New Mexico Lawsuit Update

The ongoing lawsuit in New Mexico has, once again (see here and here), been postponed to October of 2017 due to what are largely (and pretty much only) state (i.e., Public Education Department (PED)) delays. Whether the delays are deliberate are uncertain but being involved in this case… The (still) good news is that the preliminary injunction granted to teachers last fall (see here) still holds so that teachers cannot (or are not to) face consequences as based on the state’s teacher evaluation system.

For more information, this is the email the American Federation of Teachers – New Mexico (AFT NM) and the Albuquerque Teachers Federation (ATF) sent out to all of their members yesterday:

Yesterday, both AFT NM/ATF and PED returned to court to address the ongoing legal battle against the PED evaluation system. Our lawyer proposed that we set a court date ASAP. The PED requested a date for next fall citing their busy schedule as the reason. As a result, the court date is now late October 2017.

While we are relieved to have a final court date set, we are dismayed at the amount of time that our teachers have to wait for the final ruling.

In a statement to the press, ATF President Ellen Bernstein reflected on the current state of our teachers in regards to the evaluation system, “Even though they know they can’t be harmed in their jobs right now, it bothers them in the core of their being, and nothing I can say can take that away…It’s a cloud over everybody.”

AFT NM President Stephanie Ly, said, “It is a shame our educators still don’t have a legitimate evaluation system. The PED’s previous abusive evaluation system was thankfully halted through an injunction by the New Mexico courts, and the PED has yet to create an evaluation system that uniformly and fairly evaluates educators, and have shown no signs to remedy this situation. The PED’s actions are beyond the pale, and it is simply unjust.”

While we await trial, we want to thank our members who sent in their evaluation data to help our case. Remind your colleagues that they may still advance in licensure by completing a dossier; the PED’s arbitrary rating system cannot negatively affect a teacher’s ability to advance thanks to the injunction won by AFT NM/ATF last fall. That injunction will stay in place until a ruling is issued on our case next October.

In Solidarity,

Stephanie Ly

Bias in Teacher Observations, As Well

Following a post last month titled “New Empirical Evidence: Students’ ‘Persistent Economic Disadvantage’ More Likely to Bias Value-Added Estimates,” Matt Barnum — senior staff writer for The 74, an (allegedly) non-partisan, honest, and fact-based news site backed by Editor-in-Chief Campbell Brown and covering America’s education system “in crisis” (see, also, a prior post about The 74 here) — followed up with a tweet via Twitter. He wrote: “Yes, though [bias caused by economic disadvantage] likely applies with equal or even more force to other measures of teacher quality, like observations.” I replied via Twitter that I disagreed with this statement in that I was unaware of research in support of his assertion, and Barnum sent me two articles to review thereafter.

I attempted to review both of these articles herein, although I quickly figured out that I had actually read and reviewed the first (2014) piece on this blog (see original post here, see also a 2014 Brookings Institution article summarizing this piece here). In short, in this study researchers found that the observational components of states’ contemporary teacher systems certainly “add” more “value” than their value-added counterparts, especially for (in)formative purposes. However, researchers  found that observational bias also exists, as akin to value-added bias, whereas teachers who are non-randomly assigned students who enter their classrooms with higher levels of prior achievement tend to get higher observational scores than teachers non-randomly assigned students entering their classrooms with lower levels of prior achievement. Researchers concluded that because districts “do not have processes in place to address the possible biases in observational scores,” statistical adjustments might be made to offset said bias, as might external observers/raters be brought in to yield more “objective” observational assessments of teachers.

For the second study, and this post here, I gave this one a more thorough read (you can find the full study, pre-publication here). Using data from the Measures of Effective
Teaching (MET) Project, in which random assignment was used (or more accurately attempted), researchers also explored the extent to which students enrolled in teachers’ classrooms influence classroom observational scores.

They found, primarily, that:

  1. “[T]he context in which teachers work—most notably, the incoming academic performance of their students—plays a critical role in determining teachers’ performance” as measured by teacher observations. More specifically, “ELA [English/language arts] teachers were more than twice as likely to be rated in the top performance quintile if [nearly randomly] assigned the highest achieving students compared with teachers assigned the low-est achieving students,” and “math teachers were more than 6 times as likely.” In addition, “approximately half of the teachers—48% in ELA and 54% in math—were rated in the top two performance quintiles if assigned the highest performing students, while 37% of ELA and only 18% of math teachers assigned the lowest performing students were highly rated based on classroom observation scores”
  2. “[T]he intentional sorting of teachers to students has a significant influence on measured performance” as well. More specifically, results further suggest that “higher performing students [are, at least sometimes] endogenously sorted into the classes of higher performing teachers…Therefore, the nonrandom and positive assignment of teachers to classes of students based on time-invariant (and unobserved) teacher
    characteristics would reveal more effective teacher performance, as measured by classroom observation scores, than may actually be true.”

So, the non-random assignment of teachers biases both the value-added and observational components written into America’s now “more objective” teacher evaluation systems, as (formerly) required of all states that were to comply with federal initiatives and incentives (e.g., Race to the Top). In addition, when those responsible for assigning students to classrooms (sub)consciously favor teachers with high, prior observational scores, this exacerbates the issues. This is especially important when observational (and value-added) data are to be used for high-stakes accountability systems in that the data yielded via really both measurement systems may be less likely to reflect “true” teaching effectiveness due to “true” bias. “Indeed, teachers working with higher achieving students tend to receive higher performance ratings, above and beyond that which might be attributable to aspects of teacher quality,” and vice-versa.

Citation Study #1: Whitehurst, G. J., Chingos, M. M., & Lindquist, K. M. (2014). Evaluating teachers with classroom observations: Lessons learned in four districts. Washington, DC: Brookings Institution. Retrieved from https://www.brookings.edu/wp-content/uploads/2016/06/Evaluating-Teachers-with-Classroom-Observations.pdf

Citation Study #2: Steinberg, M. P., & Garrett, R. (2016). Classroom composition and measured teacher performance: What do teacher observation scores really measure? Educational Evaluation and Policy Analysis, 38(2), 293-317. doi:10.3102/0162373715616249  Retrieved from http://static.politico.com/58/5f/f14b2b144846a9b3365b8f2b0897/study-of-classroom-observations-of-teachers.pdf

 

The “Value-Added” of Teacher Preparation Programs: New Research

The journal Education of Economics Review recently published a study titled “Teacher Quality Differences Between Teacher Preparation Programs: How Big? How Reliable? Which Programs Are Different?” The study was authored by researchers at the University of Texas – Austin, Duke University, and Tulane. The pre-publication version of this piece can be found here.

As the title implies, the purpose of the study was to “evaluate statistical methods for estimating teacher quality differences between TPPs [teacher preparation programs].” Needless to say, this research is particularly relevant, here, given “Sixteen US states have begun to hold teacher preparation programs (TPPs) accountable for teacher quality, where quality is estimated by teacher value-added to student test scores.” The federal government continues to support and advance these initiatives, as well (see, for example, here).

But this research study is also particularly important because while researchers found that “[t]he most convincing estimates [of TPP quality] [came] from a value-added model where confidence intervals [were] widened;” that is, the extent to which measurement errors were permitted was dramatically increased, and also widened further using statistical corrections. But even when using these statistical techniques and accomodations, they found that it was still “rarely possible to tell which TPPs, if any, [were] better or worse than average.”

They therefore concluded that “[t]he potential benefits of TPP accountability may be too small to balance the risk that a proliferation of noisy TPP estimates will encourage arbitrary and ineffective policy actions” in response. More specifically, and in their own words, they found that:

  1. Differences between TPPs. While most of [their] results suggest that real differences between TPPs exist, the differences [were] not large [or large enough to make or evidence the differentiation between programs as conceptualized and expected]. [Their] estimates var[ied] a bit with their statistical methods, but averaging across plausible methods [they] conclude[d] that between TPPs the heterogeneity [standard deviation (SD) was] about .03 in math and .02 in reading. That is, a 1 SD increase in TPP quality predict[ed] just [emphasis added] a [very small] .03 SD increase in student math scores and a [very small] .02 SD increase in student reading scores.
  2. Reliability of TPP estimates. Even if the [above-mentioned] differences between TPPs were large enough to be of policy interest, accountability could only work if TPP differences could be estimated reliably. And [their] results raise doubts that they can. Every plausible analysis that [they] conducted suggested that TPP estimates consist[ed] mostly of noise. In some analyses, TPP estimates appeared to be about 50% noise; in other analyses, they appeared to be as much as 80% or 90% noise…Even in large TPPs the estimates were mostly noise [although]…[i]t is plausible [although perhaps not probable]…that TPP estimates would be more reliable if [researchers] had more than one year of data…[although states smaller than the one in this study — Texs]…would require 5 years to accumulate the amount of data that [they used] from one year of data.
  3. Notably Different TPPs. Even if [they] focus[ed] on estimates from a single model, it remains hard to identify which TPPs differ from the average…[Again,] TPP differences are small and estimates of them are uncertain.

In conclusion, that researchers found “that there are only small teacher quality differences between TPPs” might seem surprising, but not really given the outcome variables they used to measure and assess TPP effects were students’ test scores. In short, students’ test scores are three times removed from the primary unit of analysis in studies like these. That is, (1) the TPP is to be measured by the effectiveness of its teacher graduates, and (2) teacher graduates are to be measured by their purported impacts on their students’ test scores, while (3) students’ test scores are to only and have only been validated for measuring student learning and achievement. These test scores have not been validated to assess and measure, in the inverse, teachers causal impacts on said achievements or on TPPs impacts on teachers on said achievements.

If this sounds confusing, it is, and also highly nonsensical, but this is also a reason why this is so difficult to do, and as evidenced in this study, improbable to do this well or as theorized in that TPP estimates are sensitive to error, insensitive given error, and, accordingly, highly uncertain and invalid.

Citation: von Hippela, P. T., Bellowsb, L., Osbornea, C., Lincovec, J. A., & Millsd, N. (2016). Teacher quality differences between teacher preparation programs: How big? How reliable? Which programs are different? Education of Economics Review, 53, 31–45. doi:10.1016/j.econedurev.2016.05.002

VAM-Based Chaos Reigns in Florida, as Caused by State-Mandated Teacher Turnovers

The state of Florida is another one of our state’s to watch in that, even since the passage of the Every Student Succeeds Act (ESSA) last January, the state is still moving forward with using its VAMs for high-stakes accountability reform. See my most recent post about one district in Florida here, after the state ordered it to dismiss a good number of its teachers as per their low VAM scores when this school year started. After realizing this also caused or contributed to a teacher shortage in the district, the district scrambled to hire Kelly Services contracted substitute teachers to replace them, after which the district also put administrators back into the classroom to help alleviate the bad situation turned worse.

In a recent post released by The Ledger, teachers from the same Polk County School District (size = 100K students) added much needed details and also voiced concerns about all of this in the article that author Madison Fantozzi titled “Polk teachers: We are more than value-added model scores.”

Throughout this piece Fantozzi covers the story of Elizabeth Keep, a teacher who was “plucked from” the middle school in which she taught for 13 years, after which she was involuntarily placed at a district high school “just days before she was to report back to work.” She was one of 35 teachers moved from five schools in need of reform as based on schools’ value-added scores, although this was clearly done with no real concern or regard of the disruption this would cause these teachers, not to mention the students on the exiting and receiving ends. Likewise, and according to Keep, “If you asked students what they need, they wouldn’t say a teacher with a high VAM score…They need consistency and stability.” Apparently not. In Keep’s case, she “went from being the second most experienced person in [her middle school’s English] department…where she was department chair and oversaw the gifted program, to a [new, and never before] 10th- and 11th-grade English teacher” at the new high school to which she was moved.

As background, when Polk County School District officials presented turnaround plans to the State Board of Education last July, school board members “were most critical of their inability to move ‘unsatisfactory’ teachers out of the schools and ‘effective’ teachers in.”  One board member, for example, expressed finding it “horrendous” that the district was “held hostage” by the extent to which the local union was protecting teachers from being moved as per their value-added scores. Referring to the union, and its interference in this “reform,” he accused the unions of “shackling” the districts and preventing its intended reforms. Note that the “effective” teachers who are to replace the “ineffective” ones can earn up to $7,500 in bonuses per year to help the “turnaround” the schools into which they enter.

Likewise, the state’s Commissioner of Education concurred saying that she also “wanted ‘unsatisfactory’ teachers out and ‘highly effective’ teachers in,” again, with effectiveness being defined by teachers’ value-added or lack thereof, even though (1) the teachers targeted only had one or two years of the three years of value-added data required by state statute, and even though (2) the district’s senior director of assessment, accountability and evaluation noted that, in line with a plethora of other research findings, teachers being evaluated using the state’s VAM have a 51% chance of changing their scores from one year to the next. This lack of reliability, as we know it, should outright prevent any such moves in that without some level of stability, valid inferences from which valid decisions are to be made cannot be drawn. It’s literally impossible.

Nonetheless, state board of education members “unanimously… threatened to take [all of the district’s poor performing] over or close them in 2017-18 if district officials [didn’t] do what [the Board said].” See also other tales of similar districts in the article available, again, here.

In Keep’s case, “her ‘unsatisfactory’ VAM score [that caused the district to move her, as] paired with her ‘highly effective’ in-class observations by her administrators brought her overall district evaluation to ‘effective’…[although she also notes that]…her VAM scores fluctuate because the state has created a moving target.” Regardless, Keep was notified “five days before teachers were due back to their assigned schools Aug. 8 [after which she was] told she had to report to a new school with a different start time that [also] disrupted her 13-year routine and family that shares one car.”

VAM-based chaos reigns, especially in Florida.

U.S. Department of Education: Value-Added Not Good for Evaluating Schools and Principals

Just this month, the Institute of Education Sciences (IES) wing of the U.S. Department of Education released a report about using value-added models (VAMs) for measuring school principals’ performance. The article conducted by researchers at Mathematica Policy Research and titled “Can Student Test Scores Provide Useful Measures of School Principals’ Performance?” can be found online here, with my summary of the study findings highlighted next and herein.

Before the passage of the Every Student Succeeds Act (ESSA), 40 states had written into their state statutes, as incentivized by the federal government, to use growth in student achievement growth for annual principal evaluation purposes. More states had written growth/value-added models (VAMs) for teacher evaluation purposes, which we have covered extensively via this blog, but this pertains only to school and/or principal evaluation purposes. Now since the passage of ESSA, and the reduction in the federal government’s control over state-level policies, states now have much more liberty to more freely decide whether to continue using student achievement growth for either purposes. This paper is positioned within this reasoning, and more specifically to help states decide whether or to what extent they might (or might not) continue to move forward with using growth/VAMs for school and principal evaluation purposes.

Researchers, more specifically, assessed (1) reliability – or the consistency or stability of these ratings over time, which is important “because only stable parts of a rating have the potential to contain information about principals’ future performance; unstable parts reflect only transient aspects of their performance;” and (2) one form of multiple evidences of validity – the predictive validity of these principal-level measures, with predictive validity defined as “the extent to which ratings from these measures accurately reflect principals’ contributions to student achievement in future years.” In short, “A measure could have high predictive validity only if [emphasis added] it was highly stable between consecutive years [i.e., reliability]…and its stable part was strongly related to principals’ contributions to student achievement” over time (i.e., predictive validity).

Researchers used principal-level value-added (unadjusted and adjusted for prior achievement and other potentially biasing demographic variables) to more directly examine “the extent to which student achievement growth at a school differed from average growth statewide for students with similar prior achievement and background characteristics.” Also important to note is that the data they used to examine school-level value-added came from Pennsylvania, which is one of a handful of states that uses the popular and proprietary (and controversial) Education Value-Added Assessment System (EVAAS) statewide.

Here are the researchers’ key findings, taken directly from the study’s summary (again, for more information see the full manuscript here).

  • The two performance measures in this study that did not account for students’ past achievement—average achievement and adjusted average achievement—provided no information for predicting principals’ contributions to student achievement in the following year.
  • The two performance measures in this study that accounted for students’ past achievement—school value-added and adjusted school value-added—provided, at most, a small amount of information for predicting principals’ contributions to student achievement in the following year. This was due to instability and inaccuracy in the stable parts.
  • Averaging performance measures across multiple recent years did not improve their accuracy for predicting principals’ contributions to student achievement in the following year. In simpler terms, a principal’s average rating over three years did not predict his or her future contributions more accurately than did a rating from the most recent year only. This is more of a statistical finding than one that has direct implications for policy and practice (except for silly states who might, despite findings like those presented in this study, decide that they can use one year to do this not at all well instead of three years to do this not at all well).

Their bottom line? “…no available measures of principal [/school] performance have yet been shown to accurately identify principals [/schools] who will contribute successfully to student outcomes in future years,” especially if based on students’ test scores, although the researchers also assert that “no research has ever determined whether non-test measures, such as measures of principals’ leadership practices, [have successfully or accurately] predict[ed] their future contributions” either.

The researchers follow-up with a highly cautionary note: “the value-added measures will make plenty of mistakes when trying to identify principals [/schools] who will contribute effectively or ineffectively to student achievement in future years. Therefore, states and districts should exercise caution when using these measures to make major decisions about principals. Given the inaccuracy of the test-based measures, state and district leaders and researchers should also make every effort to identify nontest measures that can predict principals’ future contributions to student outcomes [instead].”

Citation: Chiang, H., McCullough, M., Lipscomb, S., & Gill, B. (2016). Can student test scores provide useful measures of school principals’ performance? Washington DC: U.S. Department of Education, Institute of Education Sciences. Retrieved from http://ies.ed.gov/ncee/pubs/2016002/pdf/2016002.pdf