Designing High Quality Evaluation Systems for High School Teachers

8/3/2019 Designing High Quality Evaluation Systems for High School Teachers

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Designing High Quality EvaluationSystems for High School TeachersChallenges and Potential Solutions

John H. Tyler November 2011


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Designing High QualityEvaluation Systems for HighSchool TeachersChallenges and Potential Solutions

John H. Tyler November 2011



Contents 1 Introduction and summary

5 Practice-based teacher evaluation

8 Practice-based evaluation in high school

13 Using student performance measures to evaluate teach

17 Evaluating high school teachers based on student performance:

Challenges and solutions

23 Other student performance measures

27 Conclusion

31 About the author and acknowledgements

32 Endnotes

35 References



1 Cr r Amrica Prgr | Digig hig Quaiy eauai sym r hig sc tacr

Introduction and summary

A cenral par o educaion reorm oday is he wide-ranging and unprecedened

eor o eiher revamp exising eacher evaluaion sysems or develop and imple-

men enirely new sysems. In he pas hree years, or example, 32 saes and he

Disric o Columbia have made some change o heir sae eacher evaluaion

policy, and 23 saes currenly require ha eacher evaluaions include objecive

evidence o suden learning, up rom only our saes in 2009.1 Te success o his

work will in large par be judged by he exen o which he resuling sysems can

evaluae eachers wih rigor, objeciviy, and in ways ha diereniae eachers’abiliies o promoe suden learning.

Meeing his high bar in our naion’s high schools poses especially dicul chal-

lenges, and ye he sakes or doing so are enormous, a poin brough home by he

exan research. One paricular srand o research ocuses atenion o he impor-

ance o ideniying and addressing eacher eeciveness within schools , where he

bulk o he variaion in eacher eeciveness resides.2 A he same ime, research

indicaes a clear and urgen need o accomplish his ask in our naion’s high schools.

Te argumen or ocusing atenion a he high school level is hree-pronged.

Firs, he perormance o high school sudens lags behind ha o demographically

similar sudens in he elemenary and middle grades, which suggess ha, relaive

o he earlier years, here is a heighened need or improving he qualiy o insruc-

ion in high school.3 Second, dropou decisions are made by sudens in heir high

school years, which means improving average eacher qualiy in high school is

one poenial avenue or addressing he subbornly persisen dropou rae. Te

research-based linkage is ha suden engagemen is relaed o dropping ou and

eachers’ behaviors and pracices are, in urn, relaed o suden engagemen.4

Tird, high school is our las line o deense or preparing sudens or college and

he world o work—and eachers are an obviously criical componen o he qual-

iy o ha preparaion. Sudens enering college lacking a solid high school educa-




ion oen have o spend ime in remedial college courses, a siderack associaed

wih ewer earned credis and a lower likelihood o graduaing wih a degree.5 In

erms o labor marke consequences, young people who ener oday’s labor orce

wihou basic academic skills, he abiliy o hink criically and creaively, and who

are decien in so-called “noncogniive” skills are a a compeiive disadvanage in

he global, inormaion-age economy.6

High-qualiy eacher evaluaion sysems are seen as one lever or improving he

eacher workorce and hence he oucomes o sudens, including high school su-

dens. Te curren degree o consensus around eors o improve eacher evalua-

ion is sriking or he world o kindergaren-hrough-12h-grade educaion. From

radiionally conservaive educaion observers and aciviss o eachers’ union

leaders, rom proessional educaion organizaions o philanhropic oundaions,

and rom he U.S. Deparmen o Educaion o local educaion agencies, a wide

array o individuals, groups, and organizaions are involved and oen cooperaing

in eors o suppor he design, esing, and implemenaion o he nex genera-ion o eacher evaluaion sysems.7

On he public side he U.S. Deparmen o Educaion made eacher evalua-

ion an inegral par o he Obama adminisraion’s $4.3 billion Race o he op

compeiive gran iniiaive designed o encourage and reward saes ha are

creaing he condiions or educaion innovaion and reorm. Meanwhile, in he

nonpro arena some o he naion’s mos prominen oundaions are reallocaing

gran money oward eacher evaluaion iniiaives, one example o which is he

Bill & Melinda Gaes Foundaion invesmen o $290 million in our “inensive

parnership” sies o suppor eacher eeciveness iniiaives ha include eacher

evaluaion and anoher $45 million in he Measures o Eecive eaching, or

ME, projec, a wo-year eor o develop mehods and ools or ideniying and

developing good eaching.

As he various eacher evaluaion iniiaives move orward over he coming years,

how hey play ou will likely be shaped by a simple bu imporan conexual

realiy. While here is wide agreemen abou he need or new and beter ways o

evaluae eachers, dieren sakeholders place dieren emphases on wha hey

ulimaely wan rom evaluaion sysems. Some see eacher evaluaion as a way o ideniy and remove low-perorming eachers. Ohers view eacher evaluaion

as he cornersone o new perormance-based eacher compensaion sysems.

Sill ohers hink ha he emphasis should be on evaluaion as a mechanism or

improving eaching pracice, a way o help eachers ge beter. A he end o he




day, however, he exen o which any o his can happen ress on evaluaion ha can

consisenly deermine who are he more and less eecive eachers in our classrooms.

Inormaion o accomplish his comes rom wo sources. Firs, we can use eacher-

relaed inputs o he educaion process, such as classroom eaching observaions or

classroom ariacs such as lesson plans and eacher-designed suden assessmens.From hese pracice-based measures, we make inerences abou a eacher’s abiliy

o promoe suden learning. Second, we can measure outputs rom he eaching-

learning process—acual suden perormance—and, based on hese measures,

make inerences abou he eacher’s conribuion o ha oupu. In each case

doing his well or high school eachers is a challenge.

In erms o pracice-based measures o eeciveness, he many conen areas ha

are covered in a ypical comprehensive high school make i impossible or all

eachers o be observed and evaluaed by individuals who have raining in he

eacher’s conen area. Tis no only poenially compromises he validiy and reli-abiliy o he evaluaion resuls; i decreases he likelihood ha eachers will buy

ino and suppor he evaluaion sysem.

Likewise, he diculies in using suden perormance daa o evaluae high

school eachers begins wih he ac ha hese eachers rarely each in grades or

subjecs where sudens have had comparable pre- and pos-ess ha can be used

o consruc prooypical value-added measures or he eacher. Anoher issue

in using value-added measures a he high school level is ha, unlike he case or

elemenary sudens, we have o worry abou he ac ha sudens in, say, an 11h-

grade English course ook dieren pahs o ge o ha course.

I hese dieren pahs aec heir oucomes, hen value-added models ha do

no accoun or his “pah dependence” may no accuraely esimae he eacher o

record’s conribuion o suden learning. A similar problem is presen i each-

ers aec learning across courses in a given year. Failure o accoun or his kind

o “cross-erilizaion” would again call ino quesion value-added measures o

eacher eeciveness.

Tus, here are clear challenges o eecively evaluaing high school eachers.Neverheless, saes and school disrics across he naion are conroning hese

challenges and in he process soluions are emerging. A preview o he poenial

soluions ha he analysis in his paper suggess may be employed in building

opimum evaluaion sysems or high school eachers includes:




•Developing new and enhancing exising assessmens ha es high school each-

ers’ conen-based pedagogical knowledge•Exploring, developing, and esing he increased use o echnology such as

classroom video recording as a means or generaing eciency and produciviy

gains in pracice-based evaluaion•

Conducing more research on he properies and use o Suden LearningObjecives, or SLOs, as a measure o eecive eaching based on suden

perormance•Coninuing invesigaions ino how value-added measures can be eecively

used a he high school level•Finding he bes ways o incorporae all available inormaion rom boh

pracice-based measures and suden perormance daa ino he ulimae

evaluaion o eachers

Tis paper examines he challenges and poenial soluions o evaluaing high school

eachers, looking rs a pracice-based evaluaion and hen urning o suden peror-mance as he basis or evaluaion. In each case he sage is rs se wih a brie discus-

sion o he overarching, across-grade issues ha accompany each mehod.

In reviewing he issues a hand, i is imporan o keep in mind ha hese wo

models o evaluaion, pracice-based and suden-perormance-based evaluaion,

make inerences based on dieren poins in he educaion process—inpu versus

oupu, and hey rely on dieren kinds o daa—qualiaive and more subjecive

versus quaniaive and objecive. And hey are a dieren sages o developmen-

al evoluion—well-esablished or many years (hough evolving) or pracice-

based evaluaion versus rapid developmens over he las 10 years in using suden

perormance daa or evaluaion. Neverheless, he early evidence is ha mos new

evaluaion sysems will be characerized by some combinaion o boh o hese

mehods o evaluae eachers, including high school eachers.




Practice-based teacher evaluation

Pracice-based eacher evaluaion reers o he use o inormaion rom various

aspecs o a eacher’s pracice in evaluaing eacher eeciveness. Pracice-based

inormaion on eacher eeciveness can come rom:

• Classroom observaions• eacher-produced ariacs such as lesson plans, eacher-designed suden

assessmens, and porolios• Evidence o how a eacher works wih colleagues and adminisraors• Communicaions wih parens• Proessional developmen aciviies• Oher evidence o a eacher’s proessional aciviies

O hese elemens, classroom observaions o he eacher a work are arguably he

mos direc evidence o a eacher’s abiliy o aec suden learning. Tis would

sugges ha evaluaion ha uses some or all o he above componens should give

classroom observaions he mos weigh in compuing a nal summaive score or

a eacher. Unorunaely, here is litle inormaion regarding how disrics cur-

renly weigh he dieren measures when hey combine hem ino a summaive

evaluaion score or he eacher.8

An imporan eaure o pracice-based evaluaion o bear in mind is ha i is

based on inpu measures ino he eaching-learning process raher han oupu

measures direcly associaed wih suden learning and achievemen. Te argu-

men or inpu-based evaluaion is ha eachers are evaluaed on pracices ha

educaion expers believe o be relaed o suden learning, an argumen ha has

less resonance in oday’s environmen o educaion accounabiliy han i migh

once have had. Tere are hree pracice-based evaluaion proocols ha have beenlinked o suden achievemen growh bu he grea majoriy o disrics use evalu-

aion proocols ha have no been validaed agains suden achievemen gains.9




Unil very recenly, pracice-based measures were he only available means in

mos disrics or evaluaing eachers, and while a small handul o disrics are

beginning o incorporae oupu measures ino evaluaion sysems, using inpu

measures o eachers’ pracice is sill he way ha virually all disrics currenly

judge eacher eeciveness.10 In mos disrics he responsibiliies associaed

wih carrying ou pracice-based evaluaion lie wih building principals, assisanprincipals, curriculum heads, and oher school-level adminisraors.11 A major par

o heir evaluaion responsibiliies is conducing he classroom observaions o

eachers, a ime-inensive process. Te insrumens used o guide he evaluaion

process—he assessmen orms, perormance crieria, and evaluaion proce-

dures—are largely creaed by he disrics, a process ha leads, no surprisingly,

o considerable variaion across disrics in he srucure, use, and likely qualiy o

he evaluaion.12 Some o he problems wih principal-led evaluaions, in paricular

he endency o rae eachers higher on he evaluaions han is likely warraned,

so-called “leniency bias,” are deailed in a 1997 paper by Pamela D. ucker, where

principals inormally idenied 5 percen o heir insrucional sa as being“incompeen” bu gave only 1 percen ormal raings his low.13

Leniency bias on he par o principals is no a problem unique o evaluaions o

eachers ha come rom principal-led evaluaions.14 “Te Widge Eec,” a 2009

sudy by Te New eacher Projec o 12 disrics ha are considered o have some

o he mos well-developed evaluaion sysems in he naion, including sysems

ha uilize rained evaluaors or classroom observaions and oher aciviies,

replicaed ucker’s resuls o a decade earlier. Among he 12 disrics ha uilized

a binary raing sysem or eachers, 99 percen o he eachers received he high-

es raing. Meanwhile, in hose disrics ha uilized a our-poin raing scale, 94

percen o he eachers received one o he op wo raings, and less han 1 percen

were raed a he lowes level.15 O course, he problem wih his is ha when viru-

ally all o he eachers receive he highes scores, an evaluaion sysem oregoes he

opporuniy o meaningully diereniae eacher eeciveness in ways ha could

provide valuable inormaion o he disric and o eachers in need o assisance.

In addiion o he ailure o use exising evaluaion o diereniae among he

variaion in eacher eeciveness wihin schools ha research consisenly veri-

es, anoher issue is ha high-qualiy pracice-based evaluaion can be relaively cosly. Te Cincinnai school disric, or example, which is widely recognized as

having one o he bes evaluaion sysems in he counry, allocaed beween $1.8

million and $2.1 million per year or eacher evaluaion beween he 2004-05 and

2009-10 school years.16 Tis ranslaes ino abou $7,500 per eacher or each o




he approximaely 250 eachers who underwen a comprehensive evaluaion each

year.17 Approximaely 90 percen o his cos is atribuable o he salaries o he

12-15 maser eachers who leave he classroom or hree years o serve as rained

evaluaors in he Cincinnai sysem.18

While issues ha poenially compromise or complicae he use o pracice-basedevaluaion ge maniesed a he high school level, so oo do he advanages o using

pracice-based evaluaion. In paricular, when done well, pracice-based evaluaion

can provide inormaion o eachers and adminisraors regarding wha good each-

ers are doing well, and hereore could be shared wih colleagues, and wha srug-

gling eachers are ailing o do well and need assisance o improve. Also,

advocaes o pracice-based evaluaion sugges ha because he rubrics agains

which a eacher’s pracice will be judged are known and available in public docu-

mens, discussion around hese explici eaching pracices can oser dialogue in a

school and a disric around wha good eaching looks like. In his case he evalua-

ion sysem can change he discussion around eaching. I is also he case ha each-ers and eachers’ unions, including high school eachers, end o be more supporive

o pracice-based evaluaions relaive o evaluaions based on suden es scores.

Finally, here is emerging evidence rom a Cincinnai-based sudy by Eric S. aylor

and John H. yler ha suggess well-designed pracice-based evaluaion can help a

eacher ge beter.19 Linking 10 years o daa rom he Cincinnai pracice-based sys-

em o suden es score daa in ha disric, aylor and yler nd ha eachers who

go hrough a comprehensive evaluaion are more eecive a promoing suden

achievemen growh han hey were in he years prior o being evaluaed, conrolling

or he eecs o experience on eacher eeciveness. Te research shows ha no

only are eachers more eecive in he year o he evaluaion, bu he same eachers

are even more eecive a promoing suden learning in he years ollowing evalua-

ion. Tis research suggess ha here are subsanial human capial gains associaed

wih going hrough a rigorous and high-qualiy evaluaion process.

Wha’s more, he size o he esimaed eec is subsanial. A suden augh by a

eacher aer ha eacher paricipaes in he Cincinnai evaluaion program will score

abou 10 percen higher in mah han a similar suden augh by he same eacher

beore ha eacher was evaluaed. I hose wo sudens began heir respecive yearsa he 50h percenile o mah achievemen, he suden who was augh aer he

eacher wen hrough evaluaion would score a abou he 55h percenile a he end

o he year while he oher suden would remain a he 50h. Te sudy is unable,

however, o ideniy he mechanisms o he evaluaion process ha lead o he gains




in eacher qualiy, bu a prime candidae is he eedback ha eachers receive aer

each o he our classroom observaions during he year.

Mos discussions around evaluaion oday ocus on heir use o ideni y low- and

high-perorming eachers so ha he poor perormers can be removed rom

he classroom or provided wih exra help and, in some ew insances, he high-perorming eachers can be rewarded via a meri-based compensaion sysem. Te

possibiliy raised by he aylor and yler sudy ha rigorous pracice-based evalu-

aion can help make eachers beter, eecively serving as proessional develop-

men, adds an imporan dimension o eacher evaluaion reorm.20

Practice-based evaluation in high school

Challenges and solutions

Te challenge in designing high-qualiy, pracice-based evaluaion sysems or high

school eachers begins wih he conen specializaion embodied in high school edu-

caion. Unlike elemenary school, sudens in high school move rom class o class,

rom eacher o eacher, and each eacher presumably (hough no always) possesses

specialized conen knowledge. Tis srucure poses real issues or pracice-based

evaluaion o eachers since in he ideal i requires evaluaors who are also conen

specialiss. Tus, he high school principals and assisan principals asked wih

evaluaion in mos disrics would ideally be well-versed in he conen being augh

by each eacher hey are evaluaing as well as in he bes pracices or eaching ha

conen. Given he number o dieren courses and conen areas augh in a ypical

comprehensive high school, his ideal is no realisic.

In disrics ha supplemen or supplan principal-led evaluaions wih maser-

eacher evaluaors, as is done or example in Cincinnai and Washingon, D.C.,

i is more likely ha conen experise beween he evaluaor and he eacher

being evaluaed can be mached. Even in his siuaion, however, i is no easi-

ble o have an evaluaor wih conen specializaion or every subjec covered in

high school. A ypical comprehensive high school, or example, can have up o50 dieren courses ha are oered and augh, and when career and echnical

educaion courses are included, he number o dieren courses across conen

areas can be 100 or more.21




Some o he concern regarding conen specializaion can be miigaed by he

naure o he evaluaion proocol ha is used o evaluae and score eachers’

pracice. Te Danielson Framework or eaching, or example, is designed around

he concep ha good eaching looks he same across grades and subjecs and hus

he rubrics in he ramework are appropriae or all eachers, including high school

eachers. Te Classroom Assessmen Scoring Sysem-Secondary, or CLASS-S,ool, he newes proocol rom he CLASS-amily ou o he Universiy o Virginia,

is designed or use across subjecs in high school. Tus, heoreically, an evaluaor

lacking experise in a given conen area should be able o evaluae high school

eachers across subjecs using hese ools.22

Using conen-neural evaluaion ools does no, however, solve all o he prob-

lems, he mos imporan o which may be eacher buy-in. Consider he case o

a calculus eacher who migh be evaluaed by someone wih he closes available

experise—perhaps a individual wih a mah background and mah cericaion—

bu who has never augh calculus. Even i he evaluaion rubric guides he evalua-or on general insrucional behaviors ha should be seen and scored in a calculus

classroom, one can imagine he eacher asking “How can I be airly evaluaed by

someone who has never beore augh calculus?” Tis siuaion suggess a less-

han-ideal dynamic beween he eacher and evaluaor, a dynamic ha in he bes

o siuaions may inhibi how he eacher values any consrucive eedback rom

he evaluaor and in he wors o cases may lead o a union-backed grievance i he

evaluaion comes in low and here are negaive consequences or he eachers.

Tere are, however, ways o a leas parially address he overarching problem.

When he principal is no he primary evaluaor in he sysem, disrics can

atemp o spread heir evaluaion experise across conen areas when selecing

and raining evaluaors, knowing here will sill be some subjecs where here is

conen mismach beween he evaluaor and he eacher. When he sysem relies

on building adminisraors o conduc he evaluaion, he model could be adaped

so ha, or example, a leas one classroom observaion is carried ou by some-

one in he disric wih conen experise ha maches ha o he eacher under

evaluaion. Tis will increase he logisical burden o he evaluaion sysem and

poenially he cos, bu he payo in erms o eacher and union buy-in could be

worh i in he long run. Even so, given he number o dieren conen areas ina comprehensive high school, i is no realisic o hink ha disrics will ever be

able o provide conen-specic evaluaion or all eachers under evaluaion.






evaluaors who could be locaed anywhere. A disric could hen have is own core o

evaluaors who score video les in a cenral locaion or even in heir homes. One could

also imagine disrics sharing he coss and eors o evaluaors. One disric migh

no be able o keep, or example, an evaluaor o dance insrucion busy, bu evalua-

ing dance insrucion migh be a ull-ime job or a rained evaluaor employed across

several disrics. Tis concep naurally leads o he possibiliy o he developmen o markes or rained evaluaors across conen areas.

Tere are oher advanages o high-qualiy classroom eaching videos. Firs, here

are likely subsanial cos savings. Te cameras used in he ME projec currenly

cos abou $4,500 each and he soware license can cos an addiional $150 per

eacher evaluaed.25 Using Cincinnai as an example, i 12 ull-ime evaluaors in

he Cincinnai sysem were replaced wih 12 video cameras and he 250 each-

ers were evaluaed via a new video sysem, he rs-year coss or he camera and

licensing would be abou $370 per evaluaed eacher. Tere would, o course, be

addiional coss associaed wih paying evaluaors o view and score he videos,along wih oher suppor such as echnical suppor or he operaion and some

eacher raining on how o se up and use he equipmen. Given ha Cincinnai

currenly spends $7,500 per evaluaed eacher, here is a lo o per eacher money

le or hese addiional coss aer he iniial $370 video invesmen. Also, he larg-

es par o he $370 per evaluaed eacher invesmen, he $4,500 purchase cos

per camera, is no a cos ha recurs every year.

Anoher advanage o a video approach o classroom observaions is ha since he

evaluaor has he opion o rerun any porion o he video, here is he opporu-

niy o review pars o he episode as migh be needed, leading o greaer scoring

accuracy. Te opporuniy or muliple evaluaors o score he same eaching

episode would also allow or increased scoring accuracy and greaer objeciviy

relaive o “one-sho” in-person classroom observaions.26 Moreover, sel-refecive

eachers would have he opporuniy o wach heir own eaching episodes and

learn rom hem. Finally, over ime, a disric could build a library o exemplary

eaching episodes across all conen areas or use in proessional developmen

aciviies, paricularly wih new eachers.

Wha is no ye clear is wheher eachers who currenly resis he validiy o beingevaluaed by ou-o-conen evaluaors will have a dieren atiude oward being

evaluaed on video by ou-o-disric evaluaors who would poenially have litle

or no conexual inormaion o accompany he videoaped eaching episode.

Neverheless, given he direc personnel coss and ineviable conen mismach




associaed wih he curren pracice-based mehods o evaluaing high school

eachers, he increased use o echnology in eacher evaluaion holds subsanial

promise, paricularly when i comes o addressing he challenge o eecively

evaluaing high school eachers across he curriculum.27

While evaluaing high school eachers using perormance-based measures poseschallenges o school disrics, he challenges are no insurmounable. Te real

quesion in he years ahead will no be wheher we have he ools and mehods

or evaluaing high school eachers in valid and reliable ways, bu raher wheher

we exercise he will o evaluae as many eachers as possible o he bes o our

abiliy and hen use ha inormaion o diereniae high school eachers in

ways ha allow or meaningul personnel and insrucional decisions.

Anoher orm o eacher evaluaion gaining accepance is based on suden perormance

measures. Ye, like wih pracice-based evaluaions, here are pluses and minuses.




Using student performance

measures to evaluate teachers

eacher evaluaion using suden perormance measures is a rapidly emerging area

ha is gaining a oohold in saes and disrics across he naion. Several acors

have come ogeher o make his possible. Te esing requiremens o NCLB ha

have emerged in he las decade have provided he necessary measures o suden

perormance; he rapid spread, increased qualiy, and declining coss o compu-

erizaion and elecronic daa warehousing have eased he burden on daa sorage

and manipulaion. In addiion, advancemens in saisical modeling echniques

have provided he analyical ools necessary or using suden es scores o evalu-ae eachers. All o hese acors have come ogeher o make i possible o evalu-

ae a porion o he eachers in mos disrics based on heir abiliy o promoe

suden perormance on sandardized ess, so-called “value-added” measures o

eacher eeciveness.

Tese quasi-experimenal saisical models yield esimaes o he conribuion

o eachers o suden achievemen, conrolling or nonschool sources o suden

achievemen growh. Anoher way o characerize value-added measures is ha

hey are he dierence beween he acual achievemen o a eacher’s group o

sudens and he prediced achievemen o hese sudens given heir prior es

scores, demographic characerisics, and oher measures in he model. Simply pu,

he objecive o a value-added growh model or eacher evaluaion is o eliminae

acors conribuing o boh suden achievemen levels and student growth over

which a eacher who is being evaluaed has no conrol.

From he disric sandpoin he advanages o using value-added o measure

suden growh and evaluae eachers begins wih he ac ha his mehod is

much cheaper han pracice-based eacher evaluaion. Given ha disrics already

have he daa in hand or calculaing eacher value-added measures, he primary coss o develop value-added sysems are likely o be relaed o echnical assisance

consulaion ha may be needed o help wih daa sysem consrucion and model

developmen. Tese coss should all as value-added models and he daa sruc-

ures required or hem become more sandardized and esablished over ime.




A second advanage o value-added measures o eacher eeciveness is ha hey

evaluae eachers on observed oupu—suden learning. One could argue ha

he ess on which value-added measures are based do no adequaely measure

he ypes o suden learning ha we wan o promoe in schools. Tis, however,

is a criicism o he ess currenly in use raher han a criicism o he value-added

mehods ha rely on hese ess.28

I is also he case ha value-added measures are more objecive han perormance-

based measures ha ulimaely rely on human judgmen and ha hese saisi-

cal measures o eacher eeciveness generae diereniaion among eachers by

consrucion. Given ha disrics do no currenly use perormance-based eacher

evaluaion in ways ha produce meaningul diereniaion among eachers, he

variaion inheren in value-added scores is poenially a signican bene.29

No surprisingly, here are cauions ha accompany he use o value-added as a

mehod or evaluaing eachers, beginning wih he ac ha value-added measuresprovide no inormaion ha could help a eacher become more eecive. Wih

value-added esimaes, a eacher only knows where he or she ranks in he value-

added disribuion relaive o oher eachers. Tere is no addiional inormaion in

a eacher’s value-added score ha would inorm he eacher as o why he or she is

ranked low or high relaive o ohers.

Tere is also concern ha i value-added-based evaluaions are used or high-

sakes decisions, hen eachers will have he incenive o “each o he es” or

chea. In his case “eaching o he es” does no reer o explicily eaching

maerial ha a given es covers, somehing we migh wan eachers o do or well-

consruced ess. Raher i reers o spending valuable class ime on es-aking

echniques or ocusing on responses o specic, expeced quesions—i is each-

ing ha does no promoe real and lasing learning gains. When i comes o chea-

ing, here is evidence ha when es resuls are ied o high-sakes decisions, some

eachers will resor o cheaing as a way o aricially infaing es scores.30

Anoher concern is ha, a heir bes, value-added measures only capure a

eacher’s conribuion o his or her sudens’ learning as measured by sandardized

es scores. Te concern here is ha hese ess only measure a subse o wha we wan sudens o learn and by ocusing eacher evaluaion on his sphere, we risk

disoring eaching and learning ha encompasses he breadh o wha we wan

sudens o learn. One counerargumen o his is ha sandardized ess cover




maerial ha had been developed by relevan sakeholders ha is deemed o be

imporan and ha hese ess end o be predicive o laer lie oucomes ha we

care abou.31 Anoher counerargumen is ha or eecive eachers, preparing

sudens o do well on hese ess is a byproduc o heir normal eaching across

he breadh o he curriculum.

wo relaed issues—measuremen error and ineremporal sabiliy—also pose

some cause or concern when i comes o value-added esimaes. Perormance

on any assessmen will vary rom one adminisraion o he nex or random

reasons—a naural fucuaion known as measuremen error. For value-added

measures his means ha any given eacher’s ranking in a disribuion o eacher

value-added esimaes is an approximaion ha conains a degree o uncerainy.

Wha his means pracically is ha idenicaion o eachers in he upper or lower

reaches o he value-added disribuion can be done wih reasonable condence.

Te value-added models, however, end o be less useul or diereniaing each-

ers who are more proximae o each oher in he disribuion.

Measuremen error also comes ino play i insead o considering he value-added

measures o wo dieren eachers in he same year, one were ineresed in he

value-added measures o he same eacher in dieren years. Te concern here

is abou he degree o ineremporal sabiliy o he value-added measures: he

exen o which value-added scores or any given eacher are sable rom one year

o he nex. While eachers’ eeciveness may change somewha rom year o year,

one would no expec radical year-o-year changes in rue, underlying abiliy. Tus,

i value-added scores are good esimaes o a eacher’s abiliy, hen hey should be

relaively sable across ime.32 Saisically speaking, his means we would expec a

high year-o-year correlaion in value-added scores. I one year’s value-added score

perecly prediced he nex year’s score, hen he year-o-year correlaion would

be one. And i here is no year-o-year relaionship, hen he correlaion would be

zero. Resuls o his poin across numerous sudies sugges ha year-o-year value-

added correlaions are usually 0.2–0.5 or elemenary school eachers, suggesing

ha a eacher’s value-added score in one year is no necessarily a good predicion

o his or her value-added score in he subsequen year—a roubling proposiion o

some. I is he case, however, ha wih more inormaion his problem is subsan-

ially abaed. Using daa rom wo prior years, or example, insead o one, subsan-ially improves he abiliy o predic uure perormance.33

Regarding he saisical properies o value-added esimaes, i is worh reieraing

wo poins made in a sudy by Dan Goldhaber.34 Te rs is ha here are errors in




measuremen in any endeavor o capure complex human behavior. Tis includes

using pracice-based measures o eaching eeciveness, even hough measure-

men error associaed wih, say, classroom observaion scores is rarely considered

or discussed. Second, value-added esimaes are on par wih perormance mea-

sures in oher elds in erms o heir predicive validiy. Tis includes he mos

saisical o all proessional spors, Major League Baseball, where saisical mea-sures o oupu are regularly used o reward players and consruc employmen

conracs, even hough he year-o-year correlaion o many oupu measures are

similar o wha we see or value-added scores.35

Te purpose o conrolling or prior suden es scores and oher suden- and

class-relaed acors in value-added measures is o ry o isolae he eec o he

curren eacher on suden achievemen gains. Jesse Rohsein has conduced

research ha has brough ino quesion how well ypical value-added models acu-

ally accomplish his, bringing atenion o poenial biases in value-added esi-

maes. Tese biases arise when sudens are sored ino classrooms on he basis o “dynamic” acors such as suden home issues ha are ime varying, unobservable

o he researcher, and are relaed o suden oucomes.36

Similar o he jus-discussed insabiliy issues, a response o he concern lies in

having addiional years o daa o correc or his ype o poenial bias. Using rich

daa rom he San Diego school disric, Cory Koedel and Julian Bets were able

o replicae he biases revealed in Rohsein’s work. Addiionally, hey show ha

a sucienly complex value-added model ha evaluaes eachers over muliple

years can reduce he soring bias o saisical insignicance.37 One implicaion o

his line o work is ha while one year o value-added daa migh be used o make

low-sakes decisions such as deciding on proessional developmen allocaion, a

disric would wan o rely on muliple years o daa or making high-sakes deci-

sions such as eacher enure or job erminaion.

A las concern wih value-added measures o eacher eeciveness is ha only

15 percen o 35 percen o he eachers in any given disric each in grades and

subjecs where sudens have boh a sandardized end-o-year es and a suiable

prees.38 Primarily because o he sae sandardized ess arising rom he NCLB

esing regime, hese “esed” grades and subjecs end o be mah and reading ingrades 3–8. Tis is obviously a major challenge or using value-added o evaluae

high school eachers bu some o he op value-added researchers in he counry

are working on his problem as will be discussed shorly.




Evaluating high school teachers based on student performance

Inherent challenges

Basing a subsanial porion o a eacher’s evaluaion on suden perormance mea-

sures was no only required o win Race o he op unds; i is somehing ha many sae deparmens o educaion and school disrics across he naion are exploring

even wihou supporing ederal unds. Aer all, eachers each in order o impac

suden academic perormance, and many argue ha i makes sense o evaluae

eachers on how well hey accomplish ha goal. While value-added measures are

currenly he mos researched and alked abou mehod or doing his, here are

oher mehods under consideraion ha will be discussed in his secion. Firs, le’s

look a he special issues ha high school eachers pose or value-added models.

As a roadmap o his discussion, he ollowing issues will be aken in urn:

• Te availabiliy o suiable ess a he high school level• Te pah dependency o sudens in a given class• Te poenial spillover eecs o eachers in dieren subjecs• How o weigh he dieren subjecs a eacher migh each in an overall value-

added score• Te poenial or perverse incenives unique o high school• Te logisics o suden atribuion• Having small numbers o eachers in he value-added disribuion

Availability of suitable tests

Unlike grades 3–8, here are no regular sae ess across grades and core subjecs

mandaed by NCLB a he secondary level.39 As a resul, mos saes have no

developed sae ess or all high school grades, posing a cenral challenge a he

high school level or using sandard value-added models ha require boh a pre-

and pos-es.40 Addiionally, unlike he elemenary grades where we can hink

o mah and reading as being “core subjecs” in he elemenary and even middle

school grades, he noion o core subjecs has much less racion in high school where sudens begin o branch ou and explore dieren opics and conen.




Some saes and disrics can parially address he oucome-es problem via

“end-o-course,” or EOC, exams or semeser exams ha have been developed o

assess suden masery o course-specic knowledge. Tese exams are ied o sae

or disric curricula in a specic course, are adminisered as sudens complee a

course, and usually have high sakes or he suden such as wheher he course is

passed or credi. Currenly, here are 23 saes ha have EOCs or a leas somecourses, bu even in hese saes, many high school eachers sill each in grades or

subjecs ha are no covered by EOCs.41 Georgia is an example o a sae ha has

developed saewide EOCs ha all sudens in given courses have o ake and pass.

Tere are, however, only eigh conen areas across he our core subjec areas

(mah, ELA, science, and social sudies) ha have EOCs in Georgia. Tus, while

sudens aking biology, or example, would have an EOC in Georgia, sudens

aking physics would no.

Te one disric in he naion ha is working on developing a comprehensive

arsenal o course-specic semeser examinaions is Hillsborough Couny PublicSchools, ampa, Florida. Hillsborough Couny Public Schools has developed

over 500 semeser examinaions or courses ranging rom 9h-grade English o

sculpure o rigonomery o welding. Hillsborough also worked wih he Florida

Deparmen o Educaion o make heir semeser examinaions available o oher

disrics across he sae via he Florida End o Course Exam Clearinghouse. Te

scope o he Hillsborough eor, over 500 exams, illusraes he magniude o he

eor required o develop course specic examinaions ha could cover every

high school eacher.

Neverheless, as disrics and saes develop semeser or EOC exams and share

hem hrough sae sponsored exam clearinghouses or oher venues, an increasing

number o high school eachers will a leas be eaching in courses ha will have

an associaed pos-es or use in value-added calculaions.

In grappling wih he high school es availabiliy issue, researchers oen concep-

ualize he value-added model less in erms o measuring suden growh rom

one year o he nex, as is he general concepual model a he elemenary level,

and more in erms o exceeding (or alling shor o ) predicted achievement .43 Tis

concepualizaion helps clariy he expansion o value-added models o noncore-subjec areas and grades, like high school, where growh may no be easily dened

or measured. In his realm here may or may no be pre-ess available or use as

direc predicors o he oucome and, as a resul, researchers will oen have o rely

on wha could be ermed relaed predicors o he oucome.44




aking mah as an example, as a resul o NCLB mandaes, sudens in grades 4–8

will have boh an oucome measure (or example, ourh-grade sae mah exam)

and a direc predicor in mah (he previous year’s hird-grade sae mah exam).45

Conras his wih he high school siuaion where even when here is an available

EOC exam ha can be used as an oucome measure (an EOC exam in geomery),

here may seldom be a suiable prior es ha could be used as a direc predicor. As a resul, value-added models a he high school level will oen have o rely on

relaed predicors o he oucome measure.

A his poin, he value-added research communiy is in he early sages o develop-

ing and esing models ha atemp o address he lack o direc predicors (pre-

ess) in high school. In his work, some models use scores rom conemporaneous

ess in oher subjecs as relaed predicors.46 Ta is, i he oucome is an EOC or

10h-grade geomery, hen scores rom 10h-grade English and science exams, i

available, migh be used in he predicive model. Oher models under consideraion

and esing include no only conemporaneous, oher-subjec ess bu also an EOCor summaive exam rom he previous year in he same conen area. Sill oher

models being sudied would incorporae he conen area eighh-grade sae exam

as a secondary predicor. A his poin researchers are engaged in sudies o develop

he bes possible predicive value-added models or use in evaluaing high school

eachers. Success on his ron may only sar he decision process or disrics as i is

unlikely ha here will be black and whie answers as o wha is he “righ” value-

added model a disric should use o evaluae high school eachers.

Since dieren models will embody dieren assumpions and rely on dier-

en variables o conrol or ouside-o-class infuences on suden perormance,

disrics will likely have o make policy decisions regarding which models hey will

use or high school evaluaion. Neverheless, he work on his ron is impressive

wih grea srides having been made wih many disrics and saes currenly in

he process o considering how, no wheher, o use value-added as one acor in

evaluaing heir high school eachers.

Path dependency

In elemenary school sudens generally ollow he same pah hrough he grades

wih litle deviaion in erms o he subjecs hey sudy and in wha year hey

sudy hem. Tus, elemenary-level value-added esimaes res on a airly solid

assumpion ha, in general, sudens arrive a he oucome measure via he same




academic pahway. Sudens aking he h-grade sae mah exam, or example,

ge here by passing rs hrough ourh grades and aking he mah curricula in

each o hese grades. Where here are deviaions, say, or being held back a year or

being in a gied and alened program, hese deviaions can be accouned or in

he model as long as his inormaion is in he adminisraive daa.

On he oher hand, a common pah o a given course is rarely he case in high school

given ha sudens in he same cohor can ake dieren courses each year as well as

dieren sequencing o he same courses as hey progress hrough high school. I he

courses aken prior o or conemporaneous wih some oucome measure have he

poenial o impac ha measure, and i he impac is dieren depending on when

he earlier courses were aken relaive o he oucome o ineres, hen i is imporan

o accoun or such pah dependency in high school value-added models. Given

ha here are many possible “pahs” o, say, he EOC exam in 11h-grade physics,

accouning or pah dependency is no a simple mater.

One way o sudy his poenial problem is o use exising daa o sudy how

sensiive value-added measures are o pah dependency. Exising daa in a given

disric, or example, could be used o deermine he mos common wo, hree,

or our pahs sudens ake o, say, 11h-grade physics. Value-added esimaes

ha hen conrolled and didn’ conrol or hese pahs could be compared. I

i urns ou ha in mos cases pah dependency is no a srong predicor o he

oucome, given oher predicors in he model, hen here is less concern wih ry-

ing o accoun or pah dependency. I his is no he case, hen he ask will lie in

developing racable mehods ha conrol or he dieren pahs sudens ake in

arriving a he oucome o ineres.

Teacher spillover effects

Again unlike elemenary school, where sudens end o be augh all o he sub-

jecs by one eacher, high school sudens have up o ve or six dieren eachers

every semeser. I one’s perormance is infuenced by all o heir eachers, regard-

less o he oucome measure, hen value-added esimaes or he eacher o record

ha did no accoun or he spillover eecs o oher eachers could be biased. I mos o a given eacher’s sudens, or example, ended o have very high-perorm-

ing eachers in heir oher subjecs and here were spillover eecs ha aeced

he sudens’ scores in he oucome subjec, hen ailure o accoun or his would

lead o upward bias in he value-added esimaes o ha eacher: He or she would




receive credi or he sysemaically good eachers ha his or her sudens had in

heir oher subjecs. Tis oo is a poenial horny issue because o all o he poen-

ial combinaions o “oher eachers.” Again, a poenial way o sudy his issue is

o use exising daa and model some o he mos common combinaions o oher

eachers observed in he daa or given oucomes o ineres and deermine how

imporan i is o accoun or sudens’ oher eachers.47

Teacher weighting across different courses

Te issue here is ha some, i no many, high school eachers will each more han

one course. Te ypical high school mah eacher, or example, migh each an

Algebra I course along wih some Algebra II courses and some geomery courses

in he same year and/or semeser. Or, given he breadh o courses oered in

he ypical comprehensive high school, a single eacher migh be responsible or

eaching, say, hisory, psychology, and sociology. In developing a measure o how eecive a eacher is, how should he value-added-relaed perormance in each o

he various subjecs be weighed? Tis is a policy decision raher han a modeling

decision ha disrics will have o make, and here is no clear answer as o wha is

he “righ” decision. Since he decision will mos likely aec eachers’ nal evalu-

aion score, however, i is a serious issue in evaluaion sysem design ha disrics

will have o consider.

Perverse incentives

Tere are cerain perverse incenives ha can arise a any grade level when eacher

evaluaion is based on suden es scores. High school eachers whose evalua-

ions are dependen upon heir sudens’ es scores are cerainly no immune

rom he empaion o “each o he es” or o chea in ways ha could aricially

infae es scores. In addiion o hese grade-neural perverse incenives, however,

eacher evaluaion based on value-added models a he high school level mus

guard agains perverse incenives specic o high school. In paricular, we would

wan o guard agains pracices ha incenivized eachers o encourage heir

lowes-perorming sudens o eiher drop ou o school or drop he course beorehe end-o-year exam. High school evaluaion sysems also need o assure ha all

sudens, including hose repeaing a course, which is mos common in he ninh

grade, are included in he esing regime so ha eachers will have he incenive o

each all sudens o he bes o heir abiliy.




Logistics of attribution

Assigning he correc sudens o he correc eachers is an imporan issue or

all value-added models, and he evidence is ha correcly capuring a eacher’s

roser o sudens based on adminisraive daa is a ar-rom-rivial ask. In a

sudy by he nonpro, school-improvemen organizaion Batelle or Kids hacovered 57 disrics and 730 schools in wo saes, 26 percen o all suden

assignmens were moved, added, or deleed rom he disric-repored daa

hrough Batelle’s more careully execued eacher-linking process.48 Correc su-

den atribuion is an even more dicul process a he high school level han a

he elemenary level i or no oher reason han each eacher has muliple classes

o sudens, each o which require accurae atribuion. Roser vericaion, espe-

cially in high school, is a major challenge ha disrics conemplaing he use o

value-added measures have o ake seriously.

Given boh he challenge and he imporance o correcly linking sudens andeachers, several organizaions across he naion are devoing resources and ime o

help saes and disrics develop daa sysems and inrasrucure ha will allow or

he kind o linkage required by high-qualiy value-added sysems. Among hese orga-

nizaions are Batelle or Kids, he Daa Qualiy Campaign, and he eacher-Suden

Daa Link Projec o he Cener or Educaional Leadership and echnology.49

Teacher group size

All value-added esimaes place eachers in a disribuion o oher eachers. In he

case o value-added a he elemenary level, he eacher is usually compared o

oher eachers in he disric in he same grade and year. Tus a h-grade eacher

in a midsized school disric migh be in a disribuion wih 75 o 100 oher h-

grade eachers. A poenial issue wih high school value- added is ha in addiion

o he grade by year comparison group, eachers need o be compared o oher

eachers eaching he same subjec. Tis can be poenially problemaic or mid- o

small-size disrics as here may no be enough, say, physics eachers in he disric

or he comparison o be meaningul. In ha ype o scenario, wha does i mean o

be a he botom (or op) o he value-added disribuion o physics eachers whenhere are our physics eachers oal in he disric? Value-added wih small numbers

o eachers in he comparison group probably makes litle sense and in hese cases

oher measures o eacher eeciveness will have o be used or he disric in con-

juncion wih he sae deparmen o educaion would need o deermine wheher i

makes sense o compare eachers saewide raher han disricwide.




Potential opportunities

Tere are also poenial opporuniies or using value-added measures in high

school eacher evaluaion no presen in he elemenary school seting. Since

he end-o-year sae exams used a he elemenary level are aken by all su-

dens in a sae, hey are largely designed o be “curriculum ree.” In conras,he EOC ess and oher course-relaed ess being considered or high school

value-added are designed o be in alignmen wih he curriculum being augh.

As a resul, eachers have more power o impac suden perormance on ess

aligned wih he augh curriculum han hey do on perormance on curricu-

lum-ree sae exams. I is also likely ha incenives are beter aligned, which

in urn yields greaer eacher buy-in when he es over which a eacher will be

held accounable is sensiive o he augh curriculum.

A second poenial advanage or high school value-added is ha in mos cases

here will be subsanially more sudens on a high school eacher’s roser hanan elemenary eacher’s since high school eachers as a rule each several classes.

Tese addiional sudens help reduce he measuremen error discussed earlier,

meaning ha a eacher’s value-added score is more precisely esimaed.

A nal opporuniy worh noing is ha he series o challenges a disric aces

in rying o develop good value-added measures or heir high school eachers is

leading disrics o conemplae he enire evaluaion, esing, and daa ener-

prise o he disric in a more coheren way han has generally been he case

o his poin. Disrics on he leading edge o his work undersand ha using

value-added o evaluae high school eachers requires hinking abou esing

and daa issues in a coheren and sysemaic way. When done well his holis-

ic approach can have posiive spillover eecs ha can bene more han jus

eacher evaluaion in he disric.

Other student per formance measures

As previously noed, many saes and disrics are developing suden peror-

mance measures ha are no based on value-added esimaes. In large par heseeors are in response o some o he diculies discussed above in consrucing

value-added measures or eachers in nonesed grades and subjecs. One resul o

his work is he developmen o Suden Learning Objecives o measure eacher

eeciveness. SLOs are daa-based arges o suden growh ha eachers se or




he sudens a he sar o he semeser or school year. eachers are hen evaluaed

a he end o he semeser or school year on he exen o which heir sudens me

he objecives ha hey se or heir sudens. SLOs are currenly in use in Denver,

Colorado; Ausin, exas; and Charlote-Mecklenburg, Norh Carolina. Many

new sysems, including he sae sysem in Rhode Island, are incorporaing SLOs

ino new evaluaion sysems.50

In some insances SLOs are used only in nonesedgrades and subjecs, while in oher cases a disric is incorporaing SLOs ino he

evaluaion o eachers in addiion o, insead o in place o, value-added measures.

Te ypical seps a eacher goes hrough in seting SLOs are:51

• A he beginning o he semeser or year, review available daa on he sudens

in he class, including prior-year es perormance and any course pre-ess ha

have been adminisered.

• Based on he daa, se a designaed number o objecives, usually wo—class-roomwide and suden- or subgroup-specic. An example o a class-level objec-

ive migh be: “Increase he Algebra I end-o-course pass rae by 5 percenage

poins over las year’s 85 percen pass rae.”

• Ideniy appropriae measures agains which objecive atainmen will be

judged. Following he above example, he measure or judging objecive atain-

men would be he class pass rae on he Algebra I end-o-course exam.

In many insances eachers mus review and discuss heir SLOs wih heir prin-

cipal (and someimes cenral oce sa) as a par o he SLO-seting process.

Te principal (and cenral oce sa when appropriae) mus hen approve and

sign o on each eacher’s SLOs. While here is litle research o dae on SLOs,

principal and/or cenral oce approval is likely a key par o he SLO process.

Te incenive wih no oversigh is or eachers o se easily achievable SLOs ha

heir sudens can readily mee.

Mos o wha we know abou SLOs a his poin comes rom Denver and Ausin.

A 2004 pay-or-perormance pilo program based on 17 Denver schools, includ-

ing wo middle schools and wo high schools, ound ha 89 percen o 93 perceno he eachers in he pilo me heir objecives over he our years o he pilo

(1999–2003). Furher, he qualiy o he SLOs se by eachers wen up over he

our years.52 In sudying he relaionship beween he qualiy o he SLOs se by

middle school and high school eachers and heir sudens’ perormance, here




was consisen evidence o a posiive relaionship, hough his evidence was

oen no saisically signican. Posiive and saisically signican correlaions

beween he number o objecives me by eachers and he achievemen o heir

sudens were ound in he wo high schools.53

In Ausin, SLOs are par o he REACH sraegic compensaion program.54

Tere,SLOs are based on he sae curriculum—he exas Essenial Knowledge and

Skills. In 2009-10 eachers in REACH schools received sipends o beween

$1,000 and $1,500 or each me SLO. Te SLO process in Ausin begins wih

eachers examining heir sudens’ perormance daa and ideniying wo areas

o greaes needs. Pre-assessmens are hen adminisered o he sudens in he

seleced area o needs. Based on he resuls o he pre-ess, eachers hen se SLOs

ha mus be reviewed and approved by he campus principal and disric cenral

oce. Each SLO mus indicae perormance arges ha sudens will mee by

he end o he school year and how perormance will be assessed. Suden resuls

rom he end-o-year pos-assessmen are hen used o deermine wheher or noa eacher me his or her SLOs. In an analysis based on 2009-10 sae es daa,

sudens o REACH high school mah and science eachers who me a leas one

o heir SLOs demonsraed greaer ne achievemen growh han did he sudens

o REACH eachers who did no mee SLOs.55

Te nonexperimenal naure o boh he Denver and he Ausin sudies relaing

SLOs o suden achievemen leave some doub regarding ha relaionship and

indicae he need or addiional sudies on he opic. Fuure sudies should also

look a he relaionship beween SLOs and suden achievemen gains, no jus

levels. Anoher issue wih which SLO-based evaluaion will need o grapple in he

uure is comparabiliy across classrooms when SLOs are based on he individual

choices o eachers. Finally, i is no clear a his poin how eecive he SLO

evaluaion process can be a diereniaing among eachers who are dierenially

eecive. Te early evidence rom he Denver pilo projec looks disurbingly simi-

lar o he resuls rom he “Te Widge Eec.”

Anoher way in which several disrics and a leas one sae (Delaware) are

developing nonvalue-added measures o suden achievemen growh is hrough

“common growh measures.” o develop a se o common growh measures, acommitee o eachers and oher educaors a eiher he sae or disric level

reviews available measures o suden growh and hen makes recommendaions

o he disric or sae, which hen approves a lis o measures or each subjec

and grade under consideraion. In Delaware more han 300 educaors have




been enlised o help develop suden growh measures in 30 conen areas.56 In

addiion o Delaware ve upsae school disrics in New York are developing

common growh measures o use in evaluaion sysems. Tis is a promising and

much-needed developmen in ha he common growh measure process is even

less sudied han SLOs. A his juncure i is oo early o know he exen o which

eiher can serve as useul ools in eacher evaluaion sysems.




Conclusion

Developing eecive ways o evaluae high school eachers holds he promise

o improving he high school educaion experience or he millions o sudens

who will be augh by hese eachers. Based on wha we know rom research and

experience, he ollowing ideas should guide evaluaion sysem developmen and

implemenaion and he ongoing work in his area in he coming years.

The best evaluation systems will incorporate all availableinformation from both practice-based information and student

performance data into the ultimate evaluation of teachers

Tis means ha boh value-added measures and SLOs should be used when pos-

sible and ha value-added measures should be used wih as many high school each-

ers as possible. Te ough decisions should be around how o weigh he dieren

componens, including value-added, no wheher or no o use hem a all in eacher

evaluaion. Based on he research evidence, sysems ha do no use all o hese mea-

sures are leaving inormaion abou he eeciveness o heir eachers on he able.

A he same ime, jus because i may be hard o develop value-added measures

or all high school eachers in a disric, disrics should no use his as an excuse

o orego value-added evaluaion or he subse o eachers where he daa are

available. Jus as he sandard pay scale across all subjec areas ha is common in

educaion is shorsighed and reduces he supply o qualied mah and science

eachers who could be recruied ino schools, reusing o use value-added inorma-

ion wih some eachers because i may no be available or all is equally unwise.

A good evaluation system will not shortchange its practice-based

evaluation component

Tere are very ew sysems ha currenly make he invesmens necessary o

conduc high-qualiy pracice-based evaluaion. Well-designed sysems use dedi-




caed and rained evaluaors, maser eachers who leave he classroom or wo o

hree years and whose sole responsibiliy is evaluaion o he disric’s eachers.

eachers are observed in he classroom muliple imes during he year, he class-

room observaions are o sucien lengh o gaher meaningul daa abou ha

eaching episode, and he visis are mosly unannounced. Well-designed sysems

use research-based evaluaion proocols and he raining o evaluaors on heseproocols is aken seriously. While such sysems can be cosly, disrics can ose

some o he coss by only puting a porion o he eachers on he ull, comprehen-

sive evaluaion cycle each year. I is arguably beter pracice o evaluae a porion

o he eachers a a level o high qualiy each year han i is o evaluae all o he

eachers wih low-level evaluaion every year. Furhermore, research suggess ha

high-qualiy evaluaion can pay or isel by increasing eacher produciviy, and

ha given his disrics could urher ose evaluaion coss by redirecing some

proessional developmen dollars o evaluaion.57

I is likely ha many disrics ha rely on principals or heir eacher evaluaionaciviies do so because hey see he cos savings o his approach relaive o hav-

ing a cadre o maser eachers who serve as evaluaors. I is also likely ha ew o

hese disrics ake ino accoun he opporuniy coss o shouldering principals

wih his exra duy when considering he coss and benes o principal-led evalu-

aion relaive o alernaive approaches o evaluaion. Given he rising imporance

o high-qualiy eacher evaluaion going orward, disrics should henceorh

consider he ull coss and benes, no jus he accouning coss, o using princi-

pals o carry he bulk o he evaluaion load. When considering he ull coss and

benes o having principals versus ull-ime, rained evaluaors, or some combina-

ion o principals and evaluaors, carry ou evaluaion, principal-led evaluaions

may no be as atracive as disrics currenly perceive hem o be.

We need to continue the work that is being done to develop and test

value-added models appropriate for use with high school teachers

An imporan es or resuling models will be he exen o which high school

eachers’ value-added scores are correlaed wih heir classroom observaion

scores. Tis linkage has been esablished in some ew bu imporan insancesa he elemenary and middle school levels.58 Te akeaway rom hose sudies

is ha low- and high-value-added eachers are doing somehing dieren in he

classroom, and he evaluaors observing hese eachers are seeing ha dierence

and scoring i, even hough he evaluaors hemselves have no knowledge o where




a eacher migh be in he value-added disribuion. Finding his same kind o

relaionship beween value-added and classroom observaion scores a he high

school level would provide an addiional level o condence in wha are likely o

be relaively complex high school value-added models.59

More research focused on SLOs is needed

Given he increasing use o his evaluaion mehod, we need more inormaion

on he exen o which SLO scores are relaed o a eacher’s abiliy o promoe

suden learning gains. Absen his evidence we have o rus ha SLOs are mea-

suring eecive eaching. We need research ha can deermine wheher he SLO-

seting process makes eachers beter and raises he general level o eaching on a

campus and in a disric as some advocaes claim. Given ha SLOs may be used

more a he high school level han a he elemenary level, his research evidence is

paricularly imporan or high school evaluaion.

More work needs to be done on the possibility of developing

assessments that can gauge a teacher’s ability to teach his or her

content

We rs need o know more abou he exen o which hese conen-specic peda-

gogical assessmens are relaed o a eacher’s abiliy o promoe suden learning in

he conen. I we nd here is promise on ha criical dimension, hen ha would

be cause or a push o develop more o hese assessmens across addiional high

school conen areas.

Teacher evaluation should take the lead in finding a way to use

technology for efficiency and productivity gains

Educaion has a dismal record in eecively using echnology. I eacher evaluaion

is o have he impac envisioned by many, we may no be able o aord o ollow

his patern. Especially in he realm o pracice-based evaluaion, echnology holdshe promise o allowing us o do more, do i beter, and wih less cos, paricularly

a he high school level. Te promise o digial video echnology is ha all eachers

in a high school could be “observed” several imes during he year via video, hese

eaching episodes could be viewed by conen specialiss, and he oal coss will




be less han he coss o raining, providing adminisraive suppor, ransporaion, and

salary or disric-based, ull-ime evaluaors. In addiion, as he disric builds a video

collecion o exemplary eaching sessions, i will develop an in-house bank o examples

ha novice eachers and ohers can view as proessional developmen exercises.

***

Te inense work being done across he naion is rooed in he belie ha i we can

do a beter job a eacher evaluaion, he ulimae resul will be beter oucomes or

our kids and by exension our naion. A large par o answering ha promise ress

wih how well new evaluaion sysems perorm a he high school level. An impres-

sive array o high-perorming eachers and adminisraors, evaluaion expers,

economiss and saisicians, echnology leaders, and sae and ederal policymakers

are currenly working on eacher evaluaion issues, wih much o his work ocusing

on he high school quesion. Te urgency wih which his work is being done and

he iming o much o he gran money ied o new evaluaion iniiaives suggessha in he nex ew years, new evaluaion sysems will be in place. I is air o say ha

jus as puting eacher evaluaion ron burner in a disric can change he way each-

ers alk abou heir cra, he naional eor currenly in place is changing he way we

alk abou eaching and how we can and should evaluae eachers across he naion,

including hose in our high school classrooms.




About the author

John H. Tyler is associae proessor o educaion, economics, and public policy

a Brown Universiy. He is also a research associae a he Naional Bureau o

Economic Research. yler has conduced research on he linkages beween

school, skills, and labor marke oucomes, paricularly or low-educaed, low-skilled individuals. His mos recen work has examined quesions peraining o

eacher evaluaion, and in paricular he has examined he relaionship beween

eacher evaluaion measures and eachers’ measured abiliy o impac suden

achievemen gains.

Acknowledgements

Te auhor would like o hank he many people who ook ime o discuss or

correspond on issues in his paper, especially Andy Baxer, Connie Casson,Charlote Danielson, Brian Gill, Dan Goldhaber, Bridge Hamre, Julia

Indelaccio, Rob Meyer, Chrisine Sargen, Maurine and Dave Sigler, Mary Ann

Snider, Eric aylor, and om omberlin.

Te Center for American Progress thanks the Bill & Melinda Gates Foundation for

generously providing support for this paper.




Endnotes

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47 n a i ca wr a ud i a gi cur a am “r acr,” a mig b ca r xamp rud i a r rack, i i pib para u c r, cmprau acr rm au-adddima acr i qui.

48 Ba r Kid, “t Imprac Accuray likig Iruci sud Drmi tacr eci” (2010), aaiaba p://www.barkid.rg/sric/tacig_eci-/likig_tacr_ad_sud.m?fag=.

49 Irmai wrk rgaizai ar dig i

ara ud-acr daa ikag ca b ud, rpciy,a: “Ba r K id,” aaiab a p://www.barkid.rg ;“Daa Quaiy Campaig,” aaiab a p://www.daaquaiy-campaig.rg; “tacr-sud Daa lik Prjc,” aaiab ap://www.d.rg.

50 s. sawcuck, “Wad: Way Maur M tacr,” EducationWeek , Fbruary 2, 2011.

51 “CtAC - sud larig objci (slo),” aaiab ap://www.cacua.cm/.m.

52 Cmmuiy traiig ad Aiac Cr, Catalyst for Change:Pay for Performance in Denver, Final Report (2004).

53 sud acim wa maurd i ma ad radig uigb Iwa t Baic ski, r ItBs, ad Crad sudAm Prgram, r CsAP, ma ad egi .

54 Irmai i i ci ak rm: l. scmi ad n. Ibaz,“AIsD ReACh Prgram Upda: 2009-2010 txa Am Kwdg ad ski (tAKs) Ru ad sud larigobjci (slo)” (Aui, tX: Aui Idpd sc DiricDparm Prgram eauai, 2011).

55 Ibid.

56 summary r yar rpr rm Dawar’ wiig Rac tp appicai ud a p://www.ii2015dawar.rg/wp-c/upad/2011/06/Prgr-Rpr-2011.pd.

57 tayr ad tyr, “t ec eauai tacr Prrmac.”

58 Fr i wrk a i ra Dai Framwrk, : t.J. Kaad r, “Idiyig eci Carm Pracic Uig sudAcim Daa,” Journal of Human Resources 46 (3) (2011):587–613; A. Miawki, “t Raiip Bw sud Prr-

mac scr ad sud Acim: eidc rm Ciciai,”Peabody Journal of Education 79 (4) (2004): 33–53; e. hzapp,“Criri-Rad vaidiy eidc r a sadard-Bad tacreauai sym,” Journal of Personnel Evaluation in Education 17(3) (2003): 207–219. Fr i wrk a i ra ClAss-s, ClAss r u i ig c, : J.P. A ad r, “obrai eci tacig i scdary sc Carm: Prdicigsud Acim wi ClAss-s,” Uiriy virgiia, 2011.Fr i wrk a i ra PlAto , : P. Grma adr,“Maur r Maur: t raiip bw maur irucia pracic i midd c egi laguag Arad acr’ au-addd cr.” Wrkig Papr w16015 (naiaBurau ecmic Rarc, 2010).

59 I r a armid “aidai” udi a mary wr gray a a wr pracic-bad auai wa ruy capurig acig a wa rad ud cr grw. ta i, aumpi a raci wa capurd by a acr’ abiiy prm u-

d cr grw ad pracic-bad cr wr maurdagai i adard. Wa I am prpig r i a r mr cmpx ad a y i udrdpd ig c au-addd md, ir aidai agai acr’ pracic-badcr cud p i b dcidig md pcicai adgraig cdc ad buy-i arud ua md.

http://www.battelleforkids.org/Services/Teaching_Effectiveness/Linking_Teachers_and_Students.html?sflang=en


http://www.battelleforkids.org/

http://www.dataqualitycampaign.org/


http://www.tsdl.org/

http://www.ctacusa.com/slos.html

http://www.vision2015delaware.org/wp-content/uploads/2011/06/Progress-Report-2011.pdf




http://www.ctacusa.com/slos.html

http://www.tsdl.org/



http://www.battelleforkids.org/






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Designing High Quality Evaluation Systems for High School Teachers