Talking Our Way Around Expert Caution: A Rhetorical Analysis of VAM

Abstract

This study turns a rhetorical lens on the debate about how best to use value-added modeling (VAM) in teacher evaluation by addressing the question, Which arguments legitimize the dismissal of expert caution about proposed education reforms? My rhetorical analysis of a corpus of nonacademic texts (e.g., newspapers, magazines, political speeches) reveals three persuasive strategies that function to get around technical concerns about VAM. By pointing out these strategies and explaining how they work, the study disrupts their persuasive potential and suggests a potentially overlooked role of expertise in public decision making.

Keywords

case studies communication discourse analysis educational policy high-stakes testing media research utilization rhetoric school/teacher effectiveness teacher evaluation textual analysis value-added modeling

“As a general rule, you should be worried when the people who are producing something are the ones who are most worried about using it.” —Douglas N. Harris (Otterman, 2010)

A lot has been said about the use of value-added modeling (VAM) in teacher evaluation. We have studied the technical properties of models, their strengths and limitations as measures of teacher quality, how they are perceived by teachers and administrators, and so forth. This article takes a novel approach, looking through a rhetorical lens at the debate about the role of VAM in teacher evaluation. During the past several years, technical concerns¹ from the research community seem not to have hindered some policymakers from embracing robust programs of VAM-based teacher evaluation² (National Council on Teacher Quality, 2017). My work investigates this phenomenon by asking, Which arguments might function to discount expert³ caution? In particular, I look for commonly deployed rhetorical moves, persuasive uses of language (e.g., patterns in the way arguments are motivated, structured, or supported; recurring topoi; common stylistic devices) that have the potential to shape audience perception in identifiable ways. The three moves I identify provide a way around expert caution, a logic according to which technical concerns need not constrain policies of VAM-based teacher evaluation.

This work is important for education researchers who may find themselves with technical concerns about high-stakes uses of complex tools like VAM. By revealing how these concerns can be rhetorically obfuscated, this study helps researchers think about how they might shift their own language to combat this obfuscation and thus protect students whose education may be jeopardized if faulty information is used to evaluate teachers. The study is also of direct importance to the broader public. The sidestepping of expert caution in nonexpert discourse is a worrying phenomenon not just in the case of education but in any decision-making context that involves input from the research community. My work puts the phenomenon on the radar of policymakers and other nonexperts, priming them to listen for (and perhaps seek out) expert commentary on the technical capacity of complex tools. Furthermore, if nonexperts can recognize the identified rhetorical moves at work, they may be less likely to overlook, minimize, or dismiss expert caution.

In subsequent sections, I situate the study theoretically and within existing empirical research. After describing my textual corpus and methodological approach, I present my findings and conclude with a discussion of my results and their implications.

Theoretical Orientation

Although this study deals with the role of research in policy, it is not grounded in the currently widespread enthusiasm for evidence-based education policy that former education secretary Arne Duncan expressed to researchers at the Institute of Education Sciences:

Gut feelings aren’t good enough. They don’t give us a complete and accurate picture of what that school needs to do to get better. That’s your role. We need you to tell us whether we’re on the right path. … You give us the cold hard facts. (Duncan, 2010a, para. 8)

In Duncan’s (2010a) appeal, we see some of the assumptions that frequently underlie calls for evidence-based policy: “that policies are driven by facts rather than values and these can be clearly separated; that ‘evidence’ is context-free, can be objectively weighed up and placed unproblematically in a ‘hierarchy’; and that policymaking is essentially an exercise in decision science” (Russell, Greenhalgh, Byrne, & McDonnell, 2008, p. 40).

Decades of work across several disciplines have revealed deep problems with these assumptions. The idea that scientific inquiry locates the cold hard facts does not hold up under theoretical (e.g., Bourdieu, 1975; Longino, 1990) or empirical (Latour & Woolgar, 1979; Shapin & Schaffer, 1985) scrutiny. And this is especially true in education research, where construct definition and counterfactual selection are notoriously subjective endeavors (e.g., Hammersley, 2014; Messick, 1981; Shaddish, Cook, & Campbell, 2002). Furthermore, the notion that research can tell us whether we’re on the right path is oversimple, for policy debates rarely boil down to issues the research community can resolve (Boyd, 1999; Jasanoff, 2012; Johnson 1999).

This conception of the role of research evidence is widespread in the field of education (Slavin, 2002; Wiseman, 2010), but my work is rooted in different theoretical ground. I understand policymaking as a fundamentally discursive, value-laden process that proceeds more through the construction of compelling arguments and less through the logical use of critically examined evidence (Asen, 2010; Fischer & Forester, 1993; Johnson, 1999; Majone, 1989). From this perspective, research evidence is one of many rhetorical resources an actor may marshal to define issues, set agendas, and justify policies. Inquiry grounded in this perspective focuses on “the struggle over ideas, the ‘naming and framing’ of policy problems, the centrality of audience and the rhetorical use of language in discussion to increase the audience’s adherence to particular framings and proposals” (Russell et al., 2008, p. 40).

To be clear, I believe that sound research—in particular, expert caution about VAM—matters in public decision making. As Pearson (2010) points out, this belief is not incompatible with the policy-as-discourse approach. These two perspectives must be combined, he argues, into “an understanding of the policy-making process that weaves together rhetorical analysis and research validity … in order that the ensemble of evidence and reasoning is understood” (p. 81). This is where, theoretically speaking, my work begins.

Existing Research

There is an appreciable body of work analyzing the discourse of educational policy. Scholars consider the rhetorical dimensions of a range of topics, including teachers (Cohen, 2010; Reyes & Rios, 2003; Steudeman, 2014), teachers’ unions (Goldstein, 2011), professors (Winslow, 2015), the state of education (McIntush, 2000), school choice (Weathers, 2007), standardized testing (Phillips, 2004), federal oversight (Asen, 2012), and the role of the media in education policy (Anderson, 2007; Hermansen, 2014).

The present study belongs to this body of work, but it also belongs to another literature that explores how research evidence is rhetorically constructed, marshaled, and disavowed in public decision making. For example, Ceccarelli (2011) identified tactics used to manufacture disciplinary controversy around climate change. Freudenburg, Gramling, and Davidson (2008) showed how uncertainty was exaggerated in asbestos regulation. Oreskes and Conway (2010) studied the cultivation of ignorance around the tobacco-cancer connection. And in a study of debates about alcohol-pricing legislation, Katikireddi, Hilton, and Bond (2016) observed that econometric models functioned primarily as ways to surface conflicting values; their actual implications for pricing were less important.

At the intersection of these two literatures, we find only a handful of studies considering how research evidence is strategically used in educational policymaking. Asen, Gurke, Conners, Solomon, and Gumm (2013) found that research evidence is introduced into school-board debates “to identify problems, to advocate solutions, to critique existing programs, and for other purposes” and that “rather than bolstering a linear, rational process, research participates in a multidirectional process where advocacy plays a key role” (p. 58). In their study of the role of research evidence in district-level decision making, Coburn, Toure, and Yamashita (2009) showed that “district administrators invoke evidence as part of their framing processes to justify, support, and legitimize their proposed solutions” (p. 1144), a process that “differs markedly from the normative models put forth by advocates of evidence-based decision making” (p. 1146).

Very little work has been done to understand how controversy about VAM plays out in popular discourses. A notable exception is Gabriel and Lester’s (2013) case study of VAM coverage by the Los Angeles Times between 2009 and 2011. Methodologically, their study and mine are similar, but our purposes differ. They ask how writers juxtapose various facets of VAM-based teacher evaluation (e.g., teacher quality, teacher evaluation, teachers’ unions, parents, district policy, and VAM) into a single normative narrative. I focus instead on distinct strategies for rhetorically managing technical concerns.

Corpus Construction

My corpus was constructed from three domains where teacher evaluation policy is discussed for the benefit of an audience without technical expertise in VAM: popular media (e.g., general-audience magazines, newspapers, websites), advocacy discourse (e.g., think tanks, political advocacy groups), and policy messaging from the Department of Education. I considered the time period between 2008 (when then chancellor of Washington, DC, public schools Michelle Rhee captured national attention with her highly controversial implementation of VAM-based teacher evaluation) and 2016 (when this research was conducted).

The popular-media portion of my initial corpus consisted of content from two mainstream, general-audience publications. A search of Time Magazine archives simultaneously using the terms “teacher” and “evaluation” yielded 317 articles, 62 of which discussed VAM. A search of the Washington Post archives using the phrases “teacher evaluation” and “value added” (quotation marks used in search) yielded 277 texts, 276 of which discussed VAM.⁴ This popular-media content included a mix of genres (news articles, commentary from staff columnists, op-eds, etc.), all of which are represented in the excerpts that illustrate my findings.

I assembled my initial set of advocacy-discourse texts by reviewing the websites of 64 advocacy groups and think tanks (listed in the appendix) that are described by the American Legislative Exchange Council (Ladner & Lips, 2012) or Diane Ravitch (2014) as taking an active role in education reform. Many of these organizations advocate for changes to the teaching profession including the ways teachers are prepared, evaluated, and compensated and the terms of their employment. Their websites vary in the extent to which they discuss VAM-based teacher evaluation policy, from no discussion to extensive coverage (e.g., blog series, white papers, draft legislation, communication strategies). This domain contributed 192 texts to my initial corpus.

The policy-messaging portion of my initial corpus consisted of speeches from Education Secretary Arne Duncan. A search of the Department of Education’s website using the search phrase “teacher evaluation” yielded 45 speeches, 22 of which discussed VAM.

I added to my initial corpus as I came across new texts that met my selection criteria. My initial corpus consisted of 552 texts; I added 195 during my analysis, so my final corpus included 747 texts, as summarized in Table 1.

Table 1

Distribution of Corpus Texts, by Domain

Texts	Popular Media	Advocacy Discourse	Policy Messaging	Total
Initial	338	192	22	552
Added	164	27	4	195
Total	502	219	26	747

Methodology

My research proceeded in four phases that follow Morgan’s (2008) account of emergent data analysis. Phase 1 consisted of an initial survey of my corpus, during which my coding scheme was relatively open and descriptive; this phase concluded with a set of 15 loosely articulated, potential rhetorical moves. In Phase 2, I designated a third of my corpus for active analysis, and with each subsequent phase, I added a third of my data. Throughout Phases 2 through 4, I moved between emerging theory (my hypothesized set of potential rhetorical moves) and data, iteratively refining my list of moves until I was confident they reflected my corpus material in an accurate and parsimonious way.

The methodological approach taken in rhetorical analysis and grounded theory is very similar (Krathwohl, 2009; Leach, 2000), and readers unfamiliar with the former may understand my process as an instance of the latter. As in grounded theory, my analysis was oriented primarily by my research question and my data, rather than an established theoretical framework (though at certain points, a classic analytical lens from rhetorical studies⁵ helped clarify my understanding or description of an emerging rhetorical move).

Evidence for knowledge claims in rhetorical analysis is qualitative, and this is one way the method differs from typical quantitative methods of content analysis. Rhetorical analysis invites close reading of texts to identify persuasive potential, rather than the reduction of a corpus to countable bits. Readers evaluate the credibility of a study based not on quantitative evidence but on the soundness of the researcher’s arguments, the strength of her evidence, and the reasonableness of her inferences (Jasinski, 2001; Zarefsky, 2008).

Findings

Below I present three rhetorical moves. Although I noticed other minor patterns of argument during my analysis, they were not as salient in my reading of the corpus, nor were they deployed as consistently.

Manufacturing Resolution of Technical Concerns (MRTC)

The first move I will present, MRTC, suggests that technical concerns need not hinder adoption of VAM-based teacher evaluation because they can be or have been resolved. This move draws its persuasive potential from a mismatch between a technical concern and what I will refer to as a “misaligned finding”: a research finding that is spuriously presented as a mitigating counterpoint to the technical concern. This finding must be similar enough (e.g., substantively, methodologically) to the technical concern with which it is juxtaposed that a reader or listener does not perceive the mismatch. The canonical form of the move is as follows. The move opens with a technical concern. This is followed by an adversative (e.g., “but,” “however,” “others say”). The move closes with the misaligned finding. This move distorts the truth but not by fabricating research findings. Everything the rhetor reports is accepted in the expert community. Rather, the crux of the truth distortion is that the misaligned scientific finding is presented as if it resolves the technical concern when, in fact, it does not.

Consider the following instance of MRTC in a New York Times news article that discusses teacher quality, how to measure it, and its long-term effect on students. The move opens with the technical concern that VAM scores are inconsistent for the majority of teachers in the middle of the distribution. This is linked (with the adversative, “but”) to two misaligned findings about special cases where the concern does not apply: “[VAM scores] tend to bounce around for a given teacher from year to year and class to class. But looking at an individual’s value-added score for three or four classes, the researchers found that some consistently outperformed their peers” (Lowrey, 2012, para. 7).

In this example, the findings that follow the adversative do not align with the concern, in the sense that they apply only to teachers for whom a lot of data are available or teachers at the top of the score distribution. A perceptive reader or one with some background knowledge about VAM may notice this misalignment, in which case the move may lose its persuasive power. But for many readers, the take-away message may be defined less by the details of the passage and more by its overall cadence: It moves from doubt to confidence, and this order is key. The author begins with a “yellow light” (i.e., the technical caution) and ends with what many lay readers will interpret as a “green light” (i.e., the special-case findings). Consider how differently the passage would read with a green-to-yellow construction: “Looking at an individual’s value-added score for three or four classes, the researchers found that some consistently outperformed their peers. But VAM scores tend to bounce around for a given teacher from year to year and class to class.” Had the author ordered the passage like this, the take-away message would be one of caution instead of resolved caution.

The structure of MRTC (“X … on the other hand, Y”) is a common one in journalistic genres. Such structures reflect balancing norms and a professional ethos of fairness. To be sure, this rhetorical convention can purposefully be exploited by political actors to shape public opinion, or—in a less dramatic vein—journalists may unintentionally perpetuate a false sense of disciplinary controversy (e.g., climate change rhetoric—see Ceccarelli, 2011). In the present study, I refrain from speculation about rhetor intent. My purpose here is only to describe the argumentative pattern of MRTC and analyze its potential audience effect.

Terrifically misaligned findings

Even when MRTC involves terrifically misaligned findings, this yellow-to-green construction may still mitigate technical concerns. Consider this excerpt from a New York Times news article about the 2012 teachers’ strike in Chicago:

Several studies have shown that teachers who receive high value-added scores—the term for the effect that teachers have on student test performance—in one year can score poorly a year later. “There are big swings from year to year,” said Jesse Rothstein, associate professor of public policy and economics at the University of California, Berkeley. But other studies have shown that students taught by teachers who achieve high value-added scores go on to have lower teenage pregnancy rates, are more likely to go to college and earn higher incomes as adults. (Rich, 2012, para. 16)

To be sure, an astute reader may note that evidence of long-term teacher effects does not resolve a concern about unstable VAM scores. But to a casual or hurried reader, the adversative (“but other studies have shown”) and the yellow-to-green construction may be sufficient to manufacture resolution of Rothstein’s concern.

“Expert-augmented” MRTC

I found a few instances of MRTC in which the canonical form of the move was augmented by referring to specific experts: one linked to the technical concern, and another linked to the misaligned finding. Consider the following example of this “expert-augmented” MRTC, taken from a New York Times news article discussing controversy about VAM-based teacher evaluation:

“If these teachers were measured in a different year, or a different model were used, the rankings might bounce around quite a bit,” said Edward Haertel, a Stanford professor who was a coauthor of the report. “People are going to treat these scores as if they were reflections on the effectiveness of the teachers without any appreciation of how unstable they are.” Other experts disagree. William L. Sanders, a senior research manager for a North Carolina company, SAS, that does value-added estimates for districts in North Carolina, Tennessee and other states, said that “if you use rigorous, robust methods and surround them with safeguards, you can reliably distinguish highly effective teachers from average teachers and from ineffective teachers.” (Dillon, 2010, para. 11–13)

The misalignment here is similar to what we saw in the first example of this section. Haertel’s concern is with the stability of scores for individual teachers; Sanders’s “resolution” deals only with teachers at the top (“highly effective”) and bottom (“ineffective”) of the distribution. We are able to compare these “extreme” teachers (either to teachers at the other extreme or teachers in the middle) with more confidence, but comparisons between and among most teachers (i.e., the nonextreme ones) remain deeply problematic. Three days prior to being quoted in this article, Sanders himself emphasized the danger of this conceptual misalignment on National Public Radio’s Morning Edition:

He [Sanders] says that value-added analysis can accurately single out both star performers and ineffective teachers. But, Sanders cautions, “can you distinguish within the middle? No you can’t, not even with the most distinguished, value-added process that you can bring to the problem.” And Sanders worries that parents may come to the wrong conclusions about those middle-performers. (Abramson, 2010, para. 10–11)

Ignoring Technical Concerns (ITC)

The second move that may legitimate VAM is ITC. This move consists of raising and addressing arguments against VAM—but only nontechnical ones. This keeps technical concerns off the table and maintains the appearance of a fair and balanced discussion of the debate. The move is similar to the use of a red herring to change the course of an argument or a straw man to set up a weak opposition argument. In all cases, a rhetor positions the conversation on grounds where it is easier for her to present a strong case and avoid issues where her position is weaker.

ITC is illustrated in a Washington Post news article about states’ use of student test scores. The discussion of VAM comprises five paragraphs. The first three introduce VAM and relate an anecdote about a teacher who raised the test scores of her struggling students. The fourth and fifth paragraphs set up and resolve two opposition positions:

Some teachers worry that an emphasis on data ignores other progress that can’t be measured on a test, such as emotional and social development. Others are concerned that the data could be used against them. “That’s a rational reaction when you think about how data has been used in the past,” Guidera said. “We have to transform the way we think about data from a hammer that’s going to hurt teachers to a flashlight that’s going to help them.” (Layton, 2012, para. 14–15)

Notice that both objections are belief oriented: about what teachers are supposed to be doing and about how personnel decisions should be made, respectively. No other concerns about VAM-based teacher evaluation are mentioned in the article. The belief-based objections are attributed to a faulty metaphor (i.e., data as a hammer) and resolved with an alternative one (i.e., data as a flashlight).

The first and most obvious way ITC rationalizes audacious use is by keeping readers unaware of technical concerns about VAM. But even if a reader is already aware of these concerns, the move may still mitigate technical objections. When expert caution is left out of the discussion, the implication is that it is not a key factor in decision making about VAM-based teacher evaluation. In this way, the reader is given license to opine about the policy without consulting the research community. The examples in Table 2 further illustrate this variant.

Table 2

Ignoring Technical Concerns

Source	Nontechnical Concerns (Emphasis Added)
News article in Time Magazine about Chancellor Michelle Rhee’s reforms to teacher evaluation in Washington, DC	“People say, ‘Well, you know, test scores don’t take into account creativity and the love of learning,’ [Michelle Rhee] says with a drippy, grating voice, lowering her eyelids halfway. Then she snaps back to herself. ‘I’m like, “You know what? I don’t give a crap.” Don’t get me wrong. Creativity is good and whatever. But if the children don’t know how to read, I don’t care how creative you are. You’re not doing your job’” (Ripley, 2008, para. 21).
Speech by Secretary Duncan at the Harvard Graduate School of Education	• “It is absolutely true that many of today’s tests are flawed. They don’t measure critical thinking across a range of content areas. They are not always aligned to college and career-ready standards. They don’t always accurately measure individual student growth” (Duncan, 2012, para. 68). • “And [standardized tests] certainly don’t measure qualities of great teaching that we know make a difference—things like classroom management, teamwork, collaboration, and individualized instruction. They don’t measure the invaluable ability to inspire a love of learning” (Duncan, 2012, para. 69). • “Now, some folks will point out, correctly, that most teachers don’t teach in tested subjects. So, how can student achievement be factored in to teacher evaluation in nontested subjects? It’s a great question. But I have every faith that teachers themselves can come up with solutions” (Duncan, 2012, para. 84).

Source

Nontechnical Concerns (Emphasis Added)

News article in Time Magazine about Chancellor Michelle Rhee’s reforms to teacher evaluation in Washington, DC

“People say, ‘Well, you know, test scores don’t take into account creativity and the love of learning,’ [Michelle Rhee] says with a drippy, grating voice, lowering her eyelids halfway. Then she snaps back to herself. ‘I’m like, “You know what? I don’t give a crap.” Don’t get me wrong. Creativity is good and whatever. But if the children don’t know how to read, I don’t care how creative you are. You’re not doing your job’” (Ripley, 2008, para. 21).

Speech by Secretary Duncan at the Harvard Graduate School of Education

• “It is absolutely true that many of today’s tests are flawed. They don’t measure critical thinking across a range of content areas. They are not always aligned to college and career-ready standards. They don’t always accurately measure individual student growth” (Duncan, 2012, para. 68).
• “And [standardized tests] certainly don’t measure qualities of great teaching that we know make a difference—things like classroom management, teamwork, collaboration, and individualized instruction. They don’t measure the invaluable ability to inspire a love of learning” (Duncan, 2012, para. 69).
• “Now, some folks will point out, correctly, that most teachers don’t teach in tested subjects. So, how can student achievement be factored in to teacher evaluation in nontested subjects? It’s a great question. But I have every faith that teachers themselves can come up with solutions” (Duncan, 2012, para. 84).

Although simple, this move is important because it appears to have been endorsed by the Department of Education. In the early 2010s, as many states were rolling out new systems of teacher evaluation in exchange for Race to the Top (RTT) funds, a department-sponsored guidance document, the “Educator Evaluation Communications Toolkit,” was published. It provided state, district, and school leaders with rhetorical strategies to “abate criticism, the spread of misinformation and unnecessary concerns” (Reform Support Network, 2013, p. 3) among teachers whose professional evaluations had just been overhauled. The document recommends ways to talk about teacher evaluation in general, but one chapter is devoted specifically to VAM-based teacher evaluation. It includes the following seven “lessons for communicating about value-added data and other measures of student learning” (Reform Support Network, 2013, p. 12):

Hold realistic expectations.

Emphasize function within the larger evaluation system.

Acknowledge shortcomings.

Anticipate and be prepared to respond to misinformation.

Stay out of the weeds.

Plan for glitches.

Move quickly to implementation.

In the explication of the fifth lesson, “stay out of the weeds,” rhetors are instructed to ignore two of the three major technical concerns about VAM:

Offer a detailed explanation to those who are interested, but stay focused on the big picture for everyone else. If you find yourself having a conversation about year-to-year instability or margins of error with a roomful of teachers, chances are most of them will not find the information either useful or helpful to their practice. (Reform Support Network, 2013, p. 12)

Recall that ITC draws on a collection of nontechnical concerns about tool use that can be raised and addressed (in lieu of discussing technical concerns). The guidance document provides these, enumerating 10 “fears and anxieties that many teachers have about the current trajectory of education reform and the future of their profession” (Reform Support Network, 2013, p. 11), none of which is technical. The list includes, for example, concerns about “an unhealthy focus on standardized testing” and “the seeming ‘mechanization’ of teaching” (Reform Support Network, 2013, p. 12).

Impugning Opposition Arguments (IOA)

Compared to the first two moves, IOA appeals less to logic and more to a sense of right and wrong. Technical concerns may or may not be mentioned; either way, the VAM controversy is constructed as a moral struggle, with opposition arguments on the low ground. Four variants of this move were identified; each suggests a different moral lapse that underlies opposition arguments.

Opponents are avoiding reality

The first variant of IOA suggests that opposition arises from a desire to avoid an unpleasant but critical reality. Several examples of this move appear in Secretary Duncan’s discourse championing RTT, particularly the parts of the program that pertained to teacher evaluation. In a speech to education journalists shortly after RTT was introduced, he asserted that policies like VAM-based teacher evaluation “expos[e] the good, the bad and the ugly around issues like teacher effectiveness. … This is not always fun. No one wants to admit their flaws—let alone do something about them” (Duncan, 2009a, para. 29–30). On his annual Back to School tour the next year—as he discussed the publication of VAM scores and their use in high-stakes teacher evaluation—we see the same moral framing: “The truth is always hard to swallow but it can only make us better, stronger and smarter. That’s what accountability is all about—facing the truth and taking responsibility and then taking action” (Duncan, 2010b, para. 80). This move signals to the audience that proponents of VAM-based teacher evaluation are champions of courage and integrity; by implication, opponents are skirting both the truth and their responsibility for it. The examples in Table 3 further illustrate this tactic.

Table 3

Opponents Are Avoiding Reality

Source	Suggestive Language (Emphasis Added)
Opinion piece in Time Magazine titled “Blame Game: Let’s Talk Honestly About Bad Teachers”	“And the politics won’t change until we can at least talk about teacher effectiveness and the broader problems of educational management in an intellectually honest way” (Rotherham, 2011, para. 12).
Open letter about education reform, published by the Washington Post and penned by several leaders of large school districts	“[A] poorly performing teacher can hold back hundreds, maybe thousands, of students over the course of a career. Each day that we ignore this reality is precious time lost for children” (Klein et al., 2010, para. 8). “Of course, we must also do a better job of providing meaningful training for teachers who seek to improve, but let’s stop pretending that everyone who goes into the classroom has the ability and temperament to lift our children to excellence” (Klein et al., 2010, para. 12).
One in a series of news articles that accompanied the release of value-added modeling scores by the Los Angeles Times	“But across the country, parents have no access to objective information about teacher effectiveness, and many districts have opted to ignore the data” (Felch & Song, 2010, para. 14).
Speech by Secretary Duncan to Arkansas teachers, administrators, and policymakers to promote reform policies of Race to the Top	“We cannot shrink from the truth” (Duncan, 2010b, para. 108).
Speech by Secretary Duncan to state governors, shortly after introduction of Race to the Top	“Some states actually have laws creating a firewall between teacher evaluation and student achievement. This isn’t fair to kids or to teachers. Worse yet, it’s not honest” (Duncan, 2009b, para. 31).

Opponents fear change

The second variant of IOA suggests that fear of change underlies opposition to VAM-based teacher evaluation. VAM is frequently depicted as sophisticated or modern, whereas other methods of measuring teacher quality are depicted as simple or obsolete. For example, in a New York Times news article, “traditional criteria like evaluations from principles” are contrasted with the “nationwide experiment” (Porter, 2015, para. 11) and “sophisticated research” (Porter, 2015, para. 13) that constitute VAM-based teacher evaluation. In the article’s penultimate paragraph, we see the suggestion that a fear of technological change motivates opponents of the policy:

Brad Jupp, a special adviser to Secretary Arne Duncan, compares the anxiety about the adoption of new evaluation tools to the uncertainty in the 1940s over what would happen if the sound barrier was broken. Some people thought it would destroy the plane. Others thought the plane would accelerate to a million miles per hour. When Chuck Yeager finally broke it in 1947, neither happened. (Porter, 2015, para. 29)

Rhetors also may emphasize the shift in culture or thinking that accompanies VAM-based teacher evaluation and then suggest that opponents are uncomfortable with this philosophical change. We see this strategy in a report published by the advocacy organization Students First, titled “Elevating the Teaching Profession: Increasing Teacher Quality”: “State and school leaders must work concurrently to change the culture around evaluations and how they are used. We must as a nation become comfortable with differentiating performance among educators” (Students First, 2013, p. 6). This variant of IOA presents readers with a choice: brave support of VAM-based teacher evaluation or fearful inflexibility. The tactic is further illustrated in Table 4.

Table 4

Opponents Fear Change

Source	Suggestive Language (Emphasis Added)
Speech by Secretary Duncan to the National Education Association, shortly after introduction of Race to the Top	“Now, let’s talk about data. I understand that word can make people nervous” (Duncan, 2009c, para. 61).
Guidebook of rhetorical strategies (sponsored by the Department of Education) for communicating about VAM-based teacher evaluation and other Race to the Top–mandated reforms to the profession	“The concept is a new one, and represents a shift from past systems. Teacher evaluations traditionally have not been tied to student performance, and many educators and researchers are understandably anxious about this unfamiliar and unexplored territory” (Reform Support Network, 2013, p. 11).
Speech by Secretary Duncan to education leaders in Los Angeles; the excerpted text precedes an entreaty for VAM-based teacher evaluation	“The time is now to get off the well-trod road in favor of the road less traveled. The time is now to confront challenges—and leave the comfort zone behind” (Duncan, 2011, para. 20).
News article in the New York Times titled “Principals Protest Role of Testing in Evaluations”	“Asked if he was surprised by the number of principals who had signed [a statement of opposition to VAM-based teacher evaluation], he wrote, ‘It’s not at all surprising’ that the introduction of a new evaluation system ‘would produce anxiety’” (Winerip, 2011, para. 13).

Note. VAM = value-added modeling.

Opponents are withholding information

The third variant of IOA is used in the debate about whether the VAM scores of individual teachers should be available to parents or the public. Technical concerns bear directly on this debate because publishing imprecise, inconsistent, or inaccurate information about an individual is understood by some to be a form of libel. These concerns are eclipsed when the debate is constructed around topoi like right to information (i.e., citizens should have access to information held by public bodies) and political censorship (i.e., political power can be maintained by withholding information). This move appears often when news outlets defend their choice to publish VAM scores. For example, after expressing sympathy to the family of a teacher who committed suicide following the publication of his VAM score, the New York Times continued its condolence statement with the following:

The Times published the database, which is based on seven years of state test scores in the L.A.U.S.D. schools, because it bears directly on the performance of public employees who provide an important service, and in the belief that parents and the public have a right to judge the data for themselves. (Lovett, 2010, para. 11)

When the debate is framed in this way, the implicit message is that those who oppose making VAM scores public are trying to withhold or hide information that ought to be publicly available. For a reader or listener who values principles of transparent governance, this variant of IOA aligns transparency with the release of scores. The examples in Table 5 further illustrate this tactic.

Table 5

Opponents Are Withholding Information

Source	Suggestive Language (Emphasis Added)
One in a series of news articles that accompanied the release of VAM scores by the Los Angeles Times	“For now, parents remain mostly in the dark. … Which instructor a child gets is usually decided behind closed doors by principals and teachers, whose criteria vary widely” (Felch, Song, & Smith, 2010, para. 103–105).
One in a series of news articles that accompanied the release of VAM scores by National Public Radio and the Cleveland Plain Dealer	“If public information exists about the quality of a teacher, who are we to deny that information to the parent?” (IdeaStream, 2013, para. 16).
News article in the Washington Post in which a parent discusses teachers whose VAM scores are at the bottom of the distribution	“Any kid who is stuck with one of those teachers is going to have a problem. … Why would you want to hide that information from parents?” (Brown & Balingit, 2015, para. 13).
News article in the New York Times in which the chancellor of New York City schools defends his release of VAM scores	“For too long parents have been left out of the equation, left to pray each year that the teacher greeting their children on the first day of school is truly great, but with no real knowledge of whether that is the case, and with no recourse if it’s not” (Otterman, 2010, para. 10).

Note. VAM = value-added modeling.

Opponents have ulterior motives

In the final variant of IOA, technical concerns are associated with nonexperts who have known political interests in the debate. This curbs the decision-making heft of technical concerns in two ways. First, it draws attention away from the substantive content of the concerns and toward the political aspects of the debate. Second, by associating the concerns with nonexperts, the move strips them of an aura of objectivity they might have otherwise had. To be clear, there is almost never a direct assertion that the experts who express concern have a partisan interest in the debate. But through a sort of guilt by association, the move suggests that perhaps concerns can be taken with a grain of salt, considering that they align with the motives of partisan groups. This occurs in the previously quoted New York Times article that discusses teacher quality, how to measure it, and its long-term effect on students:

Supporters [of VAM-based teacher evaluation] argue that such metrics hold teachers accountable and can help improve the educational outcomes of millions of children. Detractors, most notably a number of teachers unions, say that isolating the effect of a given teacher is harder than it seems, and might unfairly penalize some instructors. Critics particularly point to the high margin of error with many value-added ratings. (Lowrey, 2012, para. 6–7)

The implicit message here is that teachers’ unions are raising technical concerns only because it serves their political agenda. Less subtle instances of this move may include an explicit account of why the concern has been raised, as in the following excerpt from a policy paper published by the advocacy organization Bellwether Education Partners:

Evaluations by RAND, The Gates Foundation’s MET project, and other researchers show that while value-added models should be used with caution, they can help responsibly inform some personnel decisions and are not the lottery their critics make them out to be. Yet critics have seized on technical elements of value-added data as a way to undercut teacher evaluations generally. (Rotherham & Mitchel, 2014, p. 15)

The final sentence in the passage makes it clear that the reader should not take technical concerns at face value. Because they are raised to further a political agenda, they should invite skepticism, and their authority in decisions about teacher evaluation policy is dubious. Additional examples of this variant are provided in Table 6.

Table 6

Opponents Have Ulterior Motives

Source	Suggestive Language (Emphasis Added)
News article in the New York Times titled “Grading Teachers by the Test”	“Critics have questioned the Harvard scholars’ findings. Teachers argue there is no way they could isolate the impact of teaching itself from other factors affecting children’s learning, particularly such things as the family background of the students, the impact of poverty, racial segregation, even class size” (Porter, 2015, para. 16).
Editorial in the New York Daily News titled “Release of Teacher Test Data in English and Math Is a Big Step Forward”	“Teachers union boss Michael Mulgrew has demagogued the ratings effort. Nitpicking the methodology and mocking the complex formula, he says the reports should have been withheld” (“Release of Teacher Test,” 2012, para. 10).
News article in the Washington Post titled “Contentious Teacher-Related Policies Moving From Legislatures to the Courts”	“Critics say that the unions are exaggerating both the problems associated with value-added scores and the weight that they carry in evaluations. Value-added scores account for up to 50 percent of evaluations in some states, and a smaller portion in many others, with the remainder of teachers’ ratings comprised of classroom observations and other measures. ‘Essentially teacher unions don’t want any evaluation,’ said Eric Hanushek, an economist at Stanford University’s conservative Hoover Institute and a supporter of value-added measures. ‘That’s what they’re angling for’” (Brown, 2015, para. 8–9).
News article in the Los Angeles Times titled “D.C. Schools May Hold Lesson for L.A.”	“Some educational experts and union leaders say that value-added is not reliable enough for high-stakes decisions on firing, tenure or pay. … Senior program officer Steve Cantrell said concerns that the method may inaccurately assess some teachers must be balanced against the likelihood that it will improve the chances for children to have an effective instructor. ‘If you shift the perspective from what is best for adults to what is best for students, then it’s super clear that value-added can improve the system over time,’ he said” (Watanabe, 2010, para. 13–15).

Discussion

This study identified three rhetorical moves (see Table 7) with the potential to legitimate VAM-based teacher evaluation. The first move acknowledges technical concerns and suggests that they have been or can be resolved. Technical concerns are absent from the second move, where a rhetor responds only to nontechnical opposition arguments. In the third move, opposition arguments (technical or nontechnical) are depicted as morally suspect. These moves, the caution they obfuscate, and the case of VAM overall point to an oft-overlooked role of expertise in public decision making.

Table 7

Summary of Findings: Three Rhetorical Moves

Rhetorical Move	Description
Manufacturing resolution of technical concerns	Suggesting that technical concerns about VAM can be or have been resolved
Ignoring technical concerns	Raising and addressing only nontechnical concerns about VAM
Impugning opposition arguments	Suggesting that opposition to VAM is morally suspect: • Opponents fear change. • Opponents are withholding information. • Opponents have ulterior motives.

Note. VAM = value-added modeling.

What makes the case of VAM so interesting is that a highly technical research tool is nestled into a warren of deeply nontechnical issues. The purpose of education, the importance of different kinds of learning, the responsibilities of teachers—these questions draw on values and beliefs and thus belong in the jurisdiction of the broadest possible sweep of stakeholders. Yes, experts can weigh in, but our expertise should lend no special credence to our input.

But there are two issues where our expertise is directly relevant. The first is obvious: We are uniquely qualified to evaluate the technical capacity of our tools. It makes no sense to pose the question, How large do standard errors tend to be for this type of teacher with this type of data? to a broad swath of stakeholders. The question belongs to education researchers familiar with VAM.

The second issue where our expertise better qualifies us to weigh in is the higher order question, Is this a technical issue or not? Bromme and Goldman (2014) explain that when “problems … of social policy have both science- and nonscience-related dimensions to their framing, possible solutions, and side effects” (p. 64), nonexperts face a greater challenge than experts in distinguishing between these two dimensions. This is because debates are often rhetorical shell games of technical, political, social, ethical, and other issues in which nonexperts have to work simultaneously to understand the technical issues and to keep their eyes on them. This means experts are at an advantage when it comes to the latter because they expend minimal effort on the former. Bromme and Goldman also note that advocates may take advantage of this asymmetry, intentionally conflating science- and nonscience-related dimensions of a problem (we saw this in IOA) in order to deliberately distort the state of the science (we saw this in MRTC).

So what does this suggest about our role as experts in situations where the policy use of a research tool has run ahead of its methodological capacity? In addition to urging caution, we can improve communication for other stakeholders by distinguishing technical from nontechnical issues. For example, “you and I may disagree about what to do with below-average teachers, but whether VAM can identify them reliably is a technical question and experts have answered it.”

Walsh (2010) notes that public trust and perceived legitimacy are low for experts who try to smuggle their political views into a debate by rhetorically flashing their expertise badge. Her work suggests that clarifying the issues where we are not experts may actually increase our perceived legitimacy around issues where we are. True, this will not resolve fundamental differences of values or beliefs that underlie disagreements in education reform. But it may help us debate—and disagree—more productively.

Footnotes

Appendix

List of advocacy groups and think tanks identified by Ladner and Lips (2012) or Ravitch (2014) as reform oriented.

Notes

Author

GLORY TOBIASON, PhD, is a lecturer in the Graduate School of Education and Information Studies at the University of California, Los Angeles; 300 Charles E. Young Drive North, GSEIS Building, Room 301, Los Angeles, CA 90095; tobiason@cresst.ucla.edu. Her research focuses on the rhetorical dimensions of education research and policy, with a particular focus on teachers and teacher evaluation.

References

Abramson

(2010, August 27). “L.A. Times” teacher ratings database stirs debate. Morning Edition [Radio program]. Washington, DC: National Public Radio. Retrieved from http://www.npr.org/templates/story/story.php?storyId=129456212

American Educational Research Association. (2015). AERA statement on use of value-added models (VAM) for the evaluation of educators and educator preparation programs. Educational Researcher, 44(8), 448–452.

American Statistical Association. (2014). ASA statement on using value-added models for educational assessment. Alexandria, VA: Author. Retrieved from http://www.amstat.org/policy/pdfs/ASA_VAM_Statement.pdf

Anderson

G. L.

(2007). Media’s impact on educational policies and practices: Political spectacle and social control. Peabody Journal of Education, 82(1), 103–120.

Asen

(2010). Reflections on the role of rhetoric in public policy. Rhetoric and Public Affairs, 13(1), 121–143.

Asen

(2012). Lyndon Baines Johnson and George W. Bush on education reform: Ascribing agency and responsibility through key policy terms. Rhetoric & Public Affairs, 15(2), 289–317.

Asen

Gurke

Conners

Solomon

Gumm

(2013). Research evidence and school board deliberations: Lessons from three Wisconsin school districts. Educational Policy, 27(1), 33–63.

Bitzer

L. F.

(1968). The rhetorical situation. Philosophy and Rhetoric, 1(1), 1–14.

Bourdieu

(1975). The specificity of the scientific field and the social conditions of the progress of reason. Social Science Information, 14(6), 19–47.

10.

Boyd

W. L.

(1999). Paradoxes of educational policy and productivity. Educational Policy, 13(2), 227–250.

11.

Bromme

Goldman

S. R.

(2014). The public’s bounded understanding of science. Educational Psychologist, 49(2), 59–69.

12.

Brown

(2015, February 28). Contentious teacher-related policies moving from legislatures to the courts. Washington Post. Retrieved from https://www.washingtonpost.com/local/education/contentious-teacher-related-policies-moving-from-legislatures-to-the-courts/2015/02/28/6ec1f31e-b83d-11e4-aa05-1ce812b3fdd2_story.html?utm_term=.1089f34dc258

13.

Brown

Balingit

(2015, March 16). Virginia pushed into debate of teacher privacy vs. transparency for parents. Washington Post. Retrieved from https://www.washingtonpost.com/local/education/parent-suing-state-officials-to-make-teacher-evaluation-data-public/2015/03/15/9b441a58-c98f-11e4-b2a1-bed1aaea2816_story.html?utm_term=.ed8f6cba927c

14.

Ceccarelli

(2011). Manufactured scientific controversy: Science, rhetoric, and public debate. Rhetoric & Public Affairs, 14(2), 195–228.

15.

Coburn

Toure

Yamashita

(2009). Evidence, interpretation, and persuasion: Instructional decision making at the district central office. Teachers College Record, 111(4), 1115–1161.

16.

Cohen

J. L.

(2010). Teachers in the news: A critical analysis of one US newspaper’s discourse on education, 2006–2007. Discourse: Studies in the Cultural Politics of Education, 31(1), 105–119.

17.

Dillon

(2010, August 31). Formula to grade teachers’ skill gains acceptance, and critics. New York Times. Retrieved from http://www.nytimes.com/2010/09/01/education/01teacher.html

18.

Duncan

(2009a, April 30). Partners in truth-telling: Secretary Arne Duncan’s remarks to the Education Writers Association. Retrieved from https://www.ed.gov/news/speeches/partners-truth-telling

19.

Duncan

(2009b, June 14). States will lead the way toward reform: Secretary Arne Duncan’s remarks at the 2009 Governors Education Symposium. Retrieved from https://www.ed.gov/news/speeches/states-will-lead-way-toward-reform

20.

Duncan

(2009c, July 2). Partners in reform: Remarks of Arne Duncan to the National Education Association. Retrieved from https://www.ed.gov/news/speeches/partners-reform

21.

Duncan

(2010a, June 29). Education research: Charting the course for reform—Remarks by Secretary Arne Duncan at the Institute of Education Sciences research conference. Retrieved from https://www.ed.gov/news/speeches/education-research-charting-course-reform-%E2%80%94-remarks-secretary-arne-duncan-institutes-education-research-conference

22.

Duncan

(2010b, August 25). Secretary Arne Duncan’s remarks at the Statehouse Convention Center in Little Rock, Arkansas. Retrieved from https://www.ed.gov/news/speeches/secretary-arne-duncans-remarks-statehouse-convention-center-little-rock-arkansas

23.

Duncan

(2011, March 22). The road less traveled: Remarks of U.S. Secretary of Education Arne Duncan at the United Way of Greater Los Angeles Education Summit. Retrieved from https://www.ed.gov/news/speeches/road-less-traveled

24.

Duncan

(2012, February 7). Fighting the wrong education battles: Remarks of Secretary Duncan at the Askwith Forum, Harvard Graduate School of Education. Retrieved from https://www.ed.gov/news/speeches/fighting-wrong-education-battles

25.

Fahnestock

Secor

(1988). The stases in scientific and literary argument. Written Communication, 5, 427–443.

26.

Felch

Song

(2010, August 16). U.S. schools chief endorses release of teacher data. Los Angeles Times. Retrieved from http://articles.latimes.com/2010/aug/17/local/la-me-0817-teachers-react-20100817-

27.

Felch

Song

Smith

(2010, August 14). Who’s teaching L.A.’s kids? Los Angeles Times. Retrieved from http://articles.latimes.com/2010/aug/14/local/la-me-teachers-value-20100815

28.

Fischer

Forester

(1993). The argumentative turn in policy analysis and planning. Durham, NC: Duke University Press.

29.

Freudenburg

W. R.

Gramling

Davidson

D. J.

(2008). Scientific Certainty Argumentation Methods (SCAMs): Science and the politics of doubt. Sociological Inquiry, 78(1), 2–38.

30.

Gabriel

Lester

J. N.

(2013). The romance quest of education reform: A discourse analysis of The LA Times’ reports on value-added measurement teacher effectiveness. Teachers College Record, 115(12), 1–32.

31.

Goldstein

R. A.

(2011). Imaging the frame: Media representations of teachers, their unions, NCLB, and education reform. Educational Policy, 25(4), 543–576.

32.

Hammersley

(2014). The limits of social science: Causal explanation and value relevance. Thousand Oaks, CA: Sage.

33.

Hermansen

P. M.

(2014). “There was no one coming with enough power to save us”: Waiting for “Superman” and the rhetoric of the new education documentary. Rhetoric & Public Affairs, 17(3), 511–540.

34.

IdeaStream. (2013, June 16). Grading the teachers: Why we’re publishing teachers’ value-added ratings. Retrieved from http://wcpn.ideastream.org/stateimpact/2013/06/16/grading-the-teachers-why-were-publishing-teachers-value-added-ratings

35.

Jasanoff

(2012). Science and public reason. New York, NY: Routledge.

36.

Jasinski

2001. The status of theory and method in rhetorical criticism. Western Journal of Communication, 65(3), 249–270.

37.

Johnson

B. L.

Jr. (1999). The politics of research-information use in the education policy arena. Educational Policy, 13(1), 23–36.

38.

Katikireddi

S. V.

Hilton

Bond

(2016). The role of the Sheffield model on the minimum unit pricing of alcohol debate: The importance of a rhetorical perspective. Evidence & Policy: A Journal of Research, Debate and Practice, 12(4), 521–539.

39.

Klein

Rhee

Gorman

P. C.

Huberman

Johnson

C. R.

Alonso

A. A.

. . . Sheffield

(2010, October 10). How to fix our schools: A manifesto by Joel Klein, Michelle Rhee and other education leaders. Washington Post. Retrieved from http://www.washingtonpost.com/wp-dyn/content/article/2010/10/07/AR2010100705078.html

40.

Krathwohl

D. R.

(2009). Methods of educational and social science research: The logic of methods (3rd ed.). Long Grove, IL: Waveland.

41.

Ladner

Lips

(2012). Report card on American education: Ranking state K-12 performance, progress, and reform. Washington, DC: American Legislative Exchange Council. Retrieved from https://www.alec.org/publication/2012-education-report-card/

42.

Latour

Woolgar

(1979). Laboratory life: The construction of scientific facts. Beverly Hills, CA: Sage.

43.

Layton

(2012, January 17). States should make better use of academic data, study says. Washington Post. Retrieved from https://www.washingtonpost.com/local/education/states-should-make-better-use-of-academic-data-study-says/2012/01/17/gIQAb6cs6P_story.html?utm_term=.194e9b1e8e43

44.

Leach

(2000). Rhetorical analysis. In Bauer

M. W.

Gaskell

(Eds.), Qualitative researching with text, image, and sound: A practical handbook (pp. 207–226). Thousand Oaks, CA: Sage.

45.

Longino

(1990). Science as social knowledge. Values and objectivity in scientific inquiry. Princeton, NJ: Princeton University Press.

46.

Lovett

(2010, November 9). Teacher’s death exposes tensions in Los Angeles. New York Times. Retrieved from http://www.nytimes.com/2010/11/10/education/10teacher.html

47.

Lowrey

(2012, January 6). Big study links good teachers to lasting gain. New York Times. Retrieved from http://www.nytimes.com/2012/01/06/education/big-study-links-good-teachers-to-lasting-gain.html

48.

Majone

(1989). Evidence, argument and persuasion in the policy process. New Haven, CT: Yale University Press.

49.

McIntush

H. G.

(2000). Defining education: The rhetorical enactment of ideology in A Nation at Risk. Rhetoric & Public Affairs, 3(3), 419–443.

50.

Messick

(1981). Evidence and ethics in the evaluation of tests. Educational Researcher, 10(9), 9–20.

51.

Morgan

D. L.

(2008). Emergent design. In Given

L. M.

(Ed.), The SAGE encyclopedia of qualitative research methods (pp. 246–248). Thousand Oaks, CA: Sage.

52.

National Council on Teacher Quality. (2013). State of the states 2013—Connect the dots: Using evaluations of teacher effectiveness to inform policy and practice. Washington, DC: Author. Retrieved from http://www.nctq.org/dmsView/State_of_the_States_2013_Using_Teacher_Evaluations_NCTQ_Report

53.

National Council on Teacher Quality. (2015). State of the states 2015—Evaluating Teaching, Leading and Learning. Washington, DC: Author. Retrieved from http://www.nctq.org/dmsStage/StateofStates2015

54.

National Council on Teacher Quality. (2017). Running in place: How new teacher evaluations fail to live up to promises. Washington, DC: Author. Retrieved from http://www.nctq.org/dmsStage/Final_Evaluation_Paper

55.

Oreskes

Conway

E. M.

(2010). Merchants of doubt: How a handful of scientists obscured the truth on issues from tobacco smoke to global warming. New York, NY: Bloomsbury.

56.

Otterman

(2010, December 26). Hurdles emerge in rising effort to rate teachers. New York Times. Retrieved from http://www.nytimes.com/2010/12/27/nyregion/27teachers.html

57.

Pearson

(2010). “What do we know? What should we do?” Melding research validity and rhetoric in the analysis of policy making. Evidence & Policy: A Journal of Research, Debate and Practice, 6(1), 77–90.

58.

Phillips

K. R.

(2004). Testing controversy: A rhetoric of educational reform. Cresskill, NJ: Hampton.

59.

Porter

(2015, March 24). Grading teachers by the test. New York Times. Retrieved from https://www.nytimes.com/2015/03/25/business/economy/grading-teachers-by-the-test.html

60.

Ravitch

(2014). Reign of error: The hoax of the privatization movement and the danger to America’s public schools. New York, NY: Knopf.

61.

Reform Support Network. (2013). Educator evaluation communications toolkit: Tools and resources to support states in communicating about educator evaluation systems. Retrieved from https://www2.ed.gov/about/inits/ed/implementation-support-unit/tech-assist/educator-evaluation-communications-toolkit.pdf

62.

“Release of teacher test data in English and math is a big step forward” [Editorial]. (2012, February 25). New York Daily News. Retrieved from http://www.nydailynews.com/opinion/release-teacher-test-data-english-math-big-step-article-1.1028281

63.

Reyes

X. A.

Rios

D. I.

(2003). Imaging teachers: In fact and in the mass media. Journal of Latinos and Education, 2(1), 3–11.

64.

Rich

(2012, September 11). National schools debate is on display in Chicago. New York Times. Retrieved from http://www.nytimes.com/2012/09/12/education/chicago-is-focus-of-national-debate-on-teacher-evaluation.html

65.

Ripley

(2008, November 26). Rhee tackles classroom challenge. Time Magazine. Retrieved from http://content.time.com/time/subscriber/article/0,33009,1862444,00.html

66.

Rotherham

A. J.

(2011, October 20). Blame game: Let’s talk honestly about bad teachers. Time Magazine. Retrieved from http://ideas.time.com/2011/10/20/blame-game-lets-talk-honestly-about-bad-teachers/

67.

Rotherham

A. J.

Mitchel

A. L.

(2014). Genuine progress, greater challenges: A decade of teacher effectiveness reforms. Sudbury, MA: Bellwether Education Partners. Retrieved from http://bellwethereducation.org/publication/genuine-progress-greater-challenges-decade-teacher-effectiveness-reforms

68.

Russell

Greenhalgh

Byrne

McDonnell

(2008). Recognizing rhetoric in health care policy analysis. Journal of Health Services Research & Policy, 13(1), 40–46.

69.

Shaddish

W. R.

Cook

T. D.

Campbell

D. T.

(2002). Experimental and quasi-experimental designs for generalized causal inference. Boston, MA: Houghton Mifflin.

70.

Shapin

Schaffer

(1985). Leviathan and the air-pump: Hobbes, Boyle, and the experimental life. Princeton, NJ: Princeton University Press.

71.

Slavin

R. E.

(2002). Evidence-based education policies: Transforming educational practice and research. Educational Researcher, 31(7), 15–21.

72.

Steudeman

M. J.

(2014). “The guardian genius of democracy”: The myth of the heroic teacher in Lyndon B. Johnson’s education policy rhetoric, 1964–1966. Rhetoric & Public Affairs, 17(3), 477–510.

73.

Students First. (2013). Elevating the teaching profession: Increasing teacher quality. Sacramento, CA: Author. Retrieved from https://www.studentsfirst.org/page/-/publications/TeacherBriefUpdate.pdf

74.

Walsh

(2010). Before Climategate: Visual strategies to integrate ethos across the “is/ought” divide in the IPCC’s Climate Change 2007. Issues in the Rhetoric of Science and Technology, 6(2), 33–61.

75.

Watanabe

(2010, November 14). D.C. schools may hold lesson for L.A. Los Angeles Times. Retrieved from http://articles.latimes.com/2010/nov/14/news/la-teachers-dc-schools-lesson

76.

Weathers

(2007). Privatizing schools: The struggle over how we define democracy and the role of public institutions. Working Papers in Educational Linguistics, 2(2), 67–93.

77.

Winerip

(2011, November 27). Principals protest role of testing in evaluations. New York Times. Retrieved from http://www.nytimes.com/2011/11/28/education/principals-protest-increased-use-of-test-scores-to-evaluate-educators.html

78.

Winslow

(2015). The undeserving professor: Neoliberalism and the reinvention of higher education. Rhetoric & Public Affairs, 18(2), 201–245.

79.

Wiseman

A. W.

(2010). The uses of evidence for educational policymaking: Global contexts and international trends. Review of Research in Education, 34, 1–24.

80.

Zarefsky

2008. Knowledge claims in rhetorical criticism. Journal of Communication, 58(4), 629–640.