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Diagnosis andClusteringOf Dyscalculia ThirdGradeStudents.

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dc.contributor.advisor Shahin, Ghassan
dc.contributor.author Al-Adrah, Dalal
dc.date.accessioned 2018-05-24T10:22:17Z
dc.date.accessioned 2022-05-11T06:33:11Z
dc.date.available 2018-05-24T10:22:17Z
dc.date.available 2022-05-11T06:33:11Z
dc.date.issued 5/31/2017
dc.identifier.uri http://test.ppu.edu/handle/123456789/710
dc.description.abstract Severalstudentssu erfromdyscalculia.Manyresearchandstudieshave beencarriedouttotacklethisproblem.Mostoftheseresearchestriedto identifywhetherastudentsu ersfromdyscalculiaornot,withoutanyfur- ther detailsonthecase.Basedonresultsoftheidenti cation,researchers proposedsolutionsandwaystotreatdyscalculicstudents.Thisresearch tries totacklethedyscalculiaproblemamonggrade3studentsinSouth- ern DirectorateschoolsinPalestine.Theresearchattemptstousearti cial intelligentmethodsandtoolstoclusterstudentsaccordingtotheirdyscal- culia case,andproposedinformationtechnology-basedtreatmentforeach studentaccordingtohis/hercase.Ittriestogoafurtherstepintoidentify- ing whattypeofdyscalculicstudentonsensingnumber.Theapproachused in thisresearchisperhapsthe rsttouseAItoolstocluster;butnotclassify, dyscalculic students,andtriestobreak-downthedyscalculiaprobleminto three majortypesusingthisapproach.Toachievethis,anintensivelitera- ture reviewwascarriedout,thenanexamusedbytheMinistryofEducation and HigherEducationinPalestinewasmodi edandtestedbyexperts.The modi edexamwasappliedtogradethreestudentsatschoolsofbothgen- ders inHebronandYattadirectorates.Resultsoftheexamwerecodedand input toanAItoolRtool.Thetooluseshierarchicaltechniquescluster- ing. Weapplytwohierarchicaltechniquesalgorithms;theSinglelinkand vii WARDmethod.WARDalgorithmisanagglomerativehierarchicalcluster- ing procedure,wherethecriterionforchoosingthepairofclusterstomerge at eachstepisbasedontheoptimalvalueofanobjectivefunction.Single link istechniquelooksinthedistancebetweentwoclusterstobeequaltothe shortest distance.WARDalgorithmshowbetterresultthanSingleLink,af- ter calculatedtheCopheneticCorrelalationCo cient(CPCC).SingleLink is thelowestCPCC,whichis(0.46).ButWardhas(0.7)CPCC.Notonly wastheuseoftheclusteringtodetermineifthestudentisdyscalculicor not asthepreviouswork,butwealsouseWARDalgorithmclusteringmore deeply todeterminewhatkindofdyscalculiaastudenthas.Theresultwas clustered intosevenclusterssuchas(weaknessonthethreeskills,theab- sence ofanyweaknessinthethreeskills,studentswhohavezeromarkinthe exam). Resultsshowdi erencesamonggenderandamongdirectorates,and inconsistency betweenclusteringresultsandstudentsmathachievementin school.Basedontheresultsandtheliteraturereview,amodelhasbeenpro- posedforthetreatmentofdyscalculicstudents,whereitconsistsalsoofthe identi cationandclusteringstage.Themodelwasevaluatedby24experts, and theircommentsandsuggestionwereincorporatedinthemodel. en_US
dc.language.iso en en_US
dc.relation.ispartofseries cd , 30112;no of pages 80 , informatics 1/2017
dc.subject Dyscalculia,Technologies,Intervention,Recommendation en_US
dc.title Diagnosis andClusteringOf Dyscalculia ThirdGradeStudents. en_US
dc.type Other en_US


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