States’ Teacher Evaluation Systems Now “All over the Map”

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We are now just one year past the federal passage of the Every Student Succeeds Act (ESSA), within which it is written that states must no longer set up teacher-evaluation systems based in significant part on their students’ test scores. As per a recent article written in Education Week, accordingly, most states are still tinkering with their teacher evaluation systems—particularly regarding the student growth or value-added measures (VAMs) that were also formerly required to help states assesses teachers’ purported impacts on students’ test scores over time.

“States now have a newfound flexibility to adjust their evaluation systems—and in doing so, they’re all over the map.” Likewise, though, “[a] number of states…have been moving away from [said] student growth [and value-added] measures in [teacher] evaluations,” said a friend, colleague, co-editor, and occasional writer on this blog (see, for example, here and here) Kimberly Kappler Hewitt (University of North Carolina at Greensboro).  She added that this is occurring “whether [this] means postponing [such measures’] inclusion, reducing their percentage in the evaluation breakdown, or eliminating those measures altogether.”

While states like Alabama, Iowa, and Ohio seem to still be moving forward with the attachment of students’ test scores to their teachers, other states seem to be going “back and forth” or putting a halt to all of this altogether (e.g, California). Alaska cut back the weight of the measure, while New Jersey tripled the weight to count for 30% of a teacher’s evaluation score, and then introduced a bill to reduce it back to 0%. In New York teacher are to still receive a test-based evaluation score, but it is not to be tied to consequences and completely revamped by 2019. In Alabama a bill that would have tied 25% of a teacher’s evaluation to his/her students’ ACT and ACT Aspire college-readiness tests has yet to see the light of day. In North Carolina state leaders re-framed the use(s) of such measures to be more for improvement tool (e.g., for professional development), but not “a hammer” to be used against schools or teachers. The same thing is happening in Oklahoma, although this state is not specifically mentioned in this piece.

While some might see all of this as good news — or rather better news than what we have seen for nearly the last decade during which states, state departments of education, and practitioners have been grappling with and trying to make sense of student growth measures and VAMs — others are still (and likely forever will be) holding onto what now seems to be some of the now unclenched promises attached to such stronger accountability measures.

Namely in this article, Daniel Weisberg of The New Teacher Project (TNTP) and author of the now famous “Widget Effect” report — about “Our National Failure to Acknowledge and Act on Differences in Teacher Effectiveness” that helped to “inspire” the last near-decade of these policy-based reforms — “doesn’t see states backing away” from using these measures given ESSA’s new flexibility. We “haven’t seen the clock turn back to 2009, and I don’t think [we]’re going to see that.”

Citation: Will, M. (2017). States are all over the map when it comes to how they’re looking to approach teacher-evaluation systems under ESSA. Education Week. Retrieved from

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The Elephant in the Room – Fairness

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While VAMs have many issues pertaining, fundamentally, to their levels of reliability, validity, and bias, they are wholeheartedly unfair. This is one thing that is so very important but so rarely discussed when those external to VAM-based metrics and metrics use are debating, mainly the benefits of VAMs.

Issues of “fairness” arise when a test, or more likely its summative (i.e., summary and sometimes consequential) and formative (i.e., informative) uses, impact some more than others in unfair yet often important ways. In terms of VAMs, the main issue here is that VAM-based estimates can be produced for only approximately 30-40% of all teachers across America’s public schools. The other 60-70%, which sometimes includes entire campuses of teachers (e.g., early elementary and high school teachers), cannot altogether be evaluated or “held accountable” using teacher- or individual-level VAM data.

Put differently, what VAM-based data provide, in general, “are incredibly imprecise and inconsistent measures of supposed teacher effectiveness for only a tiny handful [30-40%] of teachers in a given school” (see reference here). But this is often entirely overlooked, not only in the debates surrounding VAM use (and abuse) but also in the discussions surrounding how many taxpayer-derived funds are still being used to support such a (purportedly) reformatory overhaul of America’s public education system. The fact of the matter is that VAMs only directly impact the large minority.

While some states and districts are rushing into adopting “multiple measures” to alleviate at least some of these issues with fairness, what state and district leaders don’t entirely understand is that this, too, is grossly misguided. Should any of these states and districts also tie serious consequences to such output (e.g., merit pay, performance plans, teacher termination, denial of tenure), or rather tie serious consequences to measures of growth derived via any varieties of the “multiple assessment” that can be pulled from increasingly prevalent multiple assessment “menus,” states and districts are also setting themselves for lawsuits…no joke! Starting with the basic psychometrics, and moving onto the (entire) lack of research in support of using more “off-the-shelf” tests to help alleviate issues with fairness, would be the (easy) approach to take in a court of law as, really, doing any of this is entirely wrong.

School-level value-added is also being used to accommodate the issue of “fairness,” just less frequently now than before given the aforementioned “multiple assessment” trends. Regardless, many states and districts also continue to attribute a school-level aggregate score to teachers who do not teach primarily reading/language arts and mathematics, primarily in grades 3-8. That’s right, a majority of teachers receive a value-added score that is based on students whom they do not teach. This also calls for legal recourse, also in that this has been a contested issue within all of the lawsuits in which I’ve thus far been engaged.

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Another Study about Bias in Teachers’ Observational Scores

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Following-up on two prior posts about potential bias in teachers’ observations (see prior posts here and here), another research study was recently released evidencing, again, that the evaluation ratings derived via observations of teachers in practice are indeed related to (and potentially biased by) teachers’ demographic characteristics. The study also evidenced that teachers representing racial and ethnic minority background might be more likely than others to not only receive lower relatively scores but also be more likely identified for possible dismissal as a result of their relatively lower evaluation scores.

The Regional Educational Laboratory (REL) authored and U.S. Department of Education (Institute of Education Sciences) sponsored study titled “Teacher Demographics and Evaluation: A Descriptive Study in a Large Urban District” can be found here, and a condensed version of the study can be found here. Interestingly, the study was commissioned by district leaders who were already concerned about what they believed to be occurring in this regard, but for which they had no hard evidence… until the completion of this study.

Authors’ key finding follows (as based on three consecutive years of data): Black teachers, teachers age 50 and older, and male teachers were rated below proficient relatively more often than the same district teachers to whom they were compared. More specifically,

  • In all three years the percentage of teachers who were rated below proficient was higher among Black teachers than among White teachers, although the gap was smaller in 2013/14 and 2014/15.
  • In all three years the percentage of teachers with a summative performance rating who were rated below proficient was higher among teachers age 50 and older than among teachers younger than age 50.
  • In all three years the difference in the percentage of male and female teachers with a summative performance rating who were rated below proficient was approximately 5 percentage points or less.
  • The percentage of teachers who improved their rating during all three year-to-year
    comparisons did not vary by race/ethnicity, age, or gender.

This is certainly something to (still) keep in consideration, especially when teachers are rewarded (e.g., via merit pay) or penalized (e.g., vie performance improvement plans or plans for dismissal). Basing these or other high-stakes decisions on not only subjective but also likely biased observational data (see, again, other studies evidencing that this is happening here and here), is not only unwise, it’s also possibly prejudiced.

While study authors note that their findings do not necessarily “explain why the
patterns exist or to what they may be attributed,” and that there is a “need
for further research on the potential causes of the gaps identified, as well as strategies for
ameliorating them,” for starters and at minimum, those conducting these observations literally across the country must be made aware.

Citation: Bailey, J., Bocala, C., Shakman, K., & Zweig, J. (2016). Teacher demographics and evaluation: A descriptive study in a large urban district. Washington DC: U.S. Department of Education. Retrieved from

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Miami-Dade, Florida’s Recent “Symbolic” and “Artificial” Teacher Evaluation Moves

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Last spring, Eduardo Porter – writer of the Economic Scene column for The New York Times – wrote an excellent article, from an economics perspective, about that which is happening with our current obsession in educational policy with “Grading Teachers by the Test” (see also my prior post about this article here; although you should give the article a full read; it’s well worth it). In short, though, Porter wrote about what economist’s often refer to as Goodhart’s Law, which states that “when a measure becomes the target, it can no longer be used as the measure.” This occurs given the great (e.g., high-stakes) value (mis)placed on any measure, and the distortion (i.e., in terms of artificial inflation or deflation, depending on the desired direction of the measure) that often-to-always comes about as a result.

Well, it’s happened again, this time in Miami-Dade, Florida, where the Miami-Dade district’s teachers are saying its now “getting harder to get a good evaluation” (see the full article here). Apparently, teachers evaluation scores, from last to this year, are being “dragged down,” primarily given teachers’ students’ performances on tests (as well as tests of subject areas that and students whom they do not teach).

“In the weeks after teacher evaluations for the 2015-16 school year were distributed, Miami-Dade teachers flooded social media with questions and complaints. Teachers reported similar stories of being evaluated based on test scores in subjects they don’t teach and not being able to get a clear explanation from school administrators. In dozens of Facebook posts, they described feeling confused, frustrated and worried. Teachers risk losing their jobs if they get a series of low evaluations, and some stand to gain pay raises and a bonus of up to $10,000 if they get top marks.”

As per the figure also included in this article, see the illustration of how this is occurring below; that is, how it is becoming more difficult for teachers to get “good” overall evaluation scores but also, and more importantly, how it is becoming more common for districts to simply set different cut scores to artificially increase teachers’ overall evaluation scores.

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“Miami-Dade say the problems with the evaluation system have been exacerbated this year as the number of points needed to get the “highly effective” and “effective” ratings has continued to increase. While it took 85 points on a scale of 100 to be rated a highly effective teacher for the 2011-12 school year, for example, it now takes 90.4.”

This, as mentioned prior, is something called “artificial deflation,” whereas the quality of teaching is likely not changing nearly to the extent the data might illustrate it is. Rather, what is happening behind the scenes (e.g., the manipulation of cut scores) is giving the impression that indeed the overall teacher system is in fact becoming better, more rigorous, aligning with policymakers’ “higher standards,” etc).

This is something in the educational policy arena that we also call “symbolic policies,” whereas nothing really instrumental or material is happening, and everything else is a facade, concealing a less pleasant or creditable reality that nothing, in fact, has changed.

Citation: Gurney, K. (2016). Teachers say it’s getting harder to get a good evaluation. The school district disagrees. The Miami Herald. Retrieved from

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Ohio Rejects Subpar VAM, for Another VAM Arguably Less Subpar?

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From a prior post coming from Ohio (see here), you may recall that Ohio state legislators recently introduced a bill to review its state’s value-added model (VAM), especially as it pertains to the state’s use of their VAM (i.e., the Education Value-Added Assessment System (EVAAS); see more information about the use of this model in Ohio here).

As per an article published last week in The Columbus Dispatch, the Ohio Department of Education (ODE) apparently rejected a proposal made by the state’s pro-charter school Ohio Coalition for Quality Education and the state’s largest online charter school, all of whom wanted to add (or replace) this state’s VAM with another, unnamed “Similar Students” measure (which could be the Student Growth Percentiles model discussed prior on this blog, for example, here, here, and here) used in California.

The ODE charged that this measure “would lower expectations for students with different backgrounds, such as those in poverty,” which is not often a common criticism of this model (if I have the model correct), nor is it a common criticism of the model they already have in place. In fact, and again if I have the model correct, these are really the only two models that do not statistically control for potentially biasing factors (e.g., student demographic and other background factors) when calculating teachers’ value-added; hence, their arguments about this model may be in actuality no different than that which they are already doing. Hence, statements like that made by Chris Woolard, senior executive director of the ODE, are false: “At the end of the day, our system right now has high expectations for all students. This (California model) violates that basic principle that we want all students to be able to succeed.”

The models, again if I am correct, are very much the same. While indeed the California measurement might in fact consider “student demographics such as poverty, mobility, disability and limited-English learners,” this model (if I am correct on the model) does not statistically factor these variables out. If anything, the state’s EVAAS system does, even though EVAAS modelers claim they do not do this, by statistically controlling for students’ prior performance, which (unfortunately) has these demographics already built into them. In essence, they are already doing the same thing they now protest.

Indeed, as per a statement made by Ron Adler, president of the Ohio Coalition for Quality Education, not only is it “disappointing that ODE spends so much time denying that poverty and mobility of students impedes their ability to generate academic performance…they [continue to] remain absolutely silent about the state’s broken report card and continually defend their value-added model that offers no transparency and creates wild swings for schools across Ohio” (i.e., the EVAAS system, although in all fairness all VAMs and the SGP yield the “wild swings’ noted). See, for example, here.

What might be worse, though, is that the ODE apparently found that, depending on the variables used in the California model, it produced different results. Guess what! All VAMs, depending on the variables used, produce different results. In fact, using the same data and different VAMs for the same teachers at the same time also produce (in some cases grossly) different results. The bottom line here is if any thinks that any VAM is yielding estimates from which valid or “true” statements can be made are fooling themselves.

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New Mexico: Holding Teachers Accountable for Missing More Than 3 Days of Work

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One state that seems to still be going strong after the passage of last January’s Every Student Succeeds Act (ESSA) — via which the federal government removed (or significantly relaxed) its former mandates that all states adopt and use of growth and value-added models (VAMs) to hold their teachers accountable (see here) — is New Mexico.

This should be of no surprise to followers of this blog, especially those who have not only recognized the decline in posts via this blog post ESSA (see a post about this decline here), but also those who have noted that “New Mexico” is the state most often mentioned in said posts post ESSA (see for example here, here, and here).

Well, apparently now (and post  revisions likely caused by the ongoing lawsuit regarding New Mexico’s teacher evaluation system, of which attendance is/was a part; see for example here, here, and here), teachers are to now also be penalized if missing more than three days of work.

As per a recent article in the Santa Fe New Mexican (here), and the title of this article, these new teacher attendance regulations, as to be factored into teachers’ performance evaluations, has clearly caught schools “off guard.”

“The state has said that including attendance in performance reviews helps reduce teacher absences, which saves money for districts and increases students’ learning time.” In fact, effective this calendar year, 5 percent of a teacher’s evaluation is to be made up of teacher attendance. New Mexico Public Education Department spokesman Robert McEntyre clarified that “teachers can miss up to three days of work without being penalized.” He added that “Since attendance was first included in teacher evaluations, it’s estimated that New Mexico schools are collectively saving $3.5 million in costs for substitute teachers and adding 300,000 hours of instructional time back into [their] classrooms.”

“The new guidelines also do not dock teachers for absences covered by the federal Family and Medical Leave Act, or absences because of military duty, jury duty, bereavement, religious leave or professional development programs.” Reported to me only anecdotally (i.e., I could not find evidence of this elsewhere), the new guidelines might also dock teachers for engaging in professional development or overseeing extracurricular events such as debate team performances. If anybody has anything to add on this end, especially as evidence of this, please do comment below.

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New Book: Student Growth Measures (SGMs) in Educational Policy and Practice

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Many of you might recall that just over two years ago my book titled “Rethinking Value-Added Models in Education: Critical Perspectives on Tests and Assessment-Based Accountability,” was officially released. Another book that I co-edited along with Kimberly Kappler-Hewitt — Assistant Professor at the University of North Carolina at Greensboro — was also just released.


For those of you who might be interested, within this new book — “Student Growth Measures in Policy and Practice: Intended and Unintended Consequences of High-Stakes Teacher Evaluations” — we along with 14 total chapter authors representing multiple states across the U.S. (e.g., Henry Braun, Sean Corcoran, Jonathan Eckert, Drew Gitomer, Michael Hansen, Jessica Holloway, Margaret Plecki, Benjamin Superfine) examine “the intersection of policy and practice in the use of student growth measures (SGMs [e.g., value-added models (VAMs)]) for high-stakes purposes as per such educator evaluation systems.” We also examine “educators’ perceptions of and reactions to the use of SGMs; ethical implications pertaining to the use of SGMs; contextual challenges when implementing SGMs; and legal implications of SGM use” pre and post the passage of the Every Student Succeeds Act (ESSA).

As we all know, pre and post ESSA, the use of student test score data has been the cornerstone of really the past decade’s transfiguration of teacher evaluation and accountability systems; hence, for those of you who might be interested, this book will hopefully be of “added value” in terms of our collective understandings about SGMs/VAMs use and applications, from policy to practice.

The book is 291 pages, 14 chapters, and it was published by Palgrave Macmillan, United Kingdom, at an (unfortunately high) cost of $94. For more information click here.

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New Mexico’s Mountains and Molehills

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“A Concerned New Mexico Parent” sent me another blog entry for you all to review. In this post (s)he explains and illustrates another statistical shenanigan the New Mexico Public Education Department (NMPED) recently pulled to promote the state’s value-added approach to reform (see this parent’s prior posts here and here).

(S)he writes:

The New Mexico Public Education Department (NMPED) should be ashamed of themselves.

In their explanation of the state’s NMTEACH teacher evaluation system, cutely titled “NMTEACH 101,” they present a PowerPoint slide that is numbing in it’s deceptiveness.

The entire presentation is available on their public website here (click on “NMTEACH101” under the “Teachers” heading at the top of the website to view the 34-slide presentation in its entirety).

Of particular interest to us, though, is the “proof” NMPED illustrates on slide 11 about the value of their value-added model (VAM) as related to students’ college-readiness. The slide is shown here:


Apparently we, as an unassuming public, are to believe that NMPED has longitudinal data showing how a VAM score from grades 3 through 12 (cor)relates to the percent of New Mexico students attending college at age 20. [This is highly unlikely, now also knowing a bit about this state’s data].

But even if we assume that such an unlikely longitudinal data set exists, we should still be disconcerted by the absolutely minimal effect of “Normalized Teacher Value Added” illustrated on the x-axis. This variable is clearly normalized so that each value represents a standard deviation (SD) with a range from -1.5 SD to + 1.5 SD — which represents a fairly significant range of values. In layman’s terms, this should cover the range from minimally effective to exemplary teachers.

So at first glance, the regression line (or slope) appears impressive. But after a second and more critical glance, we notice that the range of improvement is from roughly 36% to 37.8% — a decidedly and significantly much less impressive result.

In other words, by choosing to present and distort both the x- and y-axes this way, NMPED manages to make a statistical mountain out of what is literally a statistical molehill of change!

Shame on NMPED, again!

See prior posts about New Mexico, for example, here, as also related to the preliminary injunction already granted but also ongoing lawsuit, for example, here.

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Value-Added for Kindergarten Teachers in Ecuador

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In a study a colleague of mine recently sent me, authors of a study recently released in The Quarterly Journal of Economics and titled “Teacher Quality and Learning Outcomes in Kindergarten,” (nearly randomly) assigned two cohorts of more than 24,000 kindergarten students to teachers to examine whether, indeed and once again, teacher behaviors are related to growth in students’ test scores over time (i.e., value-added).

To assess this, researchers administered 12 tests to the Kindergarteners (I know) at the beginning and end of the year in mathematics and language arts (although apparently the 12 posttests only took 30-40 minutes to complete, which is a content validity and coverage issue in and of itself, p. 1424). They also assessed something they called the executive function (EF), and that they defined as children’s inhibitory control, working memory, capacity to pay attention, and cognitive flexibility, all of which they argue to be related to “Volumetric measures of prefrontal cortex size [when] predict[ed]” (p. 1424). This, along with the fact that teachers’ IQs were also measured (using the Spanish-speaking version of the Wechsler Adult Intelligence Scale) speaks directly to the researchers’ background theory and approach (e.g., recall our world’s history with craniometry, aptly captured in one of my favorite books — Stephen J. Gould’s best selling “The Mismeasure of Man”). Teachers were also observed using the Classroom Assessment Scoring System (CLASS), and parents were also solicited for their opinions about their children’s’ teachers (see other measures collected p. 1417-1418).

What should by now be some familiar names (e.g., Raj Chetty, Thomas Kane) served as collaborators on the study. Likewise, their works and the works of other likely familiar scholars and notorious value-added supporters (e.g., Eric Hanushek, Jonah Rockoff) are also cited throughout in support as evidence of “substantial research” (p. 1416) in support of value-added models (VAMs). Of course, this is unfortunate but important to point out in that this is an indicator of “researcher bias” in and of itself. For example, one of the authors’ findings really should come at no surprise: “Our results…complement estimates from [Thomas Kane’s Bill & Melinda Gates Measures of Effective Teaching] MET project” (p. 1419); although, the authors in a very interesting footnote (p. 1419) describe in more detail than I’ve seen elsewhere all of the weaknesses with the MET study in terms of its design, “substantial attrition,” “serious issue[s]” with contamination and compliance, and possibly/likely biased findings caused by self-selection given the extent to which teachers volunteered to be a part of the MET study.

Also very important to note is that this study took place in Ecuador. Apparently, “they,” including some of the key players in this area of research noted above, are moving their VAM-based efforts across international waters, perhaps in part given the Every Student Succeeds Act (ESSA) recently passed in the U.S., that we should all know by now dramatically curbed federal efforts akin to what is apparently going on now and being pushed here and in other developing countries (although the authors assert that Ecuador is a middle-income country, not a developing country, even though this categorization apparently only applies to the petroleum rich sections of the nation). Related, they assert that, “concerns about teacher quality are likely to be just as important in [other] developing countries” (p. 1416); hence, adopting VAMs in such countries might just be precisely what these countries need to “reform” their schools, as well.

Unfortunately, many big businesses and banks (e.g., the Inter-American Development Bank that funded this particular study) are becoming increasingly interested in investing in and solving these and other developing countries’ educational woes, as well, via measuring and holding teachers accountable for teacher-level value-added, regardless of the extent to which doing this has not worked in the U.S to improve much of anything. Needless to say, many who are involved with these developing nation initiatives, including some of those mentioned above, are also financially benefitting by continuing to serve others their proverbial Kool-Aid.

Nonetheless, their findings:

  • First, they “estimate teacher (rather than classroom) effects of 0.09 on language and math” (p. 1434). That is, just less than 1/10th of a standard deviation, or just over a 3% move in the positive direction away from the mean.
  • Similarly, the “estimate classroom effects of 0.07 standard deviation on EF” (p. 1433). That is, precisely 7/100th of a standard deviation, or about a 2% move in the positive direction away from the mean.
  • They found that “children assigned to teachers with a 1-standard deviation higher CLASS score have between 0.05 and 0.07 standard deviation higher end-of-year test scores” (p. 1437), or a 1-2% move in the positive direction away from the mean.
  • And they found that “that parents generally give higher scores to better teachers…parents are 15 percentage points more likely to classify a teacher who produces 1 standard deviation higher test scores as ‘‘very good’’ rather than ‘‘good’’ or lower” (p. 1442). This is quite an odd way of putting it, along with the assumption that the difference between “very good” and “good” is not arbitrary but empirically grounded, along with whatever reason a simple correlation was not more simply reported.
  • Their most major finding is that “a 1 standard deviation increase in classroom quality, corrected for sampling error, results in 0.11 standard deviation higher test scores in both language and math” (p. 1433; see also other findings from p. 1434-447).

Interestingly, the authors equivocate all of these effects to teacher or classroom “shocks,” although I’d hardly call them “shocks” that inherently imply a large, unidirectional, and causal impact. Moreover, this also implies how the authors, also as economists, still view this type of research (i.e., not correlational, even with close-to-random assignment, although they make a slight mention of this possibility on p. 1449).

Nonetheless, the authors conclude that in this article they effectively evidenced “that there are substantial differences [emphasis added] in the amount of learning that takes place in language, math, and executive function across kindergarten classrooms in Ecuador” (p. 1448). In addition, “These differences are associated with differences in teacher behaviors and practices,” as observed, and “that parents can generally tell better from worse teachers, but do not meaningfully alter their investments in children in response to random shocks [emphasis added] to teacher quality” (p. 1448).

Ultimately, they find that “value added is a useful summary measure of teacher quality in Ecuador” (p. 1448). Go figure…

They conclude “to date, no country in Latin America regularly calculates the value added of teachers,” yet “in virtually all countries in the region, decisions about tenure, in-service training, promotion, pay, and early retirement are taken with no regard for (and in most cases no knowledge about) a teacher’s effectiveness” (p. 1448). Also sound familiar??

“Value added is no silver bullet,” and indeed it is not as per much evidence now existent throughout the U.S., “but knowing which teachers produce more or less learning among equivalent students [is] an important step to designing policies to improve learning outcomes” (p. 1448), they also recognizably argue.

Citation: Araujo, M. C., Carneiro, P.,  Cruz-Aguayo, Y., & Schady, N. (2016). Teacher quality and learning outcomes in Kindergarten. The Quarterly Journal of Economics, 1415–1453. doi:10.1093/qje/qjw016  Retrieved from

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