnew scientific ideas to students) were combined to allow both the teaching novice and younglearners to participate in recognizable genres of activity with characteristic norms and roles.We defined these practices in terms of the intellectual and relational work a teacher woulddo, rather than focus on behavioral correlates of competent practice such as writing learningobjectives on the board, maintaining a brisk classroom pace, or ways to control studentsand maintain their attention as proxies for authentic engagement in academic work.1

Each of these discourses and the planning practice was supported by a specializedtool. Just as teachers can influence students’ opportunities to learn by providing needed

1 These types of strategies have confused “attention” with “engagement.” (See, e.g., one of the strategiesdescribed by Lemov (2010) referred to as Technique #22: Cold Call “—In order to make engaged partici-pation the expectation, call on students regardless of whether they have raised their hands. Cold calling isan engagement strategy, not a discipline strategy.”)



Figure 1. Sample page from discourse tool on “making sense of material activity.”

resources, we believed that teacher interns themselves could have their own practice shapedby tools to prepare them for the work of ambitious instruction. Our initial working theory ofsupport drew upon the sociocultural hypothesis that a tool operates between an individualand the accomplishment of a complex task that might otherwise be out of reach withoutsome form of assistance. The tool, conceptual or practical, serves a catalytic function as itorganizes, amplifies, repurposes, or otherwise leverages the extant resources and abilitiesof the individual to work toward a goal (Cole, 1996; Wertsch, 1991).

For the three discourses, these tools provided a template for a series of teacher–studentor student–student exchanges that would work toward the goals of the overall conversationand for that phase of MBI. The tools have multiple “pages” (four or five), each of whichcorresponds to a type of discourse exchange that would occur at a specific point duringthe lesson. The prototypical dialogue outlined on each page of a discourse tool is not ascript, but serves to activate alternatives for prompting student thinking and interacting withit. Figure 1 shows the second page from the discourse tool referred to as “Making senseof material activity.” At this point in the practice, students are in small groups trying todiscern patterns in data from lab activity and connecting these patterns to potentially causalunobservable events or processes. The chains of possible discursive exchanges are shownrunning down the middle of the page. During the actual lesson, the teacher would cyclethrough multiple iterations of the same type of exchange, whether in small-group or whole-group conversation. This would allow more chances for students to compare, contrast, buildupon, or critique science ideas, explanations, or interpretations of experiences. When theteacher feels this particular exchange has provided enough opportunities for students toreason and share, the teacher moves to the next “page” of the discourse, which builds uponintellectual resources voiced in the previous part of the conversation. Subsequent phases ofthe discourse may require a different activity structures to support it (e.g., moving from labwork to whole-class sharing out).



Each page of the discourse tools also included preplanning questions for the participantsto answer before enacting this discourse in teaching simulations held during the methodscourse or during their internship (e.g., “How will you handle the special academic languagedemands associated with this activity?”). After planning and enacting this discourse, par-ticipants respond to a parallel series of reflection questions (e.g., “What evidence do youhave that your scaffolding was at least partially successful?”).

We refer to these as “priming tools” because they required novices to unpack for them-selves a broad range of science ideas associated with the target explanation, and at thesame time imagine ideas and language from everyday experiences or previous lessons thatstudents might draw upon to make sense of the phenomena being explained. Priming isa special form of preparation for dialogically oriented classroom activity, in which theteacher uses knowledge of students’ intellectual and experiential resources together withknowledge of the target science phenomenon to anticipate ways to respond to the thinkingof others. This process, we felt, would expand the range of what novices would recognizeas student contributions that could be built upon or challenged in productive ways.

Constructing the Big Idea

The first priming tool—referred to as the Big Idea tool—is different than the othersbecause it guides planning rather than enactment. Engaging students in productive formsof science conversation requires that a substantive, engaging, and complex set of scienceideas form the basis of the talk (Ball & Bass, 2000; Bransford et al., 2000; Engle, 2011;Ma, 1999; Newmann, Marks, & Gamoran, 1995; L. Shulman, 1986). Beginning teachers,however, are not skilled at identifying such ideas. They typically use curriculum topicsand materials uncritically to choose goals for student learning (Davis, Petish, & Smithey,2008; Kang & Anderson, 2011). From our own previous longitudinal study (Thompsonet al., 2009), we found that many of our novices, even with curriculum in hand, couldnot identify big ideas to teach. By “big ideas” we mean substantive relationships betweenconcepts in the form of scientific models that help learners understand, explain, and predicta variety of important phenomena in the natural world. Such ideas were rarely self-evidentin their instructional materials. Indeed, many units or textbook chapters were not based onimportant science ideas at all. Our participants, however, felt obligated to take mundanecurricular topics (e.g., “glaciers,” “sound,” “solutions”) at face value and not seek deeperor more comprehensive scientific ideas that could help students make sense of the manyactivities prescribed in the support materials.

A few participants, however, were able to reconstitute their curriculum around big ideas.For example, during student teaching one novice was given a unit entitled “Batteriesand Bulbs.” At first, he believed that it was his duty to teach the mechanics of electricalparaphernalia and for his students to complete exercises in making different kinds of circuitsas well as comprehend the rules that governed them. Only after teaching for several daysdid he realize that the underlying big idea was the transformation of energy. At that point,his instructional goals shifted and his teaching was refocused away from an emphasis on thematerial makeup of equipment and rote recall of rules toward having students develop andtest generalizable models of energy transformations within electrical systems. Sadly, thisexample was a rare exception. Most beginners adhered to their activity-centered curricula, ormerely altered minor lesson details. In 73 classroom observations of participants, we foundonly 27 instances in which these individuals made adaptations to the central topics of thecurriculum and only eight instances in which they identified more substantive ideas to teach.

Importantly, we found that identifying the “big idea” was a critical precondition to tryingout sophisticated forms of instruction. There were in fact no instances in which a participant



failed to reconceptualize their curriculum topic as a big idea and then during the courseof the unit attempted some form of ambitious teaching. In summary, we concluded thatwithout identifying a big idea, ambitious teaching could not be initiated. We also realizedthat, within the context of secondary science education, common curriculum does notfacilitate this work for the teacher (Kesidou & Roseman, 2002).

The Big Idea tool we designed was intended to help participants develop an explicitunderstanding of the target ideas they were to teach from their curriculum. The target ideaswould be embodied then in a natural phenomenon that students could relate to. The toolitself, like the discourse tools, is an electronic document into which participants can typeresponses to a series of prompts and that can be revised as novice teachers consult with peerson their initial ideas. The tool begins with our description of “what counts” as a scientificidea worthy to build a unit around. We wanted to discourage the notion that big ideas wereself-evident in the curriculum and that they could be expressed in terms of labels such as“chemical equilibrium,” “natural selection,” or “phases of the moon.” The tool promptsparticipants to unpack such common topics by asking a series of questions: “Should detailsand facts about these “things/events” be the target of study, or are there more fundamentalprocesses associated with these that kids should understand?,” “Are these things/eventsworth studying because they are part of a larger system of activity?,” and “What aspects ofthese might be relevant to kids’ lives?”

After participants wrestle with these prompts and begin to filter out, coalesce, andrepackage substantive science ideas from their curricula, they then select a complex naturalphenomenon/event, representing these ideas, that their students can develop explanationsfor during the course of a unit (units are construed to be 2–3 weeks long). The event ornatural phenomenon must be conceptually accessible on some initial level to all studentsand related to lived experiences or to students’ interests.

A “Big Idea,” however, is more than an event—it is the relationship between somenatural phenomenon and its underlying causal explanation (i.e., the explanatory model).We used the Taoist Yin-Yang symbol to show the conjoined nature of the relationship andasked participants after using the tool to write or draw their phenomenon and explanationinto the upper and lower halves of the symbol, respectively. One example of a Big Idea fora Gas Laws unit involves a railroad tanker car that imploded after being steam cleaned. Theexplanatory model for this puzzling phenomenon combines the observable (hot steam, rapidimplosion after a few seconds, a not-quite-complete crushing, etc.) and the unobservable(molecules of different types inside and outside the tanker moving at different speeds,collisions with the walls of the structure, energy being transferred, etc.) to create thekinds of evidence-grounded storyline that authentic science values. The phenomenon beingexplained could be approached with first-hand inquiries that students engage in over anumber of days (as in the tanker example), or a puzzling situation for which studentswill primarily use second-hand data (e.g., Why is asthma so prevalent in poor urbancommunities?). In either case, students are encouraged to pose questions themselves andattempt investigations they feel can move their developing explanation forward.

D1: Eliciting Students’ Ideas to Adapt Instruction

This first discourse practice initiates units of instruction. The goal is to elicit students’understandings of the puzzling event related to an important scientific idea and then toanalyze students’ ways of engaging with that puzzle to adapt upcoming instruction (dis-crepant events which are commonly used to capture students’ interest are only one type ofsuch phenomena—consider the asthma example previously described as a more authentic



alternative that “engages” over the long term). A number of studies have shown that allow-ing students to shape these initial conversations with references to their own experiencesand ideas positively influences their intellectual engagement and their learning (Dawes,Mercer, & Wegerif, 2004; Magnusson & Palincsar, 2005; Rosebery, Ogonowski, DiChino,& Warren, 2010). The tool associated with this practice prompts novices to consider thefollowing: planning beforehand a rich task to go along with the phenomenon that can reveala range of student thinking on the Big Idea, eliciting observations from students about thephenomenon, and encouraging students to offer initial causal hypotheses about the phe-nomenon. Near the end of the tool, the novices plan how to assist students, in a whole-classsetting, to synthesize what they think they currently know and what they want/need toknow. After the teaching episode, the tool requires the novices to use what they heardfrom students to shape further instruction. Novices make these postlesson decisions basedon (1) students’ partial understandings, (2) students’ alternative understandings, (3) ev-eryday language they use to describe the phenomenon, and (4) everyday experiences theyspontaneously use to make sense of the phenomenon.

D2: Helping Students Make Sense of Material Activity

This second practice combines laboratory work and readings with students’ initial theo-ries and models to build content knowledge and to advance students’ understanding of thefocal phenomenon. For students, this entails explaining one’s ideas to others, constructingand comparing theories, and justifying claims—all of which support conceptual growth inscience (Chinn et al., 2010; NRC, 2007; Rosebery et al., 1992) and reasoning beyond thecurrent subject matter (Brown & Campione, 1994; Resnick, 2010).

First, what is presented to students through teacher-led discussions or media are featuresof the Big Idea that are not directly observable, meaning underlying events, processes, andentities that would help students understand some aspect of the observable world but are not“discoverable” through exposure to material activity such as lab work or demonstrations.

Following this incorporation of background knowledge comes an activity in whichstudents use partial knowledge of the unobservable/theoretical processes and their owntheories to make sense of observations generated from hands-on work or from second-hand data. This is not intended to be a confirmatory activity. The tool that supports thisdiscourse prompts novices to consider how sense making can be facilitated. The discourseitself presses students to understand the sense others are making of these experiencesas well as assessing their own. This intentional and metacognitive interrogation of one’sideas has been associated with deep conceptual understanding and discovery of significantpatterns in science phenomena (Mercer & Littleton, 2007; Michaels et al., 2008; Minstrell& Kraus, 2005; Rojas-Drummond & Mercer, 2003). Over a period of days, several of these“D2” sense-making conversations occur, during which the teacher revisits with studentstheir models (typically pictorial drawings on a poster paper). It is during this time that theteacher makes the student aware of the academic language associated with the science beingstudied and how it may be similar to or different from the everyday language that studentshave used to talk about the phenomenon (Mortimer & Scott, 2003). The teacher regularlytakes stock of students’ new ideas and uses this information as formative assessment todesign further lessons.

D3: Pressing Students for Evidence-Based Explanations

The goal of this third discourse is to assist students in co-constructing evidence-basedexplanatory models for the unit’s focal phenomena. As students near the end of the MBI



unit, they are asked to draw on all investigations, readings, and ideas to finalize an explana-tory model. The students’ models emerge from a chain of reasoning that links observationsand information from a variety of sources they have had experiences with (first-hand data,second-hand data, information resources, known facts, concepts, laws, etc.) to unobserv-able events, structures, or processes. We typically extend this discourse over at least twoclass periods. The D3 tool prompts novices to follow this general pattern: reorienting stu-dents to the possible explanatory models and hypotheses that could have been proposedup to this point, coordinating students’ tentative explanations with available evidence,prompting students to talk about the strength of the evidence and the reasoning that linksevidence with explanations either in groups or individually, writing a final explanation,and having students apply the new explanatory model in contexts beyond those previouslydiscussed.

Supporting students in creating such evidence-based explanations rather than merelycomprehending or reproducing textbook explanations has been associated with more co-herent understanding of ideas (Hausmann, Nokes, VanLehn, & Gershman, 2009; Smith,Maclin, Houghton, & Hennessey, 2000) and spontaneous use of these models in relatedcontexts (Brown & Kane, 1988). When teachers encourage this rich epistemic discourseabout explanatory models, students become more adept at referencing evidence and usingit to support explanatory claims. And, as with other forms of discourse in the core, thereasoning required is possible by middle school and elementary age learners (Chinn et al.,2010; Lehrer & Schauble, 2006). The core, in total, acts as a cycle of creating, testing,and revising models (see Figure 2 for a graphic representation used to express this to ourbeginning teachers).

Figure 2. MBI unit planning heuristic used with core cohorts.



UNEXPECTED INSIGHTS FROM THE CLASSROOM: REVISING OURTHEORY OF SUPPORT FOR AMBITIOUS TEACHING

As described earlier, our initial working theory was essentially that the core as a concep-tual framework and the priming tools would mediate novices’ early attempts at teachingby helping them structure planning and providing an architecture for productive discursiveinteractions with students. However, once our participants began using the practices inclassrooms, we realized our initial theory of mediation had not taken into account dynamicinteractions among participants themselves around the use of the tools and by institutionalboundary crossings of ideas about practice (between the university and internship sites aswell as across internship sites). Our vision had been unintentionally “top down” where wewould produce all the resources and then novices would implement them in classrooms. Wehad, in particular, neglected the sociocultural perspective that the tools could not only enablecomplex forms of intellectual work by individuals (the novices) but that communities wouldreciprocally reshape those tools to better serve valued goals (Cole & Engestrom, 1993). Theuse of the priming tools in fact created the conditions for entirely new types of tools to bedeveloped—not by us but by our beginning teachers whose local knowledge of classroomsand capacity to innovate we had underestimated. Our revised theory now takes into accountinsights that emerged in the context of use by a community rather than by individuals.

Before we share the events that precipitated our shifts in theory, we summarize what thecore practices afforded us within the context of university coursework. The core allowedus as researchers to create priming tools that supported HLPs, to find or create teachingexemplars in the forms of video and case studies that represented these practices, to modelthese practices for each other during university coursework, and to critique participants’initial attempts at these practices based on a common conceptual framework about whatwas trying to be accomplished and by what means. Having a set of defined practices alsoallowed us to create a “performance progression” for novices. This instrument consists offour descriptive scales that characterize each of the four core practices, ranging from leastto most sophisticated performances (see the Appendix).2 The performance progressionfunctioned as more than an evaluative tool. We used it during debriefings after teachingsimulations to have participants identify where they believed their practice was on thecontinuum for each dimension and to project what the “next level” might look like for thembased on the more advanced forms of practice described on the continuum.

2 In labeling some versions of these practices more sophisticated than others we draw upon several crite-ria. First from a comparative perspective, the upper levels of each dimension (right side of the progression)are consistent with advanced practice as defined in expert–novice studies (see, e.g., Berliner, 1994; Hogan& Rabinowitz, 2009). From a rigor perspective, the lower anchors for each dimension require only that theteacher address surface-level features of: a topic (for the Big Idea dimension), of students’ understandingsof a scientific idea (for D1), of a science activity (for D2),and of student explanations (for D3). The upperanchors, on the other hand, characterize teacher practices that press students to reason about the links be-tween observable and unobservable features of phenomena (Big Idea, D3), to engage in epistemic dialogueabout evidence (D3), and the revising of models (D2). From a responsiveness perspective, moving fromthe lower to the upper anchors of all three discourses requires increasing sensitivity to the current state ofstudent thinking, including preexisting ideas, ways of using language, and students’ evolving explanatorymodels. From a developmental perspective, we have studied the evolution of these four practices in morethan 40 beginning teachers (see Windschitl & Thompson, 2010) and have documented that most beginroughly on the left side of the spectrum. With feedback many of the novices can use these first attemptsas stepping-stones to eventually approximate the practices on the right side of the continua. When thesenovices used the more advanced practices the student discourse in the classroom was richer intellectuallyand more students would participate in science activity and talk. We do not suggest that the practices belowthe upper anchors are inherently counterproductive, in some cases they are necessary precursors for bothteachers and students to later attempt more ambitious work (see, e.g., the lower anchor of D2).



We turn now to the events that fundamentally altered our vision of how a tool-supportedcore might work. The primary revision to our theory of design and implementation wasthat the core did not directly mediate novices’ practice. Rather, practice appeared to beinfluenced by the collectively developed pool of instructional resources that were createdby participants themselves in the process of designing lessons based on the core and furtherrefined by other participants with the help of researchers and cooperating teachers. Thestage for this was set when novices returned to the university (still enrolled in methodsclasses) to report on what practices seemed successful or problematic in their classrooms,under what circumstances, and with what resources.

The most prominent example of a participant-developed resource cluster that directlyshaped how units were taught was face-to-face tools. Face-to-face tools initially emergedbecause the core emphasized the development and revision of scientific models and internsfound it necessary in their classrooms to develop tangible public records of student think-ing. The first form of public record used by interns was a whole-class consensus modelin which the novice, with students’ input, drew an initial pictorial representation of thepuzzling phenomenon that included both observable and unobservable components. Thisdrawing was then revised by students over time. When interns returned to the universityand shared with one another how these representations were functioning for students, theycollaboratively refined how they could be used. It soon became shared knowledge thata three-panel drawing of the puzzling phenomenon, showing “before–during–after,” wasmore useful than a single-instance drawing. One novice in a middle school physical scienceclassroom had students draw the forces acting on a skateboarder, first as she was standingstill at the top of a hill, then as she was gaining speed going downhill, them jumping offbefore hitting an obstacle at the bottom of the hill. These multistage drawings routinelyrevealed more about students’ initial explanatory theories than a single frame drawing,allowed multiple entry points for students to begin contributing to such a drawing, and,near the end of a unit, required that students draw and describe the entire causal explanationin far richer detail.

This tool type developed into an entire genre of inscription that allowed students, withthe support of the interns, to represent on poster paper explanatory facets of the BigIdea and how these changed over time in response to investigative experiences, readings,and arguments by fellow students. The public representation subcategory of face-to-facetools grew to include other ways to display student thinking such as small-group modeldrawings, student-generated checklists for ideas that needed to be included as part of finalexplanations, and lists of hypotheses about phenomenon that students would add to, revise,or subtract from as the unit progressed. Interns constantly tried new versions of theserepresentations and also experimented with accompanying activity structures to supportstudent thinking over the course of a unit.

Public representations were not the only form of participant-generated face-to-face tool.Others included sentence starters to help students participate in unfamiliar academic talkabout evidence and explanation, and “thought-trackers,” which were documents for studentswith metacognitive prompts to help them record how their thinking had changed over timeabout the Big Idea, about what evidence or argument made them change their thinking,and about what gaps or puzzles they still had. Another widely used tool that directlyinfluenced practice was called “back-pocket questions.” This was simply an index card onwhich the intern would write a series of increasingly complex questions about the day’sactivity. Interns would carry this card from table to table as students engaged in small groupwork. The intern would ask an initial question that would allow them to diagnose students’current ideas, then they would reference the card for an appropriate question that mightpush students’ thinking farther.



In sum, these face-to-face tools mediated classroom talk more directly than the core,perhaps even more than the discourse tools themselves. In contrast to the priming tools(Big Idea and discourse tools), which were developed by the researchers, face-to-facetools were codesigned by the interns, the researchers, and occasionally the cooperatingteachers and were used during class with students to directly support scientific reasoningand discourse.

Example of Tool Innovations Directly Mediating Novice Practice andStudents’ Intellectual Work

We found that the participants who had enacted the most sophisticated forms of teachingcoordinated the use of several forms of face-to-face tools during the course of a singleunit, sometimes within the same class period. We share here the story of one participant,Camille, to illustrate her use of multiple face-to-face tools that were adaptations of othersused by the cohort and that were directly tied to the core practices. Camille was assignedto teach physics in a large urban high school. In November of her internship, she wasasked to construct and teach a unit on force and motion, which was to include ideas aboutfriction and inertia with moving objects. The “Big Idea” she chose revolved around streetgymnastics, an activity many of her students had seen as part of the urban landscape.Camille wanted to use a phenomenon that her student were familiar with and could begenuinely puzzled by, but also one that was demanding in terms of its fully elaboratedunderlying explanation. She chose a video of a young man running up to a building,launching himself upward with one foot on the wall, then flipping backward to land on hisfeet.

On the first day of the unit, Camille showed the video clip. Her students spontaneouslybegan theorizing about possible explanations, all of which were recorded on the board (“Hehas to build up speed,” “Its got something to do with his center of gravity,” “He’s got nofear!”). To further develop initial ideas about how physics could explain this phenomenon(Discourse 1), Camille had groups of students draw a representation of the man’s flip,including “what might be going on that is not directly observable.” As the unit progressed,these drawings (Figure 3a) became the object of on-going talk and revision as studentsconducted investigations and read about scientific ideas around force. These revisions weresupported by the use of a second tool, one that Camille had created as a hybrid from acolleague’s use of Post-it notes as ways for students to place comments on their peers’models, and from the idea of sentence starters to link everyday modes of critique withscience-specific ways of commenting on ideas. Figure 3b shows a tool that displayed fourways students could change an explanatory model, based on logic and/or evidence—to addto it, revise it, remove an element, or pose a new question about the model. In Figure 3a,a number of color-coded Post-its can be seen affixed to the poster (by the owners of theposter) after two activities and readings. These generally reflect insights or questions abouttheir current models based on new ideas. The Post-it in the upper left, for example, is a“revision” and says “We would like to change our idea of needing enough force and gravityto get in the air, to the idea of friction. The person doing the wall flip needs to overcomeinitial static friction to get started.” One of the other Post-its that signals a revision says,“We think that Station 2 [a lab activity students recently completed] supports our modelbut it also tells us that in order to push himself off the wall he has to push the wall itself.” Apurple Post-it poses a question: “We still have questions about what the flipper has to do inthe air.” This scaffolding strategy has since been taken up members of subsequent teacher



Figure 3. (a) Students’ initial model with self-comments affixed. (b) Scaffolding tool for engaging in academictalk about revising models. (c) Students’ summary table to make sense of and coordinate D2 activities. (d) Drawnportion of trial explanation with peers’ critique added.

education cohorts, who have tailored the sentence frames and the routines of how they areused to fit the needs of their classrooms.

After each investigation during the unit, Camille had students write entries into a whole-class table, including what they had learned from the activity and how they thought it wouldhelp them explain the backflip. This tool, referred to as a summary table, was an extensionof Discourse 2 (making sense of material activity), and its structure was tailored by eachintern to meet their students’ needs. Students filled the table in, using their own languageand ideas drawn from the investigations, readings, and classroom talk (Figure 3c shows



a segment of the summary table). The categories on this particular summary table were“activities,” “observations,” “why,” and “how do these help us explain a wall flip?” Thesereflect the emphases of Discourse 2, which is to help the learner make sense of an activity,but also to help learners see how the activity relates back to the focal phenomenon of theBig Idea.

Two weeks later, as part of Discourse 3, Camille had her students do “practice expla-nations,” which were then commented upon by peers using scaffolds supplied by Camille.Examples of these comments from peers are shown in Figure 3d. Here Camille had brokenthe phenomenon down into six phases, not only to encourage a richer explanation by stu-dents, but to prompt them to use evidence to support multiple parts of the explanation (notshown in the figure is an accompanying written explanation that is a full single-spaced pageof text). In this case, they required students to note in each cell what investigations they haddone that supported that part of their explanation (in cell 4, e.g., the student writes “evidencefrom sock–shoe race and block activity”). In addition to completing the practice explana-tion, students now commented on the explanations of their peers. One student, for example,notes in cell 4 that their peer had neglected to include something important—“need frictionto temporarily keep foot on wall.”

Camille’s case exemplifies how face-to-face tools were directly supportive of ambitiousteaching and grew out of the original core and its priming tools. Each of these tools had tobe adapted to particular class circumstances—they could not be used “off the shelf.” Weargued earlier that such direct influences on practice were part of a cascade of effects thatwere enabled initially by the organization of preparation experiences around the core. Abroader body of evidence for this claim comes from two observations. First, for previouscohorts of preservice teachers we had worked with, where instructional strategies similarto those in the core were taught as broad approaches rather than defined interactionalpractices and where discourse tools were not available, there was no such development orpropagation of face-to-face tools. Second, for participants like Camille who had access tothe core, every tool they developed or adapted was designed to support directly the workof one or more core practices.

Importantly, it appears that images of ambitious teaching were similar enough acrossparticipants’ classrooms for them to help one another with problems of practice. Interns, forexample, could study artifacts produced in the classrooms of their peers, hear the accountsof others’ attempts at certain practices, and then recognize what forms of assistance might bevaluable for students in these classrooms as well as their own. These facets of shared visionenabled new tools to be collaboratively developed and refined, which in turn, supportednew forms of classroom interaction and learning by students and interns themselves (seeWindschitl & Thompson, 2010, for a full account of how the cohorts described in this essayoutperformed a comparison group of preservice teachers during their internships using theperformance progression as one metric of instructional quality). We now believe that allthree types of tools—the core as a conceptual frame, the priming tools, and the face-to-facetools—all play unique, interrelated, and necessary roles in the development of practices bycommunities of novices (Table 1).

MAKING AMBITIOUS TEACHING THE NEW NORMAL

Part of any plan to rethink how we prepare teachers would have to include some consen-sus about what counts as practices that optimize K-12 student learning and participationand that are attainable by novices. We have clear indications that forms of ambitious



TABLE 1Typology of Tools used to Support Ambitious Teaching

Core as Priming Face-to-FaceConceptual Tool Tools Tools

Examples • Model-basedinquiry asframe for fourcore practices

• Big idea tool• Discourse tools

• Public representations ofstudents’ ideas,scaffolds for talk aboutrevising models basedon evidence,back-pocket questions,meta-cognitive aids(thought-trackers), etc.

Purpose • To organizeoverallpurposes,goals, directionfor a unit ofinstruction

• Becomesreferent forsharedlanguage aboutpractices withina community

• prepares teacherfor situated andpurposefulinteractions withlearners aroundfundamentallyimportant scienceideas

• Becomes basis forshared languagein communityabout features ofpractice such asdiscourse moves,scaffolding, use ofmodels, etc.

• Directly mediatesinteractions amongteacher, students, andscience ideas

• Scaffolds students toparticipate more fully incomplex reasoning,science talk, andpractice with oneanother

• Allows teachercandidates to learn fromeach other’s pedagogical“problem-solving”artifacts

Who designsand basis ofdesign

• Designed byresearchersusing primarilyreformdocuments,syntheses ofscience studies

• Designed byresearchers usingstudies of expertteaching, focusingon rigor and equityas attributes ofcompetentinstruction

• Designed by novices incollaboration withmentor teachers andresearchers, based onlocal knowledge ofclassrooms, students,curriculumcontingencies, aims ofcore practices

Basis formodification

• Modificationbased oncritique fromfield of scienceeducationresearch

• Process ofrevision andauthority formakingchanges as yetundefined

• Modificationprimarily byresearchers basedon observation ofhow novices usethem in the fieldand of responsesby their students

• Changed frequently bymeans of exchange ofideas among novices

• Legitimately usefulversions multiply withinand acrossclassrooms—efficacyassessed againstmeasures of studentparticipation, learning



teaching are indeed within the grasp of beginners if they are provided with the research-informed conceptual and practical tools. We have further argued here that if sets of HLPsfor different subjects matter areas could be articulated and taught across early learning-to-teach contexts, the broader teacher education community could collectively refine thesepractices as well as tools and other resources that support their development. The dis-tributed expertise in this system would include the beginning teachers themselves who,we have learned, can create and adapt tools to directly mediate student participation andlearning.

On a larger scale, coordinating such tools, teaching practices, inquiries into instruction,and institutional commitments could form the basis for a science of performance improve-ment and are already being woven into the fabric of some teacher education programs.Lampert and Graziani (2009) note how similarly purposed resources, developed at an Ital-ian language learning school, shaped not only individual practice, but the organization’sability to interrogate and adapt instruction as well:

We learned that the materials of the school are often the means by which social andintellectual assets are built as they are concrete representations of ambitious teachingand learning. As such, they coordinate instructional activity around a common set ofinterpretations of students’ performance and also a common set of beliefs about howteachers should respond in ways that improve student performance over time . . . . Whenthese assets are used as resources at Italiaidea they have the power to enhance other assets,which in turn positions the school as an organization to support ambitious instruction.(p. 499)

While the subtext of our argument has included the claim that some practices are morevaluable to learn than others, we acknowledge that there are no ideal forms of practice, butrather there are instructional enactments that assist novices in achieving important teachingand learning goals with greater success and consistency than others. For readers whoimagine the core and tools discussed here as an effort to hypernormalize early practice,we can assure them that our participants’ teaching attempts, both at the university andin the field, were varied, imaginative, and often adapted to the needs of their students.The notion of caring about students as human beings was also infused into our worktogether—students are more than clients or objects of instruction. Indeed our work inclassrooms has brought us to the realization that the most rigorous and equitable formsof instruction are unattainable if the teacher does not have a caring relationship withstudents.

We have shared the foundations of a working theory for how a set of HLPs might bedeveloped and supported by specialized tools. Our initial focus was on the construction ofa candidate core, but we soon understood that the practices could only “come into being”through the tools and that without such forms of support, our teachers’ efforts at rigorous andequitable forms of instruction would likely have been limited. More importantly, however,we witnessed how the newest members of a community who shared among themselves atleast a nominal vision of quality teaching could collectively invent entirely new systemsof teaching tools that, in turn, productively reshaped the work they were doing with younglearners. We are convinced that establishing a core does not mean that beginning teachersor teacher educators will have their practice “standardized”—rather, a core that belongsto a community can serve as a basis for principled experimentation by a collective ofprofessionals who are informed by shared and explicit goals for instruction and committedto the advancement of learning for all students.



REFERENCES

Adams, P. E., & Krockover, G. H. (1997). Beginning science teacher cognition and its origins in the preservicesecondary science teacher program. Journal of Research in Science Teaching, 34, 633 – 653.

Alexander, R. J., Osborn, M., & Phillips, D. (2000). Learning from comparing: New directions in compara-tive educational research, Volume II: Policy, professionals and development. Oxford, England: SymposiumBooks.

American Association of Colleges for Teacher Education. (2010). The clinical preparation of teachers: A policybrief. Washington, DC: Author.

Ball, D., & Bass, H. (2000). Making believe: The collective construction of public mathematical knowledge inthe elementary classroom. In D. Phillips (Ed.), Yearbook of the national society for the study of education,constructivism in education (pp. 193 – 224). Chicago: University of Chicago Press.

Ball, D., & Forzani, F. (2009). The work of teaching and the challenge for teacher education. Journal of TeacherEducation, 60(5), 497 – 511.

Ball, D. L., Sleep, L., Boerst, T., & Bass, H. (2009). Combining the development of practice and the practice ofdevelopment in teacher education. Elementary School Journal, 109(5), 458 – 474.

Banilower, E., Smith, P. S., Weiss, I. R., & Pasley, J. D. (2006). The status of K-12 science teaching in the UnitedStates: Results from a national observation survey. In D. Sunal & E. Wright (Eds.), The impact of the state andnational standards on K-12 science teaching (pp. 83 – 122). Greenwich, CT: Information Age.

Berliner, D. C. (1994). Expertise: The wonder of exemplary performances. In J. Mangieri & C.C. Block (Eds.),Creating powerful thinking in teachers and students: Diverse perspectives (pp. 161 – 186). Fort Worth, TX:Harcourt Brace College.

Boerst, T., & Sleep. L. (2007, April). Uses and meanings of practice in learning to do the work of mathematicsteaching. Paper presented at the annual meeting of the American Educational Research Association, Chicago,IL.

Bransford, J., Brown, A., & Cocking, R. (2000). How people learn: Brain, mind, experience, and school. Committeeon developments in the science of learning. Commission on Behavioral and Social Sciences and Education ofthe National Research Council. Washington, DC: National Academy Press.

Brown, A., & Campione, J. (1994). Guided discovery in a community of learners. In K. McGilly (Ed.), Classroomlessons: Integrating cognitive theory and classroom practice. Cambridge, MA: The MIT Press.

Brown, A. L., & Kane. M. J. (1988). Preschool children can learn to transfer: Learning to learn and learning fromexamples. Cognitive Psychology, 20, 493 – 523.

Bryk, T. (2009). Supporting a science of performance improvement. Phi Delta Kappan, 90(8), 507 – 600.Cazden, C. B. (1988). Classroom discourse: The language of teaching and learning. Portsmouth, England:

Heinemann Educational Books.Chapin, S., & O’Connor, M. C. (2004). Project challenge: Identifying and developing talent in mathematics within

low-income urban schools. Boston University School of Education Research Report No. 1, pp. 1 – 6.Chinn, C., Golan Duncan, R., Pluta, W., Buckland, L., Kempler Rogat, T., DiFranco, J., & Witham, S. (2010).

Promoting reasoning: A microgenetic study of middle-school students learning through model-based inquiry.Paper presented at the annual conference of the American Educational Research Association, Denver, CO.

City, E., Elmore, R., Fiarman, S., & Teitel, L. (2009). Instructional rounds in education: A network approach toimproving teaching and learning. Cambridge, MA: Harvard Educational Press.

Clotfelter, C. T., Ladd, H. F., & Vigdor, J. L. (2007). Teacher credentials and student achievement in high school:A cross-subject analysis with student fixed effects. Economics of Education Review, 26(6), 673 – 782.

Cobb, P., Boufi, A., McClain, K., & Whitenack, J. (1997). Reflective discourse and collective reflection. Journalof Research in Mathematics Education, 28(3), 258 – 277.

Cobb, P., Zhao, Q., & Dean, C. (2009). Conducting design experiments to support teachers’ learning: A reflectionfrom the field, Journal of the Learning Sciences, 18(2), 165 – 199.

Cohen, D. (2007). Problems in educational policy and research. In S. H. Fuhrman, D. K. Cohen, & F. Mosher(Eds.), The state of education policy and research (pp. 349 – 371). Mahwah, NJ: Erlbaum.

Cohen, D. (2011). Teaching: Practice and its predicaments. Cambridge, MA: Harvard University Press.Cohen, D., Raudenbush, S., & Ball, D. (2002). Resources, instruction, and research. In F. Mosteller & R. Boruch

(Eds.), Evidence matters: Randomized trials in education research (pp. 80 – 119). Washington, DC: BrookingsInstitution Press.

Cohen, D. K. (1989). Teaching practice: Plus ca change . . . . In P. W. Jackson (Ed.), Contributing to educationalchange: Perspectives on research and practice (pp. 27 – 84). Berkeley, CA: McCutchan.

Cole, M. (1996). Cultural psychology: A once and future discipline. Cambridge, MA: Harvard University Press.Cole, M, & Engestrom, Y. (1993). A cultural historical approach to distributed cognition. In G. Saloman (Ed.), Dis-

tributed cognitions: Psychological and educational considerations (pp. 1 – 46). Cambridge, England: CambridgeUniversity Press.



Davis, E. A., Petish, D., & Smithey, J. (2006). Challenges new science teachers face. Review of EducationalResearch, 76(4), 607 – 651.

Dawes, L., Mercer, N., & Wegerif, R. (2004). Thinking together: A programme of activities for developingspeaking, listening and thinking skills (2nd ed.). Birmingham, England: Imaginative Minds.

Deussen, T., Coskie, T., Robinson, L., & Autio, E. (2007). “Coach” can mean many things: Five categories ofliteracy coaches in reading first (issues & answers report, REL 2007-No. 005). Retrieved July 19, 2008, fromhttp://ies.ed.gov/ncee/edlabs.

Duschl, R., & Duncan, R. (2009). Beyond the fringe: Building and evaluating scientific knowledge systems. In S.Tobias & T. Duffy (Eds.), Constructivist instruction: Success or failure? New York: Routledge.

Engle, R. (2011). The productive disciplinary engagement framework: Origins, key concepts, and developments.In D. Dai (Ed.), Design research on learning and thinking in educational settings. New York: Taylor & Francis,Educational Psychology Press.

Fennema, E., Franke, M. L., Carpenter, T. P., & Carey, D. A. (1993). Using children’s mathematical knowledgein instruction. American Educational Research Journal, 30(3), 555 – 583.

Franke, M. L., & Chan, A. (2007, April). Learning about and from focusing on routines of practice. Paper presentedat the annual meeting of the American Educational Research Association, Chicago, IL.

Freese, A. R. (2006). Reframing one’s teaching: Discovering our teacher selves through reflection and inquiry.Teaching and Teacher Education, 22, 100 – 119.

Gess-Newsome, J. & Lederman, N.G. (1993). Pre-service biology teachers’ knowledge structures as a functionof professional teacher education: A year-long assessment. Science Education, 77, 25 – 45.

Green, E. (2010). Building a better teacher. New York Times Magazine, March 2, 2010.Grossman, P., Compton, C., Igra, D., Ronfelt, M., Shahan, E., & Williamson, P. (2009). Teaching practice: A

cross-professional perspective. Teachers College Record, 111(9), 2055 – 2100.Grossman, P., & McDonald, M. (2008). Back to the future: Directions for research in teaching and teacher

education. American Educational Research Journal, 45(1), 184 – 205.Hammerness, K., Darling-Hammond, L., & Bransford, J. (2005). How teachers learn and develop. In L. Darling-

Hammond & J. Bransford (Eds.), Preparing teachers for a changing world (pp. 358 – 389). San Francisco:Jossey-Bass.

Hatch, T., & Grossman, P. (2009). Learning to look beyond the boundaries of representation: Using technologyto examine teaching (overview for a digital exhibition: Learning from the practice of teaching). Journal ofTeacher Education, 60(1), 70 – 85.

Hausmann, R. G. M., Nokes, T. J., VanLehn, K., & Gershman, S. (2009). The design of self-explanation prompts:The fit hypothesis. Proceedings of the thirty-first annual conference of the Cognitive Science Society (pp.2626 – 2631). Amsterdam, the Netherlands: Cognitive Science Society.

Herrenkohl, L. R., & Guerra, M. R. (1998). Participant structures, scientific discourse, and student engagementin fourth grade. Cognition and Instruction, 16, 433 – 475.

Hiebert, J., Gallimore, R., & Stigler, J. W. (2002). A knowledge base for the teaching profession: What would itlook like and how can we get one? Educational Researcher, 31(5), 3 – 15.

Hill, H. C., Rowan, B., & Ball, D. L. (2005). Effects of teachers’ mathematical knowledge for teaching on studentachievement. American Educational Research Journal, 42, 371 – 406.

Hogan, T., & Rabinowitz, M. (2009). Teacher expertise and the development of problem representation. Educa-tional Psychology, 29(2), 153 – 169.

Hogan, T., Rabinowitz, M., & Craven, J. (2003). Representation in teaching: Inferences from research of expertand novice teachers. Educational Psychologist, 38(4), 235 – 247.

Horizon Research International. (2003). Special tabulations of the 2000 – 2001 LSC teacher questionnaire andclassroom observation data. Chapel Hill, NC: Horizon Research.

Ingersoll, R. M. (1996). Out-of-field teaching an educational equality. Washington, DC: U.S. Department ofEducation, Office of Educational Research and Improvement.

Jackson, P. (1986). The practice of teaching. New York: Teachers College Press.Kang, H., & Anderson, C. (2011). Beginning teachers’ development of classroom practice and their narratives

of practices toward reform-oriented instruction. Paper presented at the annual conference of the NationalAssociation of Research in Science Teaching, Orlando, FL.

Kesidou, S., & Roseman, J. (2002). How well do middle school science programs measure up? Findings fromProject 2061’s Curriculum Review. Journal of Research in Science Teaching, 39(6), 522 – 549.

Lampert, M. (2001). Teaching problems and the problems of teaching. New Haven, CT: Yale University Press.Lampert, M. (2010). Learning teaching in, from, and for practice: What do we mean? Journal of Teacher Education,

61(1 – 2), 21 – 34.Lampert, M., & Graziani, F. (2009). Instructional activities as a tool for teachers’ and teacher educators’ learning.

Elementary School Journal, 109(5), 491 – 509.



Lee, C. (2007). The role of culture in academic literacies: Conducting our blooming in the midst of the whirlwind.New York: Teachers College Press.

Lee, C. D. (2001). Is October Brown Chinese? A cultural modeling activity system for underachieving students.American Educational Research Journal, 38(1), 97 – 141.

Lehrer, R., & Schauble, L. (2006). Supporting the development of the epistemology of inquiry. Cognitive Devel-opment, 23(4), 512 – 529.

Leinhardt, G., & Steele, M. (2005). Seeing the complexity to standing to the side: Instructional dialogues.Cognition and Instruction, 23(1), 87 – 163.

Lemov, D. (2010). Teach like a champion: 49 techniques that put students on the path to college. San Francisco:Jossey-Bass.

Lesh, R., Hoover, M., Hole, B., Kelly, A., & Post, T. (2000). Principles for developing thought revealing activitiesfor students and teachers. In A. Kelly & R. Lesh (Eds.), The handbook of research design in mathematics andscience education (pp. 591 – 646). Mahwah, NJ: Erlbaum.

Levine, A. (2006). Educating school teachers. Washington DC: Education Schools Project. Retrieved July 10,2009, from http://www.edschools.org/teacher report release.htm.

Little, J. W. (1990). The persistence of privacy: Autonomy and initiative in teachers’ professional relations.Teachers College Record, 91(4), 509 – 536.

Ma, L. (1999). Knowing and teaching elementary mathematics: Teachers’ understanding of fundamental mathe-matics in China and the United States. Mahwah, NJ: Erlbaum.

Magnusson, S., & Palincsar, A. (2005). Teaching to promote the development of scientific knowledge andreasoning about light at the elementary school level. In M. S. Donovan & J. Bransford (Eds.), How studentslearn science in the classroom (pp. 421 – 474). Washington, DC: National Academies Press.

Mercer, N., & Middleton, K. (2007). Dialogue and the development of children’s thinking: A socioculturalapproach. London: Routledge.

Metcalf, S. J., Krajcik, J., & Soloway, E. (2000). Model-it: A design retrospective. In M. Jacobson & R. B. Kozma(Eds.), Innovations in science and mathematics education: Advanced designs for technologies in learning (pp.77 – 116). Mahwah, NJ: Erlbaum.

Michaels, S., O’Connor, C., & Resnick, L. (2008). Reasoned participation: Accountable talk in theclassroom and in civic life. Studies in Philosophy and Education, 27(4), 283 – 297. Read moreat http://www.clarku.edu/academiccatalog/facultybio.cfm?id=15#ixzz0KPZQlrC9&C. Accessed October 7,2011.

Minstrell, M., & Kraus, P. (2005). Guided inquiry in science classrooms. In M. S. Donovan & J. Bransford (Eds.),How students learn science in the classroom (pp. 475 – 514). Washington, DC: National Academies Press.

Mortimer, E., & Scott, P. (2003). Meaning making in secondary science classrooms. Philadelphia: Open UniversityPress.

Murray, F. (1989). Explanation in education. In M. Reynolds (Ed.), Knowledge base for the beginning teacher(pp. 1 – 12). New York: Pergamon.

National Research Council. (1996). National Science Education Standards. Washington, DC: National AcademyPress.

National Research Council. (2000). Inquiry and the National Science Education Standards. Washington, DC:National Academy Press.

National Research Council. (2005). America’s lab report: Investigations in high school science. Committee onhigh school laboratories: Role and vision. S. R. Singer, A. L. Hilton, & H. A. Schweingruber (Eds.), Boardon Science Education. Center for Education, Division of Behavioral and Social Sciences and Education.Washington, DC: National Academies Press.

National Research Council. (2007). Taking science to school: Learning and teaching science in grades K-8.Committee on Science Learning, Kindergarten Through Eighth Grade. R. A. Duschl, H. A. Schweingruber, &A. W. Shouse (Eds.). Board on Science Education, Center for Education, Division of Behavioral and SocialSciences and Education. Washington, DC: The National Academies Press.

National Research Council. (2011). Framework for the next generation science education standards. RetrievedSeptember 22, 2011, from http://www7.nationalacademies.org/bose/Standards Framework Homepage.html.

Nersessian, N. (2002). The cognitive basis of model-based reasoning in science. In P. Carruthers, S. Stich, & M.Siegal (Eds.), The cognitive basis of science (pp. 17 – 34). Cambridge, England: Cambridge University Press.

Newmann, F., & Associates. (1996). Authentic achievement: Restructuring schools for intellectual quality. SanFrancisco: Jossey-Bass.

Newmann, F. M., Marks, H. M., & Gamoran, A. (1995). Authentic pedagogy: Standards that boost studentperformance. Issues in restructuring schools (issue report no. 8). Madison, WI: Center on Reorganization andRestructuring of Schools. Retrieved March 12, 2009, from http://www.wcer.wisc.edu/archive/cors/Issues inRestructuring Schools/ISSUES NO 8 SPRING 1995.pdf



Rand (2002). Reading for understanding: Toward an R&D program in reading comprehension. Santa Monica,CA: Author.

Raudenbush, S. (2008). Advancing educational policy by advancing research on instruction. American EducationalResearch Journal, 45, 206 – 230.

Resnick, L. (2010). Nested systems for the thinking curriculum. Educational Researcher, 39(3), 183 – 197.Rivkin, S. G., Hanushek, E. A., & Kain, J. F. (2005). Teachers, schools, and academic achievement. Econometrica,

73(2), 417 – 458.Rockoff, J. E. (2004). The impact of individual teachers on student achievement: Evidence from panel data.

American Economic Review, 94(2), 247 – 252.Rojas-Drummond, S., & Mercer, N. (2003). Scaffolding the development of effective collaboration and learning.

International Journal of Educational Research, 39(1 – 2), 99 – 111.Rosebery, A., Ogonowski, M., DiSchino, M., & Warren, B. (2010). “The coat traps all your body heat”: Hetero-

geneity as fundamental to learning. Journal of the Learning Sciences, 19, 322 – 357.Rosebery, A. S., Warren, B., & Conant, F. R. (1992). Appropriating scientific discourse: Findings from language

minority classrooms. Journal of the Learning Sciences, 2(1), 61 – 94.Roth, K., & Garnier, H. (2007). What science teaching looks like: An international perspective. Educational

Leadership, 64(4), 16 – 23.Sfard, A., & McClain, K. (2002). Analyzing tools: Perspectives on the role of designed artifacts in mathematics

learning. Journal of the Learning Sciences, 11(2 – 3), 153 – 161.Shulman, L. (1986). Those who understand: Knowledge growth in teaching. Educational Researcher, 15(2), 4 – 14.Shulman, L. S. (1992). “Research on teaching: A historical & personal perspective.” In F. Oser, A. Dick, & J.

Patry (Eds.), Effective and responsible teaching: The new synthesis (pp. 14 – 29). San Francisco: Jossey-Bass.Smith, C., Maclin, D., Houghton, C., & Hennessey, M. (2000). Sixth grade students’ epistemologies of science:

The impact of school science experiences on epistemological development. Cognition and Instruction, 18(3),349 – 422.

Smith, J., Lee, V., & Newmann, F. (2001). Instruction and achievement in Chicago elementary schools. Chicago:Consortium on Chicago School Research, Chicago Annenberg Research Project.

Stewart, J., Passmore, C., Cartier, J., Rudolph, J., & Donovan, S. (2005). Modeling for understanding in scienceeducation. In T. Romberg, T. Carpenter, & F. Dremock (Eds.), Understanding mathematics and science matters(pp. 159 – 184). Mahwah, NJ; Erlbaum.

Sykes, G., Bird, T. & Kennedy, M. (2010). Teacher education: Its problems and some prospects. Journal of TeacherEducation, 61(5), 464 – 476.

Thompson, J., Windschitl, M., & Braaten, M. (April 2009). How pedagogical reasoning and ambitious prac-tice develops across “learning to teach” contexts. Paper presented at the annual conference of the NationalAssociation of Research in Science Teaching, Anaheim, CA.

U.S. Department of Education (2008). The final report of the National Mathematics Advisory Panel. Washington,DC: Author.

Warren, B., & Rosebery, A. S. (1996). “This question is just too easy!” Students’ perspectives on accountabilityin science. In L. Schauble & R. Glaser (Eds.), Innovations in learning: New environments for education (pp.97 – 125). Mahwah, NJ: Erlbaum.

Weiss, I. R., Banilower, E. R., McMahon, K. C., & Smith, P. S. (2001). Report of the 2000 National Survey ofscience and mathematics education. Chapel Hill, NC: Horizon Research, Inc. Retrieved February 2, 2012, fromwww.horizon-research.com.

Wertsch, J. (1991). Voices of the mind: A sociocultural approach to mediated action. Cambridge, MA: HarvardUniversity Press.

White, B., & Fredericksen, J. (1998). Inquiry, modeling, and metacognition: Making science accessible to allstudents. Cognition and Instruction, 16(1), 3 – 118.

Wilson, C., Taylor, J., Kowalski, S., & Carlson, J. (2010). The relative effects and equity of inquiry-based andcommonplace science teaching on students’ knowledge, reasoning, and argumentation. Journal of Research inScience Teaching, 47(3), 276 – 301.

Windschitl, M., & Thompson, J. (2010, December). Raising performance expectations for novice teachers: Thepromise of pedagogical tools and core practices. Paper presened at the DR-K-12 National Science FoundationConference, Washington, DC.

Windschitl, M., Thompson, J. & Braaten, M. (2008). Beyond the scientific method: Model-based inquiry as a newparadigm of preference for school science investigations. Science Education, 92(5), 941 – 967.


proposing a core set of instructional practices and tools for teachers of science

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