Landscape Analysis on Personalized Learning...Landscape Analysis on Personalized Learning July 31,...

LandscapeAnalysisonPersonalizedLearning

July31,2017

ContributingAuthors

AnnKoufman-Frederick,Ph.D.,LearnLaunchInstituteDavidO’Connor,MBA,LearnLaunchInstitute

ElizabethNiegelsky,M.A.,LearnLaunchInstituteKennethKlau,M.Ed.,MADept.ofElementaryandSecondaryEducation

StephanieIacadoro,M.Ed.,DuxburyPublicSchoolsKaitlinKlaustermeier,MBA/MPPIntern,HarvardUniversity

LeslieStebbins,M.Ed.,MLIS,Research4Education

PublishedbytheMAPLEConsortiumatLearnLaunchInstitutewiththesupportoftheNellieMae

EducationFoundationandtheBarrFoundation

TableofContents

ExecutiveSummary...............................................................................................................3

AboutMAPLEConsortium....................................................................................................6

PersonalizedLearningDefined.............................................................................................8

LandscapeAnalysis:GoalsandMethodology.....................................................................10

StatewideSurveyHighlights................................................................................................14

CatalystFocusGroupInterviewHighlights..........................................................................23

StateTechnicalInfrastructureHighlights............................................................................30

LandscapeAnalysisNextSteps............................................................................................37

Appendices...........................................................................................................................38

AppendixA:MethodologyAppendixB1:StatewideSurveyQuestionsAppendixB2:HighlanderInstituteProgressionofPersonalizedLearningAppendixC1:FocusGroupQuestionsAppendixC2:FocusGroupChartAppendixD:MSBASchoolSurveyTechnologyQuestions

ExecutiveSummaryTheMassachusettsPersonalizedLearningEdtechConsortium(MAPLE)Consortiumisapublic-privatepartnershipbetweentheMassachusettsDepartmentofElementaryandSecondaryEducationandtheLearnLaunchInstitute.Aconsortiumof31schooldistrictsrepresentingoneoutofeverysixstudentsinMassachusettspublicschools,MAPLE’sgoalistofurtheranddeepenthegrowthofpersonalizinglearningthroughoutthestate.Theconsortiumiscomprisedof14“CatalystDistricts,”thosethathavemadeastrategiccommitmenttopersonalizinglearningforallstudents,and17GeneralMembersthatarebeginningtoworktowardspersonalizinglearning.OneofMAPLE’searlyobjectivesistomapthecurrentlandscapeofpersonalizedlearninginK-12Massachusettsdistricts,creatingasnapshotofpersonalizedlearningpracticesandrelatedresourcesandcapabilitiesthroughouttheCommonwealthofMassachusetts.GoalsoftheLandscapeAnalysisTheLandscapeAnalysiswillserveasaguideforfutureMAPLEprogramming,identifyschoolexemplarstosharesuccessfulpractices,provideabaselinetodevelopmetricstomeasureprogressincatalyzingpersonalizedlearningindistricts,andinformpublicdiscussionsabouteducationalpriorities.TheLandscapeAnalysiswillalsobeusefultoorganizationsinterestedinsupportingtransforminglearningandteachingpracticesinMassachusettstobetterprepareallstudentsfortheirfutures.MethodologyTheLandscapeAnalysisstudyisguidedbythreekeyquestions:

1. WhatistheprevalenceofpersonalizedlearningpracticesinMassachusettsschooldistricts?

2. Whatistheprevalence,depth,anddescriptionofpersonalizedlearningpracticesinthe14CatalystMemberdistricts?

3. WhatistheleveloftechnicalinfrastructureandavailabilityofdevicesinMassachusettspublicschooldistricts?

Datawascollectedfrommultiplesources,qualitativeandquantitative,usingthreemethodsandsources:(1)astatewidepersonalizedlearningsurveyofleadersineachschooldistrict,(2)in-depthfocusgroupinterviewsandconversationswithCatalystDistrictsabouttheirpathtopersonalizedlearning,and(3)atechnicalinfrastructureassessmentcollectedbytheMassachusettsStatewideBuildingAuthorityin2016.

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KeyPreliminaryFindings

1. Ourmostadvanceddistrictsarestillearlyintheirtransitiontoprovidingstudentswithpersonalizedlearningexperiences,butcanprovidegoodexamplesofpersonalizinglearningtootherdistricts.

a. MostCatalystDistrictshavestrategicplansthatincludepersonalizedlearningelements,butonlyafewhavecomprehensiveplans.

b. Demandfromeducatorsfor“seeingpersonalizedlearninginaction”meansweneedtoleveragethebrightspotsinthesedistrictsmoreextensively.

2. Fewifanydistrictsinthestatehavemigratedfromtraditionalteacher-ledclassroompracticestopersonalizedlearningmodalitiesformostoftheirstudentsandclassrooms.∗

a. Over69%ofdistrictsreportthattraditionalwhole-class,teacher-ledinstructionis“always”or“often”thenormintheirschools.

b. Only8%ofdistrictsreportthatstudents“often”progressindividuallythroughtargetedonlinecontentwhiledynamicgroupspracticeskillsface-to-facewithteachersandwithpeers.

3. Themostcommonchallengesfordistrictstoexpandpersonalizedlearningintheirschoolsareintheareasofteacherprofessionaldevelopment,resourceconstraints(time,funds),andeducatorsexperiencingwhatpersonalizedlearninglookslikeintheclassroom.

∗Source:MAPLEStatewidePLSurvey(n=76)

- 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0

Peercoaching/evaldriveinstruction/grouping

Targetedtogroups/individualswithonline

24/7learningin/outofclassroom

Whole-classteacher-led

Always Often Sometimes Never

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a. However,theleadingCatalystdistrictsaredemonstratingadirectionforthestateineducatorprofessionaldevelopmentwithprogramsforunderstandingbydesign,developingacultureofinnovation,blendedlearning,usingdigitalresources,andmakingstudentthinkingvisible.

4. Collectively,districtshavenotyetidentifiedappropriatemeasurestojudgeprogressandeffectivenessofmovingtowardspersonalizedlearningpractices.

a. However,theleadingCatalystdistrictsreportfocusingmoreonimprovingsocialandemotionallearning,studentwell-being,andstudentautonomy.

5. MostdistrictshavesufficientWANandLANcapacitytoscalepersonalizelearning,butsignificantinvestmentinexpandingaccesstocomputingdevicesisstillrequired.

a. Only303(16%)ofschoolsmeetallthreecriteria(LANcapacity,WANcapacity,deviceaccess)tobedeemedreadytoscalepersonalizedlearning.

b. Almosthalfofschools,however,havesufficienttechnicalcapabilitiestointroducepersonalizedlearningpractices.

AllMASchoolsDistricts

UrbanNetworkDistricts

MAPLEConsortiumDistricts

MAPLECatalystsDistricts

Rural/CESDistricts

#Schoolsat1:1devices/student

303(16%)

71(12%)

96(32%)

45(43%)

21(25%)


391(21%)

146(25%)

73(25%)

35(34%)

13(16%)


227(12%)

62(11%)

28(9%)

14(13%)

7(8%)

Totalschoolswith3:1deviceratiosorbetter

921(49%)

279(49%)

197(67%)

94(90%)

41(49%)

6. Thereisanequitygap:Ourdisadvantagedstudentsaremostlikelytobeinschoolsleastpreparedtechnicallyandotherwisetobeabletoexperiencepersonalizedlearning.

a. Urbandistricts,withthehighestproportionofdisadvantagedstudents,areleastpreparedtechnicallyduetodevicelimitations.Only11.5%ofstudentsinurbandistrictsareinschoolsdeemedreadytoscalepersonalizedlearning.

b. Meanwhile,43%oftheschoolsinourCatalystgroup,largelysuburbanandbetter-resources,arereadytoprovidetheirstudentswithpersonalizedlearningopportunities.

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AbouttheMAPLEConsortiumTheMassachusettsPersonalizedLearningEdtechConsortium(MAPLE)Consortiumisapublic-privatepartnershiptofurtheranddeepenthegrowthofpersonalizedlearninginK-12publicschoolsintheCommonwealth.LearnLaunchInstitutepartnerswiththeMassachusettsDepartmentofElementaryandSecondaryEducationtocreatethisconsortiumthatisalignedwiththeDepartment'sstrategicprioritiestostrengthencurriculum,instruction,andassessment,andusedataandtechnologytosupportstudentlearningandperformance.

AboutLearnLaunchInstitute

LearnLaunchInstituteisanonprofitdedicatedtobuildingacommunitytodriveinnovationto

transformlearningandincreaseachievement.Oureducationinnovationecosystemmobilizes

educators,entrepreneurs,learners,investors,andindustryaffiliates.

ThevisionforMAPLEistoaccelerateandscaleuppersonalizinglearning,enabledbytechnologyinK-12publiceducation.MAPLEconnectsschoolswithnecessaryresources–astrongpeerlearningcommunity,professionallearning,digitaltools,fundingstrategies,andanemergingevidencebase–tocreatethoughtfulandinnovativenewmodelsofteachingandlearningtoimprovestudentengagementandachievement.

AboutMAPLE

MassachusettsPersonalizedLearningEdtech(MAPLE)Consortiumisapublic-privatepartnership

tocatalyzepersonalizedlearningintheCommonwealthwiththepurposeofbetterpreparingALL

studentsfortheirfuture.

MAPLEaimstobringcoherencetothepresentconstellationofeffortsbyconnectingK-12schooldistrictsacrosstheinnovationspectrum.Itenablesdistrictandschoolleaderstolearnmorefromeachother,providesinformationaboutresourcesthatstrengthenlocalmodels,andnurturesthediscoveryofnewideasthatsupporttransforminglearningandteaching.MAPLEconnectsandeducatespractitioners,allowingthemtodiscovernewinsights.Italsoaimstoprovideanimportantforumonpersonalizinglearningtobuildpublicwillandpolicyleadership.KeyGoals

§ MapthecurrentlandscapeofpersonalizedlearningmodelsinK-12Massachusettsdistricts,identifygapsandenergizesolutionstofillgapsacrossthespectrumofmodels.

§ ConnectK-12districtsacrosstheinnovationspectrumtolearnfromeachother,provideresourcesthatstrengthenlocalmodels,andnurturethediscoveryofnewideastotransformlearningandteaching.

§ Mobilizepublicdemandforpersonalizedlearning,demonstratetheefficacyofmodelsofpersonalizedlearning,andultimatelybringpersonalizedlearningenabledbytechnologytoscaleinMassachusetts.

FormoredetailonMAPLE,visitthewebsiteathttp://learnlaunch.org/MAPLE/

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MaptheCurrentLandscapeThisLandscapeAnalysisreportmapsthecurrentlandscapeofpersonalizedlearninginK-12Massachusettsdistricts.Itbeginstoinventorypractices,andapproachesthatsupportpersonalizedlearningintheCommonwealth.ThisJuly2017reportprovidesapreliminaryattempttounderstanddistrictreadinessandprogressonthepathwaytopersonalizinglearning.MAPLEwillcontinuetoexpandupontheseinitialfindings.

MAPLECatalystandGeneralMemberDistricts

MAPLEincludesK-12schooldistrictsacrosstheinnovationspectrum,classifyingthedistrictsintothreecategories:Catalyst,General,andNon-member.MAPLEcurrentlyhas31memberdistricts,includingbothCatalystandGeneral,thatinclude160,592students.ThisrepresentsaboutoneofsixstudentsinMassachusetts.Memberdistrictsare43%African-AmericanandHispanic,comparedto28%African-AmericanandHispanicinthestateasawhole,and39%arefromeconomicallydisadvantagedhomescomparedto29%inthestateasawhole.Figure1.31MAPLEMemberDistricts

The14CatalystMemberDistrictsaremostengagedandstrategicallycommittedtopersonalizedlearning.TheyareableandwillingtosharetheirsuccessfulpracticesandchallengeswithotherMassachusettsdistricts.CatalystDistrictssignanMOU,agreeingtobeveryactivecontributorsandlearnersintheMAPLElearningcommunitythatsupportsallMassachusettsdistrictsinmovingforwardwithpersonalizinglearning.

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GeneralMembersDistrictsareinterestedinseeingworkingmodels,learningwhatpedagogies,strategies,andtechnologiesaresuccessful,andparticipatinginalearningcommunity,butarenotyetfullycommittedtopersonalizinglearningatthedistrictlevel.MAPLEMemberDistricts,bolddenotesCatalystMemberDistrict

Andover Duxbury Millis RCMaharArlington FallRiver Natick RevereAttleboro Fitchburg Needham SomervilleBeverly GreaterLawrence

TechNewBedford Springfield

Brockton Groton-Dunstable NorthReading WalthamBurlington Harvard Orange Wareham

Chelsea Lexington Petersham WestfordConcord MAVirtualAcademy QuaboagRegional

MAPLEPartnersMAPLEreceivessupportfromavarietyofpartnersforthoughtleadership,professionallearningopportunities,research,andfunding.Partnersinclude:

• ThoughtleaderssuchasTheLearningAccelerator,theClaytonChristensenInstitute,HighlanderInstitute,andNovemberLearning;

• Professionalorganizationssuchasthestateassociationsforsuperintendents,schoolcommittees,curriculumdevelopment,andeducationaltechnology(MASS,MASC,MASCD,andMassCUE);

• SchoolsupportandtechnicalassistanceorganizationssuchastheCenterforCollaborativeEducation,NextGenerationLearningChallenges,EdElements,FableVision/ReynoldsCenter,andNESummitLearning;

• ResearchersathighereducationinstitutionssuchasHarvardCPREandMITOfficeofDigitalLearning;

• ProductandserviceproviderssuchasFutureReadyandFridayInstitute.MAPLEPersonalizedLearningDefinedPersonalizedlearningseekstoacceleratestudentlearningbytailoringtheinstructionalenvironment—thewhat,when,howandwherestudentslearn—toaddresstheindividualneeds,skillsandinterestsofeachstudent.

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Figure2.MAPLEDefinitionofPersonalizedLearning

Withinaframeworkofestablishedcurriculumstandardsandhighexpectations,personalizedlearningmotivatesstudentstoreachtheirgoals.Studentstakeownershipoftheirownlearninganddevelopdeep,personalconnectionswitheachother,theirteachersandotheradults.Theeffectiveuseoftechnologybolsterspersonalizedlearningactivitiesbyprovidingstudents,teachersandadministratorswithcustomizedinformationaboutstudentlearninginordertoguideinstructionalpracticesandscalepersonalizedlearningaffordablyandefficiently.Effectiveuseoftechnologyallowsteachersandstudentstofocusmoreoncreativity,criticalthinking,andcollaboration.TheMAPLEdefinitionofpersonalizedlearningconsistsof6elements:

1. PersonalConnections–Personalizedlearningsupportsdeeppersonalconnectionsbetweenstudents,teachersandotheradultsinordertofosterlearning.

2. PersonalLearningPathways-PersonalLearningPathwaysareneededsothateachstudentwillfeelmotivatedtoreachtheirgoalsandtakeownershipoftheirlearning.

3. Competency-basedProgression-Personalizedlearningincludesworkingwithinaframeworkofcurriculumstandardsandhighexpectations.

4. LearnerProfiles-Personalizedlearningprovidesteacherswithdetailedandtimelyknowledgeofstudentlearningtoguideinstructionalactivitiesandstrategies.

5. FlexibleLearningEnvironments-Thewhat,when,how,andwhereoflearningisflexibleandresponsivetoindividualstudentneeds.

6. EffectiveTechnology-Technologiesusedareeffective,affordable,scalable,andsupportPLstrategiesandgoals.

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PersonalizedlearningisseenasanimperativeifMassachusettsistoclosethesignificantpoverty-basedachievementgapinstudentlearning.TheStateboastsafirstplacerankingin4thand8thgradereading,butranksatalmostthebottom–48th–intermsofthepoverty-basedachievementgap.1Byfocusingonstudentlearningneeds,flexiblelearningenvironments,andeffectivetechnology,personalizedlearningwillgreatlyreduceachievementgaps.Personalizinglearningisalsoseenasessentialtopreparingstudentsforthe21stcenturyjobmarket.A2016surveybytheMassachusettsBusinessAllianceforEducationfoundthat75%ofemployersreportdifficultyhiringemployeeswiththerightskills,and72%ofbusinessleadersagreethatschoolsneedtochangetomeetworkforceneeds.2LandscapeAnalysis:GoalsandMethodologyThislandscapeanalysisfocusesontakingasnapshotofpersonalizedlearningpracticesandrelatedcapabilitiesthroughouttheCommonwealthofMassachusettstoserveasaguideforfutureMAPLEprogramming,identifyingschoolexemplarstosharesuccessfulpractices,providingabaselinetodevelopmetricstomeasurepersonalizedlearningimplementations,andinformingpublicdiscussionsabouteducationalpriorities.GoalsoftheLandscapeAnalysis

1. GuidefutureMAPLEprogrammingbyidentifyinggapsandpainpointsforschoolsacrossthestateastheyworktoimplementpersonalizedlearningwithintheirdistricts.Thisisnotspecifictotheuseoftechnology,butratherinvestigateswhatdistrictsaredoingineachrealmthatisrequiredtopersonalizelearningforstudentsincludingstaffdevelopment,useoftechnologyandadministratorinvolvement.

2. Determine“brightspots”thatdistrictsareproudofandviewasworkingwelltouseas

exemplarsforschoolstobetterunderstanddifferentaspectsandstrategiesforimplementingpersonalizedlearningeffectively.ThesebrightspotsmaybeidentifiedfromCatalystDistrictsthataregenerallyfurtheraheadinimplementingpersonalizedlearning,butalsofromgeneralornonmemberdistrictsthathaveidentifiedstrategiesthattheythinkareworkingwelltopersonalizestudentlearning.

3. Establishbaselinemetricsthatcanbeusedtomonitorprogressonpersonalizedlearning

implementationsovertimewithintheCatalystandGeneralMemberDistricts,andalsoacrossthestate.Thisincludesabetterunderstandingofwhatmetricsschoolsarecurrentlytrackingandwhereschoolsfallwithintheseidentifiedmetrics.

1EducationWeekResearchCenter(2016).MassachusettsStateHighlights.CalledtoAccount:NewDirectionsinSchoolAccountability.Available:http://www.edweek.org/media/ew/qc/2016/shr/em16shr.ma.h35.pdf2TheMassIncPollingGroup.(September20,2016).Mass.businessleadersfocusonrealworldskills,goodteachers.Available:https://www.mbae.org/2016-ma-employer-survey-on-education-and-workforce-readiness/

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4. Identifygapsinthetechnicalpreparednessofschooldistrictstobeabletoimplement

personalizedlearningmodelsforallstudents.InadditiontoinformingMAPLEprogrammingandidentifyingemergingbrightspotsofinnovationinMassachusettsdistricts,thislandscapeanalysiswillbeusefultoorganizationsinterestedinsupportingthereformingofteachingandlearningpracticesinMassachusettstobetterpreparingallstudentsfortheirfutures.Hence,theseinitialfindingsarebeingsharedwiththeMassachusettsDepartmentofElementaryandSecondaryEducation,MAPLEfunders,andMAPLEpartners,suchastheMassachusettsBusinessAllianceforEducation,theMassachusettsAssociationofSchoolCommittees,andtheMassachusettsAssociationofSchoolSuperintendents.LandscapeAnalysisMethodologyThelandscapeanalysisbeganwiththedesignofthestudyinFebruary2017,andthecollectionofdatainMarchthroughJune2017.Thelandscapeanalysisstudywasguidedbythreekeyquestions:

4. WhatistheprevalenceofpersonalizedlearningpracticesinMassachusettsschooldistricts?

5. Whatistheprevalence,depth,anddescriptionofpersonalizedlearningpracticesinthe14CatalystMemberdistricts?

6. WhatistheleveloftechnicalinfrastructureandavailabilityofdevicesinMassachusettspublicschooldistricts?

Inordertoanswerthelandscapeanalysiskeyquestions,datawascollectedfrommultiplesources,qualitativeandquantitative,usingthreemethodsandsources.Thethreestrandsinclude:(1)in-depthfocusgroupinterviewsandconversationswithCatalystDistrictsabouttheirpathtopersonalizedlearning,(2)astatewidepersonalizedlearningsurveyofleadersineachschooldistrict,and(3)atechnicalinfrastructureassessmentcollectedbytheMassachusettsStatewideBuildingAuthorityin2016.Theresearchmethodologiesandsourcesofeachstrandaredescribedbelow,withmoredetailinAppendixA.LandscapeStudyMethodology.

StatewidePersonalizedLearningSurvey

InAprilallsuperintendentsacrossthestatereceiveda10-15-minutesurveywithinstructionstoidentifyandpassthesurveyontobeansweredbytheappropriatestaffpersonintheirdistrict.Ofthe404districts,76districtsparticipatedinthesurveybetweenApril11andJuly6,2017.Thisrepresentsan18%rateofreturn.ThirtypercentofMassachusettsstudentsarerepresentedinthesurveyresponses.

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Themapbelow,Figure3,indicateswhichdistrictsparticipatedinthesurvey. Figure3:DistrictsthatParticipatedintheStatewideSurvey

Thegoalwastoreacha30%responserate.Togarnermoreresponses,thesurveycompletionduedatewasextendedtwice.However,thedemographicsoftherespondingdistrictsaresimilartothedemographicsofthestate.

CatalystFocusGroupInterviews

AqualitativestudyusingfocusgroupswasconductedwiththegoalofmoredeeplyunderstandingwhatschooldistrictshavebeendoinginordertoimplementpersonalizedlearninginMassachusetts.Fivefocusgroupstookplacefrommid-March2017tomid-April2017.Theywereconductedwith14CatalystDistricts,with2to4districtspresentateachfocusgroupdiscussion.Districtsincludedinthefocusgroupswere:Andover,Arlington,Beverly,Burlington,Concord-Carlisle,Duxbury,Millis,Natick,Needham,NorthReading,Revere,Somerville,Wareham,Westford.Eachfocusgrouphadavarietyofpeoplepresent,fromsuperintendentstodigitalleadersandteachersfromdistrictschools,andallparticipantshadtheopportunitytosharetheirexperiencesandideasaboutpersonalizedlearning.Intotal,thirty-eighteducatorsparticipatedinthefocusgroupdiscussions.Thefocusgroupquestionswereopen-endedandtheconversationswerewide-ranging,puttingcontexttotheissuesthatarosefromthestatesurveywhichwassentoutaroundthesametimeperiod.Thesamefivequestionswereaskedineachfocusgroupsession.Thequestionswere

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designedtounderstandhowmuchmulti-yearplanningforpersonalizedlearningistakingplaceacrosseachdistrictdistrict;whatmeasuresofsuccesshavebeenarticulated;howdistrictsareidentifyingstudentgoals,strengthsandweaknesses;whatisneededtofurthereffectivepersonalizedlearning;andifhiringplansincorporaterecruitingforpersonnelwithexperienceinpersonalizedanddigitallearning.

StateTechnicalInfrastructureStudy

MAPLEwasgivenearlyaccesstothe2016surveyresultsof1881MassachusettsschoolsdonebytheMassachusettsSchoolBuildingAuthority.Thissurvey,donelargelyin-person,isrepeatedeveryfiveyears,andisthebestsourceofbuilding-leveltechnicalinfrastructureavailable.However,asitwasdonein2016anddistrictsarecontinuouslyupgradingtheirtechnicalinfrastructure(andespeciallybuyingneworreplacementdevices),theMADepartmentofElementaryandSecondaryEducationaugmentedthisstudy.ThequestionsonthesurveyinstrumentusedbytheMSBAcanbefoundinAppendixD.Inaddition,asthedevicedataisthemostdynamic,theMAPLEteamhasreviewedalldevicedatawithitsCatalystDistrictmembers,andwillcontinuetoupdatedevicedataforothermemberdistricts.

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StatewideSurveyHighlightsTheMAPLEPersonalizedLearningStatewideSurveywassenttoSuperintendentsandAssistantSuperintendentsinallMassachusettsschooldistricts.Theshortsurveycoveredthefollowingareas:

• Teachingandlearningpracticesindistrictclassrooms• Professionaldevelopmenttosupportpersonalizationoflearning• Districtrolesthatsupportteachersintheirclassroomstopersonalizelearning• Platformsinusetosupportpersonalizationoflearning• Criticalneedstoacceleratethepersonalizationoflearningintheirschools

StudentLearningExperiencesThefirstquestionontheMAPLEStatewideSurveywasdesignedusingtheHighlanderInstitute,PersonalizedLearningProgression,2017.(SeeAppendix--)togaugetheteachingpracticesinuseinthedistrict.Eachsub-questionisacharacteristicintheprogressionfromTraditionalInstructiontoFullyPersonalized,aseitheroccurring:Always,Often,Sometimes,orNever.Theintentistodeterminewhereontheprogressiontopersonalizedlearningeachdistrictmightbe.Therearethreekeytakeaways.

1) Basedonthe(Highlander)progressionofPL,thereisalotofprogressyettobemadeinmostMAschooldistricts.Thechartindicatesthattraditionalteachingpractices–samecontentforallstudentsdeliveredatthesamepace,andwhole-classteacher-ledinstruction,aredominantacrossMassachusettsschools.

- 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0100.0

Leveledcontent/RTIModel

Teacher-ledsmallgroupsrotations

Whole-classteacher-led

Similarcontentatsamepace

Always Often Sometimes Never

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However,mostdistrictsreportsomelevelofpersonalizationoftheirteachingpractices,with24/7learningbeingthemodalitymostfrequentlyreportedas“Always”or“Often.”Examplesofthiswouldbeonlineclassesforspecialoradvancedtopics,blendedlearningclassrooms,andinternshipsandapprenticeshipsoutsideofschool.Moreadvancedpersonalization,suchasstudentsprogressingindividuallywhilepracticingskillsingroupsbasedonreal-timeformativeassessmentdata,aremuchlesscommon.

2) OnthreeindicatorsofPersonalization,Catalystdistrictsarefurtheralonginmomentsofprogressionthanotherdistricts.InCatalystdistrictsitismorelikelytohavepeertopeercoachingandevaluationdriveinstructionandgrouping,morelikelytoengagein24/7learningusingdigitalresources,andmoreliketoplacegreateremphasisonreal-worldlearningchallenges.Thefirsttwomaybearesultofthesedistrictshavingmoreyearsandresourcestoexperimentwithintegratingtechnologyintoteachingandlearning.

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0%8%

0%

25%

50%

25%33% 33%

58%

25%

0% 0%0%

10%

20%

30%

40%

50%

60%

70%

Peertopeercoachingandevaluationdriveinstructionandgrouping.

Studentsexperience24/7learninginandoutoftheclassroomusingdigitalresources.

Studentsareabletoexperiencereal-worldlearningchallengesthroughinternshipsandotherauthentic

experiences.

WhereareCatalystDistrictsdifferent?(Catalysts)

ALWAYS OFTEN SOMETIMES NEVER

3% 2% 2%9%

18% 18%

69%62%

68%

18% 18%12%

0%10%20%30%40%50%60%70%80%

Peertopeercoachingandevaluationdriveinstructionandgrouping.

Studentsexperience24/7learninginandoutoftheclassroomusingdigitalresources.

Studentsareabletoexperiencereal-worldlearningchallengesthroughinternshipsandotherauthentic

experiences.

WhereareCatalystDistrictsdifferent?(AllOtherResponses)


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3) OnotherindicatorsofPersonalization,Catalystdistrictsarenotmuchdifferentwithregardtointegratingpersonalizationininstructionasdistrictsinthesurveyoverall.Thedatashowsonlyslightdifferencesinintegratingself-pacedandblendedlearningopportunitiescomparedtoallotherdistricts.Thisfindingseemscounter-intuitiveandmayreflectconfusionoverthedefinitionsofthecategories,orlimitsofconductingthesurveyviadistrictcentralofficesratherthanschoolprincipals.

0% 0% 0% 0%8% 8%

0%

25%

58%42%

58% 58%

17%33%

25%

0%0%

10%20%30%40%50%60%70%

Studentsprogressindividuallythroughmoretargetedonlinecontentwhiledynamic

(constantlychanging)groupspracticeskillsface-to-facewithinstructorsandwithpeers.

Individualizedonlineinstructionissupportedbytutoring,check-ins,conferencing,and

coaching.

Studentsprogressbothonlineandofflineindividuallyandattheirownpace.

Studentsareabletoexperiencereal-worldlearningchallengesthroughinternshipsand

otherauthenticexperiences.

Personalization(Catalysts)


0% 3% 2% 2%9% 11% 9%

18%

66% 62%58%

68%

25% 25%31%

12%

0%

20%

40%

60%

80%

Studentsprogressindividuallythroughmoretargetedonlinecontentwhiledynamic

(constantlychanging)groupspracticeskillsface-to-facewithinstructorsandwithpeers.

Individualizedonlineinstructionissupportedbytutoring,check-ins,conferencing,and

coaching.

Studentsprogressbothonlineandofflineindividuallyandattheirownpace.

Studentsareabletoexperiencereal-worldlearningchallengesthroughinternshipsand

otherauthenticexperiences.

Personalization(AllOtherResponses)


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PersonalizedLearningInitiativesandHopesRespondentswereaskedanopen-endedquestiontogetattheconstraintsontheirabilitytomigratemorequicklytopersonalizationoflearningexperiencesfortheirstudents:“Whatisoneimportantprobleminyourdistrictthatyouthinkashifttowardmorepersonalizedlearningmightsolve?Whatwouldbemosthelpfultobetterimplementpersonalizedlearninginyourdistrictinthenearfuture?”Respondentslistedwhatwouldbemosthelpfultobetterimplementpersonalizedlearningintheirdistrictinthenearfuture.Thelistandfrequencyofthetoprequestsshowsthatteacherprofessionaldevelopmentsignificantlyexceedsotherneeds,andFunding/Time,andseeingpersonalizedlearninginaction(whichisalsoaformofprofessionaldevelopment),arealsohighonthelist.Note:Thefullanalysisofthisquestionisstillunderconsideration.

0 5 10 15 20 25

Other

Infrastructure/TechResources

CultureChange

Education- SeeingPLinAction

FundingandTime

TeacherPD

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ProfessionalDevelopmentRespondentswereasked“Whatareexamplesofprofessionaldevelopmenttopicsthatarecurrentlyofferedtoteachersoradministratorstosupportpersonalizinglearning?”Thisquestionaimedtounderstandifandhowteachersaresupportedthroughprofessionaldevelopmenttopersonalizelearning.Also,todeterminewhichPDtopicsaremostcommonlyofferedinsupportofpersonalizedlearning.

Catalystdistrictsaredemonstratingawiderscopeintheirprofessionaldevelopmentfocusthanallotherdistricts.75%ofCatalystdistrictsarereportingaprofessionaldevelopmentemphasisonBlendedLearning,whileonly28%ofallotherdistrictsarefocusingonthistopic.Thismaybeattributedtothetechnologyavailablewithinindividualdistricts,butalsohighlightstheCatalystdistrict’semphasisonprofessionaldevelopmenttosupportintegratingnewtechnologies.Catalystdistrictswere23%morelikelytofocusondevelopingaculturethatsupportsinnovation,27%morelikelytofocusonopeneducationresources,and21%morelikelytofocusonUniversalDesignforLearning.Althoughthesenumbersmaynotseemsignificant,whencomparingthistoprofessionaldevelopmenttopicsconnectedtostateaccountabilityandimprovementstandards,itisclearthatCatalystsareplacingagreateremphasisoninnovation.Forexample,SocialEmotionalLearning,DigitalLiteracy,andDataDrivenInstructionareconnectedtostatepoliciesonaccountabilityandimprovement,andCatalystsareplacinganalmostequalemphasisonthesetopics.

0%20%40%60%80%

100%

ProfessionalDevelopmentFocus

AllOtherDistricts CATALYST

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MeasuringProgresswithPersonalizedLearningRespondentswereasked“Howdoyoumeasuresuccess?Indicatethemetric(s)belowforwhichyougatherdatatoinformstudentsuccess.”Thisquestionaimedtounderstandthedifferentmeansbywhichdistrictsmeasuretheirownsuccessinachievingtheirgoals,includingtheusesofstandardizedtestresults,behavioralmeasure,andsurveys.WewerealsointerestedtoseeifthesemetricsdifferedbetweenourCatalystdistrictsandrespondentsmoregenerally.Whenlookingatmeasurementsforstudentsuccessacrossallcategories,itappearsasthatallotherdistrictsareplacingalargerfocusonaccountabilitydataascomparedtodataonstudentlearning.WhenlookingatAccountabilityData,improvinggradesandtestscoresarereportedtobealargerfocusinotherdistrictsthaninourCatalystdistricts.ThisisnotsurprisingasourCatalystdistrictsaremostlymadeupofschoolsatlevels1and2,andsodonotneedtofocusasaggressivelyonstate-mandatedaccountabilitymeasures.Catalystdistrictsareplacingmoreemphasisonmeasuringsocial-emotionallearningandwell-beingthanallotherdistricts,andstudentengagementandautonomyarealsobeingweighedatgreaterratesthanintheotherdistricts.

0%10%20%30%40%50%60%70%80%90%

Blendedlearning Usingopeneducationalresources Understandingbydesignoruniversaldesignforlearning

Makingstudentthinkingvisible Developingaculturethatsupportslearningandinnovation

WhatarecatalystdistrictsfocusingonmoreforPD?

AllOtherDistricts CATALYST

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SupportFunctionsforPersonalizedLearningThegoalofthisquestionwastounderstandwhatrolessupportpersonalizinglearninginschools.Morespecifically,howaretheelementsofPLbeingsupportedbypersonnel.Weprovidedalistofsupportfunctionsandaskedrespondentstochoosethetitleofthepersonwhoperformsthatfunctiononaregularbasis.Alldistrictsareleveragingavarietyofpositionstopushforwardwithinnovation.Nooneroleismoresupportiveofpersonalizinglearning.Districtsaremostlikelytorelyonbuildingadministrators,curriculumdirectors,andinstructionalcoacheswhensupportingteachingandlearning.ThestructuresofCatalystdistrictsneedtobefurtherexaminedtodistinguishtheirworkfromotherdistricts.Itis,however,probablylikelythatedtechspecialistswhomightbemoreprevalentinCatalystdistricts,arehelpingwithassistivetechnologyandtechtoolsforinstructionmorethananyothergroup,whilerealtimedatatoguideinstructionandlearningissharedbybuildingadministratorsandcurriculumdirectors.

0%20%40%60%80%

100%

Improvedcoursecompletionrates

Improvedgraduationrates

Improvedacademicgrades

Improvedacademictestscores

Improvedstudentattendance

Lowerdisciplinaryreferrals

Improvedparentorstudentsatisfactionasmeasuredbysurveys

MeasuringSuccessThroughAccountabilityData

allotherdistricts catalysts

0%

20%

40%

60%

80%

Improvedsocial/emotionallearning

Improvedstudentwellbeing Improvedstudenttimeontask

Improvedstudentconduct/behavior

Greaterstudentengagement Greaterstudentautonomy

MeasuringSuccessThroughStudents

allotherdistricts catalysts

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CatalystFocusGroupInterviewHighlightsThereareavarietyofrichandinformativetakeawaysandconsiderationsfromeachofthefocusgroupquestions.Fivefocusgroupsmet,includingtwotofourdistrictsateachsession.Intotal,thirty-eightCatalystdistrictandschoolleaderscontributedtothesediscussions.Manyofthesediscussionhighlightsrepresentimportantconsiderationsforprogramminggoingforward.(Foradditionaldetail,see:AppendixB1-FocusGroupQuestions;AppendixB2–FocusGroupChart)

Takeaway#1:MostCatalystDistrictshavestrategicplansthatincludepersonalizedlearningelements,butonlyafewhavecomprehensiveplans.

“ThekeydesignprincipalsbehindchangesinRevereareour‘FourPillars’ofstudent

learning–PersonalizedLearning;Competency-basedlearning;Anytime,Anywhere

Learning;andStudentOwnership.”-Revere

“Personalizedlearningispartofourapproachtohowwedoteachingandlearning…

everythingisonacontinuumandwecontinuetodeepenthedifferentpiecesof

personalizedlearningaspartofourdifferentinitiatives…it[PL]isapartofourcore

instructionalvalues.”-Natick

InadditiontoprovidingMAPLEwithageneralunderstandingofwhatplansarecurrentlyinplacewithinCatalystmemberdistricts,thequestionalsoshedlightonthelevelofdetailbeingpaidspecificallyto“personalizedlearning”asdefinedbyMAPLE,ineachoftheparticipatingdistricts.ThemajorityofCatalystdistrictsdonothavespecificplansforpersonalizedlearning,butratherincludeelementsthatconnecttopersonalizedlearning,suchasstudentengagement,technologyimplementation,orsocialemotionallearningwithintheirdistrict-levelimprovementplans.MostplansintheCatalystdistrictsareprogressing.Specifically,28%(4)ofdistrictsintervieweddescribedanexemplarphasewithpersonalizedlearningexplicitlyembeddedinamulti-yearplanwithactionsteps.Onedistrictwasfoundtobe

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inthebeginningphaseoftalkingaboutpersonalizedlearning,whilefiveofthedistrictsweredeterminedtobeinaprogressingphase,(beginningtousecomponentsofpersonalizedlearninginplans).Beginningandprogressingphasedistrictshavenotexplicitlyembeddedpersonalizedlearninginamulti-yearplanorarticulatedactionsteps.Planningforpersonalizedlearningformostdistrictsconsistedofhavinga“suiteofinnovations”thatwerenotyetexplicitlyembeddedinamulti-yearplan.Thissuiteincludedelementsofpersonalizedlearningsuchasfosteringstudentengagementorinstitutingtechnicalrequirementsthathadbeenscopedoutasdriverstowardssupportingpersonalizedlearning.Catalystdistrictleadersparticipatinginfocusgroupsindicatedthefollowingconsiderationsareimportantwheninstitutingpersonalizedlearningplans:1. Emphasizetheimportanceofsuccessforallstudents.Therewas100%agreementamong

administratorsthattheyneedtobeexplicitthat“allstudentsmeansallstudents.”Administratorscitedconcernsaboutsignificantachievementgapsandequityissueswithstudentsintheirdistricts.

“Wewanttohelpfacultyunderstandwhypersonalizedlearningissoimportant...”-

Somerville

2. Clearlydefinepersonalizedlearning.Themajorityofadministratorsagreedthatthereisa

needtofirstdefinetheterminologyassociatedwithcreatingamorepersonalizedlearningenvironmentbeforecreatingaplantospecificallyaddressidentifiedcomponents.36%ofadministratorsspecificallycitedthisneedtodefineterminologysurroundingpersonalizedlearningbeforemovingforwardwithaplanforhowtoachievemorepersonalizedlearning.

“Toconvincinglycreateaplanandgetbuy-inforit,beginbydefiningtheterminology

associatedwithpersonalizedlearning.”–Natick

3. Developandnurtureteacherearlyadoptersasleaders.50%ofadministratorsinterviewedcitedteacherleadershipascriticaltomakingprogresswithpersonalizedlearninggoals.Severaldistrictleadersreferencedearlyadopterteacherleadershipascritical.Inleadingdistricts,earlyadoptereducatorsaregiventheopportunitytoserveonaninnovationteam,whichprovidesastructuredteacherleadershipopportunityandthechanceforteacherstosupportotherteacherswithinthedistrict.

4. Developconsistentimplementationthroughprofessionaldevelopment.Themajorityof

administratorsinterviewedalsohighlightedaneedtoworkwithfacultytohelpformacohesiveunderstandingoftheintendedwork.36%ofdistrictscitedformal&informalprofessionaldevelopmentascriticaltomakingprogressinpersonalizedlearning.ProfessionalLearningCommunities(PLCs)werementionedasmosthelpfulinfosteringteacherdevelopment.

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5. Developanimplementationtimelinewithflexibilitytomanageworkloads.Manyadministratorsemphasizedtheneedforcreatinganimplementationtimelinewhenestablishingaplan,andtoprovideopportunitiesforre-evaluatingandadjustingthetimelineannuallytocreatemanageableworkloadsforimplementationteammembers.Cleargoalsandshortcyclesforspecificworkcansupportimplementationactivitiesthatmaketherolloutofnewideasmoremanageable.Administratorsreportedvaryinglengthsoftimelinesthatrangedfrom2to5yearsandrecommendedthatspecificactionstepsbeclearlydefinedandcommunicatedtostakeholderswithongoingdiscussionsofprogressmade.

Thepaceatwhichwe’rerunning[ourplan]isbasedaroundhowwecanresourceit.We

wanttobepracticalandproperlysupportourinstructionalstaff.”-Somerville“Ourstrategicplanwaswrittenin2011,tobeaworkingdocumentfor2012-2017…It

wasaveryvisionaryplanthatledtothediscussionswe’rehavingnow.”-Duxbury

Takeaway#2:MostCatalystDistrictstrackstudentlearningandachievement,butspecificPersonalizedLearningmetricshavenotbeenidentified.

Asafollow-uptohavingdistrictadministratorsreportontheirplansrelatedtoimplementingpersonalizedlearningacrossthedistrict,participantswerealsoaskedtoreportonthemetricsbeingusedtotrackthesuccessoftheirplans.Withthegoalofdeterminingwhichmeasuresarebeingtrackedorwhichmetricsaregoingtobetrackedinthefuture,administratorsweregiventheopportunitytosharethestatusofpersonalizedlearningdatacollection.Administratorsreportedthatalthoughmanyofthedistrictsareusingsurveystomeasurestudentandparentengagementandmanydistrictsareactivelytrackingacademicindicatorsofprogressthroughavarietyofelectronicplatforms,nodistrictshavedeterminedmetricsspecifictopersonalizedlearning.Otherusefulinformationdiscussedaboutcurrentdatatrackingpracticesanddatauseincluded:• Districtsleadersreportedactivelytrackingacademicindicatorsofprogressthroughavariety

ofelectronicplatforms.71%ofdistrictsareusingavarietyofdatatoidentifyareaswherestudentsarestruggling.

• Districtsleadersreportedthattheiradministratorsandteachersareprimarilyusingdatatoinforminstruction,trackimprovements,monitorstudentprogress,andidentifydistrictneeds.Themajorityofdistrictsareusingsomeformdatatodriveinstruction;and50%ofdistrictsareusingdatatotrackimprovementsalongatrajectoryofexistinginitiatives.

• Usingsurveystocollectdataisacommonstrategyforcollectingdatabyschooldistricts.93%

ofdistrictsreferencedsurveyingstaff,64%ofdistrictsreferencedsurveyingstudents,and

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14%ofdistrictsreferencedsurveyingthecommunity.Manyleadersreportedusingtechnologyplatformsforsurveyingandcollectingdata.

Takeaway#3:CatalystDistrictsfacecertainbarriersintrackingstudentdatatoinformPersonalizedLearning.

Someadministratorscitedalackofsystemsfortrackingstudentdatatoinformpersonalizedlearning,asassessmentsandfeedbackfrompersonalizedlearningendeavorscanbedifficulttoquantify.Furthermore,bothmoneyandtimeposebarrierstoextensivedatacollection,especiallywhenthedatacollectionismostappropriatelyundertakenbyteachers.Ingeneral,administratorsreferencedchallengesrelatedtocurrentdatatrackingactivitiesaswellaspotentialchallengeswithestablishingandtrackingdatarelatedtopersonalizedlearning.Quantifyinganecdotalevidence,notoverburdeningteachersandotherstaff,anddeterminingappropriatemetricsmakedatatrackingchallenging.Inparticular,identifyingusefulmetricsforpersonalizedlearningischallengingbecauseofthedifficultyincharacterizingandquantifyingcomponentsofpersonalizedlearning.InordertobetterunderstandhowMAPLECatalystDistrictsareusingstudentdataandinformationtodrivepersonalizedlearning,districtadministratorswerealsospecificallyaskedhowtheirdistrictgathersstudentinformation—fromcollectingandstoringstudentinformationtoensuringthatthisdatafollowsstudentsthroughgrade-leveltransitions.Thefocuswasondetermininghowdistrictsgettoknowtheirstudents’goals,aspirations,interests,strengthsandweaknessesincludingidentifyingwhowasinchargeofthistypeofinformationandwhereitwashoused.Districtadministratorsreportedthattherearenumerousbarriersthatmakethemeaningfulcollectionofthisongoingstudentdatadifficult,andthatusingongoingstudentdatatodrivepersonalizedlearningisinfrequentlyoccurringatthispointintime.Resourcechallengesincludingtimeandstaffmakeformalcollectionofstudentdatadifficult,eventhoughitisacknowledgedasimportant.Whilesomeadministratorsremarkedthatstudentinformationsystems,suchasAspenX2,haveprovidedahelpfulelectronicplatformthatmakesgeneralstudentinformation(grades,attendance,standardizedtestscores)readilyavailable,ithasbeendifficulttofindwaystostoreandpassonstudentinformationthatislessnumericalandmoreholistic.Someschoolshavefoundthatadvisoryprogramsorbuilt-inflex-blocksareusefulinensuringthatallstudentshavetheabilitytoformmeaningfulrelationshipswithteachersandotheradultswithintheschooltobetterunderstandstudentneeds.Otherschooldistrictleaderscitedstudent-createdportfolios,projectbasedlearning,andconferencingatthebeginningandendoftheschoolyearasdevicesforsharingthiskindofholisticstudentinformationinawaythatisrelevantandmeaningfultofurtheringpersonalizedlearningactivities.

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Thefollowinginformationwasalsogatheredandhelpstobetterunderstandthecurrentlandscapeandthechallengesexperiencedbydistrictadministratorsincollectingusefulinformationaboutstudentstohelpinformpersonalizedlearningstrategies:

• Only14%ofadministratorsinterviewedmentionedthatteachersspecificallyuseddatatopersonalizelearning.

• Advisoryprogramsandconferencingareusedtoformrelationshipsandbetterunderstandstudentstrengthsandweaknesses.28%ofdistrictscitedleveragingadvisoryprogramstosupportstudentneedsand57%ofdistrictsleveragestudent-teacherconferences,buttheydosoindifferentcapacitiesandfordifferentpurposes.

• 100%ofdistrictscitedschoolcounselorrecordkeepingasaprimaryfacultyandadministratorresourceforcompilingandsharingstudentdatawithinthelimitationsofconfidentiality.

• 50%ofdistrictscitedhavinganelectronicdatabaseforstoringstudentdata,althoughmostdistrictsuseacombinationofelectronicdataresources,teacher-to-teacherconferencing,andstudent-teacherconferencingtocollectstudentdata.

Takeaway#4:BarrierstoPersonalizedLearningincludeasignificantneedforpersonalizedprofessionaldevelopment.

Focusgroupparticipantswereaskedtodescribethemostacuteneedtheyseeintermsoffurtheringtheeffectiveuseofpersonalizedlearningwitheducatorswhoarenotearlyadopters.Thegoalofthisquestionwastohaveparticipantsself-identifybarrierstopersonalizedlearningandtogainaclearerunderstandingofwhatresourcesdistrictsmightneed.

“BepreparedtoincludesignificantPDforpersonalizedlearningforallteachersand

administrators.MakesuretomakethePDitselfpersonalized.”-Beverly

Themajority(70%)ofdistrictscitedaneedformoretailoredprofessionaldevelopmentaswellasdevelopingwaystobuildteacherbuy-inassignificantbarrierstoimplementingpersonalizedlearning.Districtadministratorsspecificallymentionedaneedtopersonalizeprofessionaldevelopmentinawaythatwouldallowforteacherstogetamorecustomizedexperience.Manydistrictsmentionedexistingmentoringandcoachingprogramswithintheirdistricts,andsomedistrictscitedjob-embeddedprofessionaldevelopmentcoachingashelpful.Ofnotewastheneedforcustomizedprofessionaldevelopmentthatcouldaddresstheneedsofdifferentaudiences:teacherearly-andlate-adoptersandprincipalshavedifferentlearningneeds.Tobringaboutchangeattheschoolandclassroomlevel,job-embeddedprofessionaldevelopmentwithcoachingandaccesstoPersonalLearningCommunities(PLCs)wasseenaspotentiallyeffective.Buy-in,intermsofchangingmindsets,andboostingmotivationwereseenasavenuestobeaddressedtobringaboutchangefromallparticipants.

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Anadditionalbarrierdiscussedby43%ofadministratorswasstatepolicyregardingcontentstandardsandtesting.Manydistrictadministratorsremarkedthatalthoughtheirteachersareencouragedtotakeriskswithnon-traditionalassignmentsandpersonalizedlearningactivities,manyteachersindicatethattheyfeellimitedbystatestandardsandtheneedtoteachspecificcontentfortesting.43%ofadministratorsmentionedthatbecauseteachersfeelpressuretohavestudentsdowellonstateassessmentsmuchofthefocusintheclassroomaddressesthisgoalratherthandeeperlearninggoals.Introducingcompetency-basedlearningwithinastatestandards-basedframeworkcanbeadifficult“sell”toteachersandprincipals.Communitysupportincludingparentsandstudentswasalsoacomponentmentionedbyseveraladministrators.Educationaboutexpectationsandhelpingparentsandstudentsunderstandthevalueofpersonalizedlearningassignmentsthataredissimilartotraditionalhomeworkneedstobeapartofanypersonalizedlearningimplementation.Themajorityofdistrictadministrators(63%)citedtimeconstraintsasabarrier,bothintermsoffindingtimeintheschooldayscheduletoallowteachersenoughroomtotakeonmorecomplexlessons,aswellastimeconstraintswithregardtoprovidingteacherswithprofessionaldevelopmentopportunities.Themajorityoffocusgrouprespondentsindicatedthatmovementtowardsimplementingpersonalizedlearningrequiresapersistentandsteadypacewhileatthesametimefiguringouthowtoallottimeforactivitiesrelatedtopersonalizedlearningincludingdatacollectionandreviewinordertoensurethatstaffdonotfeeloverburdened.

Takeaway#5:PersonalizedLearningisnotexplicitintheCatalystDistricthiringprocess.

InordertobetterunderstandwhetherornotpersonalizedlearninganddigitallearningareintegratedintotalentrecruitmenteffortsofMAPLEdistricts,focusgroupparticipantswereaskedtodescribetheirhiringandrecruitingplans.Mostdistricts(71%)citedcomfortandexperiencewithtechnologyasaquestionforpotentialnewhires,withthegoalofhiringindividualsthatwereopento,orhadexperiencewith,usingtechnologytoimprovestudentoutcomes.Whilenodistrictscitedaclearrecruitingplanoutsideoftheirstandardprocessofpostingjobsandinterviewingcandidates,somedistricts(28%)referencedhiringrubricsthatincludereferencestoelementsofpersonalizedlearningsuchasgrowthmindsetandopennesstolearningnewpractices.Thefocuswasnotontechnicalskills,buttohavingapositiveattitudetowardeducationaltechnologygenerally.

AlthoughspecificattentiontopersonalizedlearningwasnotfoundinthemajorityofMAPLEdistrictshiringpractices,manydistrictsdidreferenceonboardingprogramsfornewhiresthatincorporateelementsofpersonalizedlearningintotheirinductionplans.Somedistrictadministratorsreferencedpartneringwithlocalhighereducationinstitutionstooffernewhires,andsomeadministratorsreportedcomingupwithcreativeonboardingprogramsthatmodelthepersonalizedinstructionnewhiresareexpectedtoimplementintheirclassrooms.

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Takeaway#6:ThereisalottolearnfromemergingPersonalizedLearningbrightspots.TheCatalystInterviewFocusGroupshelpedidentifywhatfactorsdefineabrightspotandwherethereareemergingbrightspots.OneoftheoverallgoalsofthelandscapeanalysisistoidentifyemergingbrightspotsinMassachusetts.Atthispoint,itisapparentfromtheFocusGroupinterviewsthatmostoftheCatalystdistrictshavepersonalizinglearningpracticesthatareworthwhiletohighlightasemergingbrightspots.Andover,Millis,Revere,andNatickhaveembeddedpersonalizedlearningstrategiesinmulti-yearplansthatincludeactionsteps.Natickadministratorsdescribedanimpressivesuiteofinnovationsthatexplainedhowcomplicatedandmulti-facetedimplementingpersonalizinglearningisinpractice.Byidentifyingtheseearlyleaders,MAPLEwillcontinuetoprovidesupporttomovealltheCatalystdistrictstothenextlevel,whilefocusingonmakingsureallthedistrictsintheMAPLEnetworklearnaboutthepromisingpracticesandarebettersupportedtoforgeaheadimplementingwhatcouldworkintheirowncontexts.

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StateDataonInfrastructureGoalsoftheTechnicalAnalysisforPersonalizedLeaningReadinessThegoalofthispartoftheMAPLELandscapeAnalysisforPersonalizedLearningistolookatthestateoftechnicalpreparednessforschoolsacrosstheCommonwealthtobeabletoofferpersonalizedlearningexperiencesforalltheirstudentsthroughouttheschoolyear.Inotherwords,whatschoolsaretechnicallycapabletousepersonalizedlearningpracticesastheirprimaryapproachtoteachingandlearning?AllMAschoolshaveinvestedsignificantsumsinWiFi,WANcapacityincludingfiberconnectionstotheInternet,andinvariouskindsofcomputingdevicesinthelastcoupleofyears.Theseinvestmentshavebeendrivenbystatemandates(e.g.tosupportonlinedeliveryofMCAS),byteacher-driveninitiativestoincorporatemoretechnologyintotheirpractices,bydistrictstrategicplanstohelpstudentspreparefor21stCenturycareers,andmore.Buttheseinvestmentsdonotnecessarilyleadtohavingsufficienttechnicalcapabilitytosupportalarge-scalereplacementoftraditionalclassroompracticeswithonesthatarepersonalizedtotheneedsofallstudents.Forthis,technologysolutionsneedtobebothabletosupportabroadsetofstudentexperiencesaswellasprovideteachersandadministratorsthedataandtoolstoadequatelyknowwherestudentsareandofferthemappropriatelearningchallenges.ThispartoftheMAPLELandscapeAnalysisisanattempttomeasurethegapbetweenwhatschoolsneedtobefullypersonalizedandwheretheyaretoday.DefinitionsForschoolstobefullypreparedtoofferallstudentspersonalizedlearningexperiencesatastandardpractice,theymustbereadyonthethreedimensionsofInternetbandwidth,LANcapacity,anddeviceavailability.InternetReadiness/FiberReady:UsingtheMSBAsurveyquestion“Doestheschoolhaveafiberconnection?”asthekeyconsiderationfordeterminingreadinessalongthisdimension,thisquestionwasthencheckedandverifiedwithinformationaboutthedistrictse-rateparticipation,andbytheDepartment’sdirectcontactwiththedistrict.Seetablebelow.LANCapacity/WiFiReadiness:TheMSBAsurveyquestion“DoestheschoolhaveaLANcapableofdelivering1Gbpsinsidetheschool?”wasusedasthekeyconsiderationandwasaugmentedwithinformationaboutdistrictparticipationintheDigitalConnectionsPartnershipSchools(DCPS)grantprogram,aswellasbytheDepartment’sdirectcontactwiththedistrict. Internet/FiberReady

Yes

▪ Schoolsanswering“Yes”totheMSBAquestion,“Doestheschoolhaveafiberconnection?”forwhichESHhasverifiedaretakingfiberserviceviaE-ratedataordirectconsultation

▪ Virtualschools(i.e.,GCVS,TECCA)

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No

▪ Schoolsanswering“No”totheMSBAquestion,“Doestheschoolhaveafiberconnection?”

▪ Schoolsanswering“Yes”totheMSBAquestionforwhichESHverifiedareconnectedtobutnottakingfiberservice

WiFi/LANReady

Yes

▪ Schoolsanswering“Yes”totheMSBAsurveyquestion,“DoestheschoolhaveaLANcapableofdelivering1Gbpsinsidetheschool?”

▪ SchoolsthatreceivedaDCPSgrantinrounds1a,1b,or2▪ SchoolsindistrictsESE/ESHhaddirectcommunicationswith(e.g.,Boston,Duxbury,

Cambridge,etc.)▪ Virtualschools(i.e.,GCVS,TECCA)

No▪ Schoolsanswering“No”totheMSBAquestion,“DoestheschoolhaveaLANcapable

ofdelivering1Gbpsinsidetheschool?”MASchoolsReadytoScalePersonalizedLearningOnly303,or16%,ofMAschoolsinthesurveyappearreadytomovetowardsafullypersonalizedteachingandlearningapproachintermsoftechnicalpreparedness.Theseschoolsarethosethatoursurveyresearchindicatesare“Fiberready,”“WiFiready,”andhavea1:1studenttodeviceratio.ManymoreschoolshavesufficientWANandLANcapacityandareonlylackingsufficientcomputingdevicestofullypersonalizetheirpractices.Almosthalf,921outof1881,oftheschoolsinthesurveyfallintothecategoryofhavingonedeviceforatleasteverythreestudentswhilehavingsufficientLANandWANcapacitytosuggesttheyareclosetobeabletoscalepersonalizedlearningfortheirstudents.TheseschoolsarenotdistributedevenlyacrosstheCommonwealth.The14MAPLECatalystdistrictshave45schools–43%oftheirtotal–thatarepreparedtoscale,evidenceofthetechnologyinvestmentstheyhavebeenmakingthelastfewyears.Ontheotherendofthespectrum,only71(12%)schoolswithinthe574schoolsinlargeurbandistrictsmeetourcriteriaforbeingreadyforpersonalizedlearningatscale.AsalmosthalfoftheUrbanNetworkschools(279or49%)meetthecriteriaforLANandWANcapacity,themostsignificantlimitingfactoracrossthisnetworkisintheareaofsufficientdevices.

AllMASchoolsDistricts

UrbanNetworkDistricts

MAPLEConsortiumDistricts

MAPLECatalystsDistricts

Rural/CESDistricts

#SchoolsReadyat1:1

303(16%)

71(12%)

96(32%)

45(43%)

21(25%)

#SchoolsReadyat2:1or3:1

618(33%)

208(36%)

101(34%)

49(47%)

20(24%)

Totalat1:1to3:1deviceratios

921(49%)

279(49%)

197(67%)

94(90%)

41(49%)

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Ourproxyforruraldistricts,theCESdistricts,lagbehindthegenerallysuburbandistrictsintheMAPLEConsortiumbutarefurtheraheadthanourlargesturbandistricts.Intermsofminimalreadiness,withonedevicefor3orfewerstudents,theseruraldistrictsareroughlyonparwiththestateoverall. AStarkContrast:MAPLECatalystDistrictsvs.UrbanNetworkDistrictsThetableaboveisonewaytoseethecontractsbetweenMAPLE’slargestandmostdisadvantageddistricts,thoseintheUrbanSuperintendentsNetwork,withthebetter-resourceddistrictsintheMAPLECatalystgroup,whicharemoregenerallysuburban.Anotherwaytoseetheirrelativetechnicalpreparednessisinthescatterplotbelow,whichplotsthe26urbandistrictsagainstthe14Catalystdistricts(with2districts,RevereandSomerville,incommon),ontwoofthethreedimensionsoftechnicalreadinessforpersonalizedlearningatscale:WiFireadinessanddevicereadiness(1:1).The(blue)Catalystdistrictsarefoundtohavearound90-100%WiFireadiness,butwithawiderangeintermsofdevices–from0%foratwoto100%forAndover.ButtheUrban(red)districtsaregroupedinthetwolowercorners–7ofthe25withbothWiFianddevicereadinessbelow40%,withLawrenceandWorcesterbeingtheleasetechnicallyprepared,andmostoftherestabove80%intermsofWiFireadinessbutlessthan30%intermsofdevicereadiness.Springfieldrepresentsanexception,at66%devicereadinessand100%WiFireadiness.

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TheViewAcrossAllMassachusettsSchoolsThetablebelowshowsthestateofthe1881schoolsintheMSBAsurveyacrossallthreedimensions–Internetcapacity,LANcapacity,anddeviceavailability.Mostschools(85%)areInternet-ready,andalmostasmanyhavesufficientLANcapacityaswell.Thereisasignificantdrop-offwhenitcomestodevices,however,withonly21%ofschoolshavingsufficientdevicestooffereverystudentadeviceatalltimes.Perthenoteabove,thisnumberislikelytounderstatetherealsituation,asschoolsarebuyingneworreplacementdevicesonaregularbasis.

CategoryofTechnicalReadinessAllMASchools

(1881)

Internetbandwidth(“FiberReady”) 85%

LANcapacity(“WiFiReady”) 79%

Deviceready(1student/device) 21%

Library/CafeteriaWiFi 68%

Minimaldevicereadiness(3students/device) 66%

AsstudentsworkingontheirownonadevicewilloftenwanttoaccessInternetresourcesoutofclass,thislandscapeanalysisalsoincludesananalysisofwhichschoolshaveinvestedinaddingWiFiaccesspointsinlibrariesandcafeterias.Asoflate2016,68%ofschoolsreportedhavingWiFiavailableinthesecommonareas.Thissuggeststhattheneediswell-recognized,althoughmoretechnologyinvestmentisstillneededtoprovidebothfullcoverageandgoodperformance.TheViewAcrossSchoolsintheMAPLEConsortiumThetablebelowcontraststhestateofthe296schoolsinour31MAPLEConsortiumdistrictswiththewholepopulationof1881schoolsintheMSBAsurvey.AstheMAPLEdistrictsareself-selectedasbeingveryengagedwithmovingtowardspersonalizedlearningforallstudents,itisnotsurprisingthattheyaregenerallyfurtheralongintermsoftechnicalpreparednessthanthestateasawhole.


(1881)MAPLESchools

(296)MAPLECatalystSchools(104)

Internetbandwidth(“FiberReady”) 85% 94% 96%

LANcapacity(“WiFiReady”) 79% 90% 95%

Deviceready(1student/device) 21% 35% 45%

Library/CafeteriaWiFi 68% 65% 71%

Minimaldevicereadiness(3students/device)

66% 72% 96%

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AlmostallMAPLEschools(94%)areInternet-ready,andasmanyas90%havesufficientLANcapacityaswell.Likethelargerpopulationofschools,thereisasignificantdrop-offwhenitcomestodevices–35%ofMAPLEschoolsversusonly21%ofschoolsthroughoutthestatehavesufficientdevicestooffereverystudentadeviceatalltimes.Whenweloosenourstandardto3studentsperdevice,72%ofMAPLEschoolshavesufficientdevicestohaveoneperthreestudentsorbetter,anditispossiblethisnumbercouldbegreaterthan80%whenMAPLEmemberdistrictdevicedataismorethoroughlycollectedandanalyzed.Thelastcolumnpullsoutthe14CatalystDistrictschools,104overall,asthedatasuggeststhatthesedistrictsaresignificantlyaheadofthestateintermsoftechnicalreadinessforpersonalizedlearningatscale.NearlyallschoolsarereportedtohavetheLANandWANcapacityrequired.Furthermore,45%oftheirschoolshaveenoughdevicesfor1:1,andalmostall(96%)havesufficientdevicesfor3:1.WhilethesefourteendistrictsarenotrepresentativeofwhereMassachusettsisintermsoftechnicalpreparationforlarge-scalepersonalizedlearning,theydosuggestwheretheCommonwealthneedstogettoinordertofulfillthepromiseofpersonalizedlearningforallstudents.TheViewAcrossSchoolsinUrbanSuperintendentsNetworkThetablebelowcontraststhestateofthe574schoolsinthe26districtsthatcomprisetheUrbanSuperintendentsNetwork∗withthewholepopulationof1881schoolsintheMSBAsurvey.ThesenotonlythelargestMAPLEdistricts,butgenerallyhaveahighproportionofdisadvantagedstudents. Thesedistrictshavebeensuccessfulatgettinghigh-speedInternetaccessinplace,with94%beingFiberReadyasoftheendof2016.High-capacityWiFi/LANisalsoinplacein76%oftheseschools,aboutonparwiththestateoverall.Thenumberofdevices,however,telladifferentstory:only15%oftheschoolsinthesedistrictshavesufficientdevicesfor1:1,andat61%,schoolswitha3:1orbetterstudent:deviceratiolagsbehindthestate.Whilethesenumbersmightbeunderstatedforthereasonsmentionedearlier,theydostronglysuggestthaturbandistrictswillcontinuetoneedtofocusonacquiringdevicesiftheyaretobeabletoofferpersonalizedlearningexperiencesforallstudentsinalloftheirclasses.TheCatalystdistricts,whichincludetwomembersoftheUrbanSuperintendentsNetwork(Revere,Somerville),areleadingthewayintermsofdevicedeployment,andtheurbandistrictsasagrouphavemuchcatchinguptodo.ItisworthnotingthatRevere,whichstartedtofocusonpersonalizedlearningoversixyearsago,hasimplemented1:1programsinthehighschoolandmiddleschools,andoffersabout2:1deviceprogramsintheelementaryschools.

∗Boston,Brockton,Cambridge,Chelsea,Chicopee,Everett,FallRiver,Fitchburg,Framingham,Haverhill,Holyoke,Lawrence,Leominster,Lowell,Lynn,Malden,NewBedford,Pittsfield,Quincy,Revere,Salem,Somerville,Springfield,Taunton,Worcester.

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(1881)UrbanNetworkSchools(574)

Internetbandwidth(“FiberReady”) 85% 94%

LANcapacity(“WiFiReady”) 79% 76%

Deviceready(1student/device) 21% 15%

Library/CafeteriaWiFi 68% 62%

Minimaldevicereadiness(3students/device) 66% 61%

FiberReady:ThedatashowsthatthestateofFiberReadinessistypicallyuniformacrossadistrict’sschools,sothe94%readinessfortheUrbanNetworkisacombinationofdistrictswhere100%ofschools(possiblywiththeexceptionofPre-Kschools)areready,andotherdistrictswherefewschoolsareFiberReady.Asoftheendof2016,thedistrictsstillbehindinthisareawereChelsea,Malden,andQuincy.WiFiReady:ThedataforWiFiReadinessacrosstheUrbanNetworkisnotasbimodalasitiswithFiberReadiness,buttherearestillalimitednumberofdistrictsarebehindinthisarea.Theseincludethethreementionedabove(Chelsea,Malden,andQuincy),aswellasEverett,FallRiver,Lawrence,Leominster,Lynn,andWorcester.Ofthe124schoolslistedasnotWiFireadyacrossthesedistricts,fully43areinWorcester,21areinLawrence,and20areinLynn.TheViewAcrossSchoolsRural/CESDistrictsMAPLEreliesonapartnershipwiththeNorthhamptom,MA-basedCollaborativeforEducationServes(“CES”)tofunctionasaproxyforMassachusettsruraldistricts.The34districtsthatcompriseCEShave84schoolsintheMSBAsurvey,withatotalenrollmentofonly24,473,orabout281studentsperschooland720studentsperdistricts.Someofthesedistrictsarequitelargegeographically,andsotheypresentdifferenttechnologychallengesthanourdenselypopulatedurbancenters.Thetablebelowcontraststhestateofthe84schoolsintheCESdistrictswiththewholepopulationof1881schoolsintheMSBAsurvey.WhileLANcapacityisonparwiththestateoverall,anddevicereadinessmodestlyaheadofthestate,theseruraldistrictsareattimeschallengedtogethigh-bandwidthaccesstotheInternet.Thiscanbeseeninthefactthatonly75%ofCESschoolsaredeemedFiberReady,vs.85%forthestateoverall.Thedevicepictureisinteresting.Whilethereisadrop-offinreadinesswhenitcomestodevicesascanbeseenacrossallsegments,34%ofCESschoolsversusonly21%ofschoolsthroughoutthestatehavesufficientdevicesfor1:1,andfully77%haveenoughdevicestohaveoneperthreestudentsorbetter.ThesenumbersputthesedistrictsonparwithMAPLEdistricts.

35


(1881)CES∗Schools(84)

Internetbandwidth(“FiberReady”) 85% 75%

LANcapacity(“WiFiReady”) 79% 77%

Deviceready(1student/device) 21% 34%

Library/CafeteriaWiFi 68% 71%

Minimaldevicereadiness(3students/device) 66% 77%

∗CES=CollaborateforEducationalServices,basedinNorthampton.Memberdistrictsare:Amherst,Amherst-Pelham,Belchertown,Chesterfield-Goshen,Conway,Deerfield,Easthampton,Erving,FranklinCounty,Frontier,Gill-Montague,Granby,Greenfield,Hadley,Hampshire,Hatfield,Hawlemont,InstitutionalSchools,Leverett,MohawkTrail,NewSalem-Wendell,Northampton,Northampton-Smith,Orange,PioneerValley,RCMaher,Rowe,Shutesbury,SouthHadley,Southampton,SunderlandWare,Westhampton,Whately,andWilliamsburg.

36

LandscapeAnalysisNextStepsThisLandscapeAnalysisReport,July2017,isafirstattempttocaptureanindicationoftheprevalenceofpersonalizinglearninginpractice.UltimatelythesuccessoftheMAPLELandscapeAnalysiswillbethatitprovidesinformationto:

1. GeneratetakeawaysandprogrammingimplicationsforMAPLE2. identify“brightspots”ofpersonalizedlearningpracticestosharewithdistrictsacrossthe

Commonwealth3. MeasurepersonalizedlearningoutcomesinMassachusettsschooldistricts4. setabaselinelevelofprevalenceofpersonalizedlearninginMassachusettsschool

districts5. Identifytechnologygapsthatmustbefilledtoensureallstudentsareabletotake

advantageofpersonalizedlearningopportunities6. Supporteffortstostrengthenpublicunderstandingandsupportforpersonalizing

learningForthiscurrentstudy,someofthemeasuresofperceptionaboutteacherpracticeandstudentexperiencearebasedonapersonalizinglearningprogression(Highlanderinstitute)thatwasnotspecificallydesignedorfine-tunedasameasurementtool,butthistooliscurrentlybeingrevisedandimprovedforresearchpurposes.Also,forthisfirstLandscapeAnalysisReport,therearegapsinsurveyresponsesontheStatewidesurvey,andN=76,whichis~18%ofMassachusettsdistricts.Althoughthatmaybedemographicallyrepresentativeofthestate,thissurveymayhavemissedimportantvariationsintheprevalenceofpersonalizinglearningstatewide,especiallysinceruraldistrictsareunderrepresented.Also,areviewoftheresultswithMAPLEmembersalsosuggeststhatthequalityofthedatawillimproveifitiscollectedattheschoollevelratherthanthedistrictlevel.TheMSBAtechnologysurveyprovidesabaselinetousewithdistrictsacrossthestate.Itwillmakesensetoverifyandupdatethistechnologyinformationasadditionaldistrictsjointhenetwork.TheprogressofMAPLEdistrictsimplementingpersonalizedlearningwillbeupdatedeachyearbasedonthisLandscapeAnalysisinitialandsubsequentlyupdatedresearchdesignandtools.Therefore,thismethodologywillbeimprovedforthenextroundofdatacollection.

37

Appendices

AppendixA:MethodologyAppendixB1:StatewideSurveyQuestionsAppendixB2:HighlanderInstituteProgressionofPersonalizedLearningAppendixC1:FocusGroupQuestionsAppendixC2:FocusGroupChartAppendixD:MSBASchoolSurveyTechnologyQuestions

38

AppendixA.LandscapeStudyMethodologyDataCollectionMethodsandSources

DataCollectionMethod Population SampleSize(N) Timing

MAPLEFocusGroupInterviews(1.5hr-2hrs)

CatalystTeamMembers

38Membersfrom14Teams*

March-April2017

MAPLEStatewideSurvey(10-20mins)

MassSchoolDistricts

76

April-June2017

MSBATechnicalInfrastructureDistrictSurvey(Fall2016)

MassSchoolDistricts

404

Fall2016

*CatalystDistrictTeamsinclude:Andover,Arlington,Beverly,Burlington,Concord,Duxbury,Millis,Natick,Needham,NorthReading,Revere,Somerville,Wareham,WestfordPurposesoftheLandscapeAnalysisaretoprovide:

1. informationforprogramdesign,includingidentifyingstrengthsinMassachusettsdistrictsthatare“brightspots”,andgapsinlearningandimplementationthatareofhighpriorityneedsformemberdistricts;

2. aninitialbaselineunderstandingabouttheprevalenceofpersonalizedlearninginschooldistricts;

3. measuresofprogressgoingforward;4. informationovertimeabouttheprevalenceandimprovementofpersonalizedlearning

inordertohelpmobilizeastrategyforstrengtheningpublicwillforpersonalizedlearninginthestate;

5. fundersandinvestorswiththeinformationtheyneedtocontinuetosupportthegrowthofpersonalizedlearninginMassachusettspublicschooldistricts.

SuccessofthisLandscapeAnalysiswillbetoprovideinformationthat:

1. generatestakeawaysandprogrammingimplicationsforMAPLE2. identifies“brightspots”ofpersonalizedlearningpractices3. measurespersonalizedlearningoutcomesinMassachusettsschooldistricts4. setsabaselinelevelofprevalenceofpersonalizedlearninginMassachusettsschool

districts5. supportseffortstostrengthenpublicwillforpersonalizinglearning6. garnerscontinuedinvestmentbyfundersforMAPLE

ImplementationoftheMAPLEConsortiumandtheprogressofdistrictsimplementingpersonalizedlearningwillbeevaluatedeachyearbasedonthisinitialandsubsequentlyupdatedresearchdesignandtools.So,thismethodologywillbeimprovedforthenextroundofdatacollection.Itisproposed,forexample:FocusGroupinterviewscouldbeextendedtoincludetheMAPLEGeneralmembers;thequestionsontheStatewidesurveycouldbefine-tunedtoretrieveclearerinformation,aswellasbeingextendedtoincludealargernumberofdistricts;andtheTechnicalInfrastructuresurveymightbeanalyzedagainstmorerobustinformationaboutthetechnicalrequirementsforthespectrumofpersonalizinglearningimplementations.Limitations:

• Thesetoolsandquestionsareafirstversionattempttocaptureanindicationoftheprevalenceofpersonalizinglearninginpractice.

• Themeasuresofperceptionaboutteacherpracticeandstudentexperiencearebasedonachartdescribingapersonalizinglearningprogressionthatwasnotspecificallydesignedorfine-tunedasameasurementtool.

• GapsinsurveyresponsesontheStatewidesurvey,maybedemographicallyrepresentativeofthestate,buttheymayhavemissedimportantvariationsintheprevalenceofpersonalizinglearningsinceN=75,whichis~18%ofMassdistricts.

Appendix B1: Statewide Survey Questions Question 1 – Student Learning Experiences Select one option for each type of student learning experience that tells how often it occurs in your district. ‡ *This question is required.

Select one option for each type of student learning experience that tells how often it occurs in your

district.‡ *This question is required. Neve

r Sometimes Ofte

n Always

Teacher-centered instruction is delivered to the whole class at the same time.

Students progress through similar content at the same pace.

Teacher-driven instruction is delivered to smaller groups at rotating intervals in the day.

Students progress through leveled content in high, medium, and low groups using benchmarking and summative data (RTI model).

Targeted instruction is delivered to smaller groups and individuals at various times in the day supported by curated online content.

Students progress individually through more targeted online content while dynamic (constantly changing) groups practice skills face-to-face with instructors and with peers.

Individualized online instruction is supported by tutoring, check-ins, conferencing, and coaching.

Students progress both online and offline individually and at their own pace.

Students experience 24/7 learning in and out of the classroom using digital resources.

Lessons always have a next step designed to build on skills, so students are never "finished."

Mastery is demonstrated through performance-based assessments and higher order thinking applications.

1

Peer to peer coaching and evaluation drive instruction and grouping.

Students are able to experience real-world learning challenges through internships and other authentic experiences.

‡Characteristics drawn from © Highlander Institute, Personalized Learning Progression, 2017. Question 2 – Functions Performed Below is a list of functions that might be performed in your district. For each function, choose the title of the person who performs that function on a regular basis. If a particular function is not applicable, leave blank.

Below is a list of functions that might be performed in your district. For each function, choose the title of the person who performs that function on a regular basis. If a particular function is not applicable,

leave blank.

Title of person(s) who perform this function

most of the time

Help teachers/students individualize student learning based on students’ specific strengths and needs, student interests, and/or individualized goals.

Help teachers/students use digital tools to integrate face-to-face instruction with online learning.

Help teachers/students use real-time data to guide instruction/learning.

Help teachers/students build structures that allow for students to advance to new content based upon mastery, not seat time.

Support accessibility and/or assistive technology in the classroom.

Respond to technical support needs in the classroom.

Question 3 – Professional Development What are examples of professional development topics that are currently offered to teachers or administrators to support personalizing learning?

● Developing a culture that supports learning and innovation ● Data-driven instruction ● Making student thinking visible ● Socioemotional learning, self-regulation, or mindset

2

● Understanding by design or universal design for learning ● Mastery-or competency-based assessment practices ● Project-based learning ● Blended learning ● Co-teaching ● Digital literacy ● Using open educational resources ● Setting up flexible learning environments ● Piloting educational software or hardware ● Evaluating educational software or hardware ● Other - Write In Please enter an 'other' value for this selection

Question 4 – Learning Platforms Do you have, or expect to acquire, any of these learning platforms to enable your teachers to more easily personalize learning?

Do you have, or expect to acquire, any of these learning platforms to

enable your teachers to more easily personalize learning?

Currently Using

Exploring Using

Previously Used

Not Considering

Blackboard (Edline)

Brightspace (Desire2Learn)

Buzz/Agilyx

Canvas

Cortex

Google Classroom

Gooru

ITS Learning

Moodle

Schoology

Summit

3

Question 5 – Personalized Learning Initiatives and Hopes What is one important problem in your district that you think a shift toward more personalized learning might solve? *This question is required. What would be most helpful to better implement personalized learning in your district in the near future? *This question is required. Please provide 1-3 examples of personalized learning in your district for which you are particularly proud. Question 6 Measuring Success How do you measure success? Indicate the metric(s) below for which you gather data to inform student success.

● Improved course completion rates ● Improved graduation rates ● Improved academic grades ● Improved academic test scores ● Improved social/emotional learning ● Improved student well being ● Improved student time on task ● Improved student conduct/behavior ● Greater student engagement ● Improved student attendance ● Lower disciplinary referrals ● Improved parent or student satisfaction as measured by surveys ● Greater student autonomy ● Other - Write In Please enter an 'other' value for this selection

4

Micro DifferentiationTraditional Instruction

Teacher-centered instruction is delivered to the whole class at the same time

Students progress through similar content at the same pace

To move up a level, districts must begin leveraging data to develop small group instructional plans within larger content blocks

To move up a level, districts must begin using formative assessment systems across skill and subject areas to differentiate content and pacing. To move up a level, districts

must switch from teacher-centered to student-centered instruction through self-paced learning and personalized content To move up a level, districts

must support personalized content and delivery for each student by offering students voice and choice around what and how they learn.

To maintain this level, districts must support a culture of continuous individualization and redesign organizational structures to accomodate for individual student pathways.

Teacher-driven instruction is delivered to smaller groups at rotating intervals in the day

Students progress through leveled content in high, medium, and low groups using benchmarking & summative data (RTI model)

Targeted instruction is delivered to smaller groups and individuals at various times in the day supported by curated, online content

Students progress individually through more targeted online content while dynamic (constantly changing) groups practice skills face-to-face with instructors and with peers

Individualized online instruction is supported by tutoring, check-ins, conferencing, and coaching

Students progress both online and offline individually and at their own pace

Students experience 24/7 learning in and out of the classroom

Lessons always have a next step designed to build on skills, so students are never “finished.”

Macro Differentiation Individual Mastery Fully Personalized

Completely student-driven instruction is achieved by an individualized curriculum where CCSS are acquired through personalized projects that build essential 21st century skills and are designed based on student interests.

Mastery is demonstrated through performance-based assessments and higher order thinking applications

Peer to peer coaching and evaluation drive instruction and grouping.

Students are able to experience real-world learning challenges.

Leveling the Field for All Learners

INST ITUTE© Highlander Institute 2017 | www.highlanderinstitute.orgYou may share this content for non-commercial use provided that you provide appropriate credit.

Personalized Learning Progression

A

Appendix B2

Appendix C1: Focus Group Questions 1: District Implementation and Planning for Personalized Learning

Have you developed a multi-year plan to implement Personalized Learning across the district?

What defines the timeline for how quickly/slowly you plan to move? What is the plan focused

around?

Goal of question: Understand what plans are in place, how detailed they are and what success

looks like.

2: Measurement

What are the measures of success for this plan? What is being tracked today, or planned to be

tracked in the future for different stakeholders - students, teachers, principals, districts?

Goal of question: Learn what is measured in schools today.

3: Information as input into instructional strategy

How and when do you get to “know your students” - goals, aspirations, interests, strengths,

weaknesses? Where is this information kept, and who is in charge of it throughout the

student’s education?

Goal of question: Understand what information is known about the student to inform

personalized learning - Do schools even have the information that is needed to enable PL?

4: Needed support for furthering personalized learning

What is the most acute need you see in furthering the effective use of personalized learning

with teachers who are not early adopters, and for scaling these programs?

Goal of question: Have interviewees self-identify biggest barriers to understand what type of

resources they need.

5: Talent Development

Do you have a hiring or recruiting plan to attract new talent that is interested in personalized

learning or digital learning or who can bring these capabilities to the district? What training do

you provide to educators? Do you feel like this is sufficient for your needs today?

Goal of question: Understand detailed talent development process.

Appendix C2 - Focus Group Chart

1: District Implementation and Planning for Personalized Learning Have you developed a multi-year plan to implement Personalized Learning across the district? What defines the timeline for how quickly/slowly you plan to move? What is the plan focused around? Goal of question: Understand what plans are in place, how detailed they are and what success looks like District PL

planning phase

Timeline for PL planning and implementation

Contributing Factors Identified Critical Points

Millis Exemplar Ends in 2018 Action steps helped define and communicate steps to stakeholders Collaboration with admin to define PL Team of teachers collaborate with Admin to discuss progress

Teacher buy-in

Natick Exemplar Embedded in Instructional Practices

Focus on Deeper Learning Framework Defining terms from INACOL

PLCs are critical to teacher growth Technology as learning tool not teaching tool

Needham Progressing Embedded in District and Building Goals (3 year and annual)

Working on building common definitions District goal includes instructional practices and assessment to improve student outcomes

Adjusting school schedule Coaching teachers

Somerville Progressing Embedded in District Tech Plans

Teachers supporting each other Budget, people, and time have all been necessary

Innovation Specialist position

Revere Exemplar In year 2 of phase 2, second round of 5 year plan

Focus on pedagogy Collaborative work to celebrate and grow pockets of excellence

Teacher-led initiatives HS portfolio requirement

Arlington Progressing Embedded in District Tech Plans

EdTech University Summer PD Linking tech-usage with PD

PD has been critical Identify learning goals for graduates = helped shape vision

District PL

planning phase

Timeline for PL planning and implementation


Duxbury Progressing Embedded in District and Building Goals (3 year and annual)

Working on building common definitions District goal includes instructional practices and assessment to improve student outcomes

PD has been critical Teacher Buy-in

Wareham Beginning Working on buy-in on importance of PL PD has been critical Teacher Buy-in

Concord-Carlisle

Progressing No timeline to complete

1:1 program has moved toward PL Need to shift instructional mindset

Westford Progressing In 5 th year of digital learning vision

Access to devices Needs assessment drove plan

Digital Learning Vision on 4 C’s

Andover Exemplar Strategic Plan and building plans include emphasis on authentic learning

High school has personalization period Emphasis on SEL and personalization Student Resume

Innovation Teams Adjustment to Schedule

Beverly Progressing No plan that articulate PL specifically

Moving from pockets to systematic Teacher led progress @ elementary

Burlington Progressing No plan that articulate PL specifically

Just beginning to get teacher involvement to begin transition

Taking pieces and making them coherent

North Reading

Progressing 5 year plan with some strands of PL

Working on understanding definitions and moving from pockets to larger plan

Leadership retreat to focus on Future Ready

Summary:

● 14 catalyst districts surveyed o 7% beginning phase o 72% progressing o 21% exemplar

● Formal/Informal Professional Development (36%) and Teacher Leadership (50%) have been critical to progress in PL ● Few districts have separate PL plan (14%), many are embedding PL centered plans within District and Building Based Strategic plans ● 36% sited the need to define PL and establish common language

2: Measurement What are the measures of success for this plan? What is being tracked today, or planned to be tracked in the future for different stakeholders - students, teachers, principals, districts? Goal of question: what is measured in schools today District Using

Data to Drive Instruction?

Using Data to track student success?

Using data to track improvements?

Using data to identify needs?

Stakeholders surveyed

Student Staff Community

Millis x x x X Natick x x x x x x Needham Somerville x x x x x Revere X x X X X Arlington X X x x x Duxbury X x x x x x x Wareham x X x x x Concord-Carlisle

X X x

Westford x x x Andover x x X x X Beverly x X Burlington x x X North Reading

x x x x x

Summary:

● 50% using data to drive instruction ● 79% using data to track student success (typically standardized testing and state reporting) ● 50% using data to track improvements (along trajectory of existing initiatives) ● 71% using data to identify district needs ● 14% referenced surveying community as common practice ● 64% reference surveying students as common practice ● 93% referenced surveying staff

3: Information as input into instructional strategy How and when do you get to “know your students” - goals, aspirations, interests, strengths, weaknesses? Where is this information kept, and who is in charge of it throughout the student’s education? Goal of question: Understanding what information is known about the student to inform personalized learning - do schools even have the information that is needed to enable PL

District Getting to Know Students Use of data to personalize learning?

System for storing and carrying over data?

Identified Critical Points Advisory

Guidance

Teacher-Student Conference

Millis x N N Goal in place for creating learner profile Have interest survey for Ss @ SOY

Natick X X X N N Concern over teacher workload, no system in place for learner profiles

Needham X X N N Concern over teacher workload, no system in place for learner profiles

Somerville X X X N Y Partnership with Code for America Revere X X N N Student-teacher relationship Arlington X x Y N PBL used as means to personalize learning Duxbury X N Y Schoology has bones necessary to store and create

learner profiles, but not there yet Wareham x x N Y Advisory program = unknown

Focus on social-emotional Concord-Carlisle x x N Y System for keeping assessment data Westford x N Y Spreadsheets and guidance to store data Andover X x N N New resume should help with global pathways Beverly x X Y Y Responsive classroom at middle & elementary Burlington x N N Freshman academy North Reading x x N Y Friday digital learning rubric

Summary:

● 2 districts mentioned used data to personalize learning, but in different contexts ● 28% cited leveraging advisory to support student needs

● guidance record keeping is primary source for all districts ● 50% cited having system for storing data K-12 ● 57% leverage teacher-student conferences, but in different capacities and for different purposes

4: Needed support for furthering personalized learning What is the most acute need you see in furthering the effective use of personalized learning with teachers who are not early adopters, and for scaling these programs? Goal of question: have interviewees self-identify biggest barriers to understand what type of resources they need

District Resources to

Coach/Support Teachers

Teacher Buy-In State Policy that supports PL

Conflict with High Stakes Assessments

Time

Millis x x Natick x x x x X Needham X x x x Somerville X X X Revere x X x Arlington x X Duxbury x X x X Wareham x x Concord-Carlisle x x X

Westford x X x Andover X x X Beverly x x Burlington x x North Reading x x Summary

● 79% referenced PD resources and support as being critical to move teachers along ● 79% referenced Teacher Buy-In as being critical ● 43% reference state policy as being a barrier for furthering personalized learning ● 21% reference conflicts with high stakes assessments as being a barrier for personalized learning ● 63% referenced time as being critical, acknowledging that movement requires a slow and steady pac

5: Talent Development Do you have a hiring or recruiting plan to attract new talent that is interested in personalized learning or digital learning or who can bring these capabilities to the district? What training do you provide to educators? Do you feel like this is sufficient for your needs today? Goal of question: Understand detailed talent development process

District Technolo

gy Priority PL Priority


Millis Very little turnover Natick X Rigorous process, targeting teachers

comfortable with Tech Needham Looking for growth mindset

Somerville X School Committee goal = recruitment Focus Group research on hiring

Looking for growth mindset

Revere X Career Fair Caring about kids is most important

Looking for growth mindset

Arlington X Sample Lessons Looking for growth mindset Duxbury X Personalizing training for new hires to

model best practice targeting teachers comfortable with Tech

Wareham Concord-Carlisle

X x targeting teachers comfortable with Tech

Westford x X targeting teachers comfortable with Tech Andover Group interviews, collaborative process Looking for people we can learn from Beverly x x Offering coding class for teachers Burlington x Working with higher ed programs will be

crucial to maintaining qualified applicant pool

North Reading x x Group interview model Summary:

● No district cited a clear recruiting plan outside of standard practices ● 71% referenced technology as being a hiring priority with an emphasis on leveraging technology to improve student outcomes ● 28% reference PL as being included in their hiring rubric ● 28% reference growth mindset or language recognizing the need for hires ready to learn new things

DeviceToStudio_Ratio

Internet_Download_Speed

Internet_Upload_Speed

LibaryWifi_YN

CafWireless_YN

GymWireless_YN

ClassroomSufficientPower_YN

AuditoriumWireless_YN

TechInfrastrutureImpact_YN

GbpsWAN_YN

FiberConnection_YN

OnlineStatewideAssessment_YN

HundredKbpsPerStudent_YN

GbpsLAN_YN

MbpsPerStudent_YN

SuffBandwidthPurchase_YN

Data Spreadsheet corresponding headings

2016 MSBA School Survey Technology Data Spreadsheet Legend

Appendix D

MAPLEwouldliketothanktheBarrFoundationandtheNellieMaeEducationFoundationfortheirgeneroussupportindevelopingand

preparingthisreport.

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