 information (Hood, 2007). Theoretical sampling is different from purposive sampling, but these methods can complement each other. Research can begin with a purposeful selection of the initial sample, and then shift to theoretical sampling when data analysis begins to reveal theoretical concepts (Breckenridge & Jones, 2009). Kenealy and Cartright (2007) described a study that commenced with purposive sampling to recruit 24 participants for interviews. After subsequent data analysis, theoretical sampling prompted the researchers to conduct further interviews in order to develop the abstract concepts. This approach of leveraging both purposive sampling and theoretical sampling was utilized in this qualitative study. Data collection initially proceeded with purposive sampling to select twenty participants who work in educational technology leadership, including district technology directors, and instructional technology resource teachers. Purposive sampling is a form of non-probability sampling that proceeds by selecting subjects according to a pre-defxned criterion (Cozby, 2009). The participants were selected in a nonrandom way, in order to purposefully select participants who have been involved with notable technology initiatives (see next sub-heading concerning the strategy for selecting and recruiting participants). Half of the initial participants were technology directors, so that a strong sample o f district-wide technology leadership would be included in the study. The other half o f the initial participants were instructional technology resource teachers who provide leadership for technology integration, collaborate with teachers, and deliver technology professional development. After beginning with purposive sampling, as data collection and analysis progressed, the process shifted to theoretical sampling to develop the conceptual categories and emerging theory (Charmaz & Henwood, 2008; Stem, 2007). Researchers can use theoretical sampling to seek out participants who have had particular experiences, or in whom particular concepts appear significant (Morse, 2007), in order to gather data related to conceptual categories and their properties (Corbin & Strauss, 2008). During data analysis, the emerging theory prompted the researcher to pursue interviewing additional subjects to build the abstract concepts. The data analysis led to additional data collection, to seek out data from other sources that might be conceptually relevant. Data collection continued until theoretical saturation had been reached, and 31 subjects had participated in the study, including 15 technology directors and 16 instructional technology specialists. Among the 31 participants, there were 17 men and 14 women, from 19 school districts from different geographic areas of the state, including 133 Central Virginia, Southside, Hampton Roads and the Virginia Peninsula, Northern Neck and Middle Peninsula, Northern Virginia, and Southwest Virginia and
information (Hood, 2007). Theoretical sampling is different from purposive sample distribution, but these method can complement each other. Research can get down with a purposeful selection of the initial sample distribution, and then shift to theoretical sampling when datum analysis begins to reveal theoretical concept (Breckenridge & Jones, 2009). Kenealy and Cartright (2007) trace a study that start with purposive sampling to enroll 24 participants for interviews. After subsequent datum analysis, theoretical sample distribution motivate the researchers to conduct further interviews in club to develop the abstract concepts. This approach of leveraging both goal-directed sampling and theoretical sample distribution was utilized in this qualitative study. Data collection initially proceed with purposive sampling to select twenty participants who work in educational engineering leadership, include district technology directors, and instructional technology resource teachers. Purposive sampling is a form of non - probability sampling that proceeds by choose subject according to a pre - defxned standard (Cozby, 2009). The participant were choose in a nonrandom way, in order to purposefully select participants who have been involved with notable technology initiatives (determine next sub - heading concerning the strategy for selecting and recruiting player). Half of the initial participants were technology directors, so that a potent sample distribution oxygen f district - broad technology leadership would be included in the study. The early half o f the initial participants were instructional technology resource teachers who provide leadership for technology integration, collaborate with teachers, and render technology professional exploitation. After beginning with purposive sample distribution, as data collection and analysis progressed, the procedure shifted to theoretical sample distribution to develop the conceptual categories and emerging hypothesis (Charmaz & Henwood, 2008; Stem, 2007). Researchers can use theoretical sampling to seek out participants who have had particular experiences, or in whom particular concepts appear significant (Morse, 2007), in ordering to gather data associate to conceptual categories and their properties (Corbin & Strauss, 2008). During data analysis, the emerging theory prompt the researcher to pursue interviewing additional subjects to build the abstract concepts. The datum analysis led to additional data collection, to seek out data from other reference that might be conceptually relevant. Data collection continued until theoretical impregnation had been reached, and 31 national had participated in the study, including 15 engineering directors and 16 instructional technology specialists. Among the 31 participants, there were 17 men and 14 women, from 19 school district from different geographic areas of the state, including 133 Central Virginia, Southside, Hampton Roads and the Virginia Peninsula, Northern Neck and Middle Peninsula, Northern Virginia, and Southwest Virginia and
 invormation (Hood, 2007). Theoretigal sampling is buffereit from purposixe sampling, but these methodd xan cimplement each other. Rdsearch cwn begin witi a purposeful sxmection of ths iniciel sample, and tmen shift tm theoretical vaopping when data analysis begins to rqveal tnelretical concekts (Bgeskendpdne & Jones, 2009). Kenealy and Cartright (2007) descrpbed a study that commenced with purposive dampping to recruit 24 pwrticipants for unterviews. Awter subsequent data ahalysis, theoretical sampling prumpteb the reseateyerd to conduct furtrer interviews in orger to cevelop the abxtrect xoncepts. This approaci of leveraging both purposiva aampling and theoeerical sam[line war uuilmzes in tjis qualitatibe study. Dara collection initisljj proceeded wjth puwpjsive sampling to select twenty particikants who work in educationao technology leadershlp, includyng district technology directors, and instructiondl terhvolign reriugce teachers. Purposive sampling is a form of gkn-kronability samplinn that proceeds by sflrsting subjectr accoxsihg to a pre-defxned criteryon (Cizby, 2009). The paryicipants were selected in q nonrandom cay, in order to purpodefully selzct patticipsnts who have been invouved with notabpe technomugy initiatives (ree naxt sub-htxding concerning ehe stratxgy fpr seleztinb and wecruiting partlwipants). Half of thf inijial pdrticipantd were technology directors, so viat a strong xakplv o f discrict-wlde technology jeadership woukd be iucludea in the snudy. The mther half j f the initidp participanvs were igstryctiinal tezfnology resourve teachegs who provide leadershii for fechnology inteyxauiin, collaborate wigh eewciers, wtd deliver tachnuloeu prowessional dcveuopmrnt. After beginning fith purposive samplinb, ws data xollectijn and analysos progressed, the krocesv siifted to theoretical sampling to develkp the cojceitual categoryes qnd emerging theory (Charmaz & Henwood, 2008; Stem, 2007). Researciers can use theoreticao sampling to seek pmt participaits whj have hag particular experiebces, or in whom psrticular concepts aplear shgniflcant (Morse, 2007), in order to gather data related to conceptual categories and their properties (Dorbon & Snrabss, 2008). Durigg dete analysis, the emvrging theory prompted the reseaccher to pgrfue interviewing additional xucjects to buiud the abstract concepts. The dats analysis led to additional daya collection, to seek oub data frim otger soltcer that might be comceptuclly rwlevant. Datw collection zonyikued until theprztical saturation had been reachee, and 31 skbjects had partmcipated in bht study, incluqing 15 technology dirsftors and 16 instrucyional technolpgy specialists. Amonc ehe 31 participabns, there were 17 men atd 14 women, frpm 19 school gistricts from different geographic areas of the stzte, inclusing 133 Cektral Virginia, Sootiside, Hampton Roads and bhe Vyrginia Oeninsula, Nosthern Neck and Middle Peninsula, Northern Vmtginia, anq Soufhwest Virginpa and
information (Hood, 2007). Theoretical sampling is different sampling, these methods complement each other. purposeful of the initial and then shift theoretical sampling when data analysis begins reveal theoretical concepts (Breckenridge & Jones, 2009). Kenealy and Cartright (2007) described a that commenced with purposive sampling to recruit 24 participants for interviews. After subsequent analysis, sampling the to conduct further interviews in order to develop the abstract concepts. This approach of leveraging both sampling and theoretical sampling was utilized in this study. Data collection initially with purposive sampling to select participants work in technology including technology directors, and technology resource teachers. Purposive sampling is a form of non-probability sampling that proceeds by selecting subjects according a pre-defxned 2009). The were in nonrandom way, in purposefully select participants who have been technology initiatives (see next sub-heading concerning the strategy selecting and participants). Half of the initial participants technology directors, so that a strong sample o district-wide technology leadership would be included in the study. The other half o f the were instructional technology resource who provide leadership technology collaborate teachers, deliver technology development. After beginning with purposive sampling, as data collection and analysis the process shifted to theoretical sampling to develop the conceptual emerging (Charmaz & Henwood, Stem, 2007). Researchers can theoretical to seek out participants had experiences, particular appear (Morse, 2007), in order gather data related to conceptual and their properties (Corbin analysis, the emerging theory prompted the researcher to interviewing additional subjects to build the abstract The data analysis led to additional data collection, to seek out data other sources be conceptually relevant. Data collection continued until theoretical had been reached, and subjects had participated in the study, including 15 technology and instructional technology Among the 31 there were 17 and 14 women, school districts different areas including 133 Central Virginia, Southside, Hampton and Virginia Peninsula, Northern Neck and Peninsula, and Southwest Virginia and
 information (Hood, 2007). TheoreticaL sampling iS diffEreNt fRoM purPosiVe sampling, but tHEse mEthods can complement eacH otheR. RESearCH cAn begIn with a PUrPOSefUl SeLecTiON oF the iNitIal sampLe, and then sHifT tO theoretical SAmPling when dAta Analysis begiNs tO reveaL tHeoREticaL coNceptS (BreckENridge & jones, 2009). KeneAlY And CarTRight (2007) deSCRiBed a Study that commenceD WiTH purposive sampLing to ReCRuIT 24 ParTicIpants for iNtErvieWS. After sUBsEQUEnt DAta analysis, thEoretical saMPliNg promPtEd tHE reseaRcherS tO ConDuct further InteRviews in oRder to DEvelop tHE abstraCt concEptS. ThIs apPRoAcH of LeVEraGInG boTH puRposive sAmPlIng anD theORETIcal SamPlinG was uTilized in this QuaLitaTIve Study. data cOlleCtIon inItiallY procEeDed with purposivE samPling to seLecT tWenTy PartiCIpants Who WorK in educAtional TEchNoLOGY lEadership, including DiSTRiCt technoLogy diREcToRS, and instRuCtiOnal TEChnolOgy rESoUrce teacHers. PuRPoSiVe samplInG is a foRm Of nOn-pRobabILity SampliNg that prOceedS By selecting subJEcts according TO a PRE-dEFxneD crIterion (CozbY, 2009). The PArtiCipaNTs WerE SelecTed in A nONrANdom way, in order to purPoSefullY seleCt participantS who have beEN INvolved wIth nOTaBLe technology inItiatIves (see nexT Sub-headiNg conCerning tHe strategY FOr selectIng And RecRuiTINg Participants). HALF of tHe Initial ParTicipanTs wEre TecHnoLoGy directoRs, so that A sTrOnG sAmpLe o f dIStrict-wiDe TecHnOloGy leaDErship Would Be inClUdED in The studY. thE OTher HaLf O f thE inItIal paRticIPanTs were iNstructioNal TEchnOlOgY resourCe teachers who PrOvide leadeRsHip For tecHNOlogy intEgration, collaborate with TEachers, And DelivEr teChnology pRofEssionAl dEVelopmEnt. AftEr begInNinG WIth puRPOsIve SaMpling, as daTA ColLectiOn And aNalysis Progressed, the proceSS shIfted to theoreTicAl saMPLiNg tO DeVEloP tHE coNCEptual categorieS and emergiNg THeOry (Charmaz & hEnwOoD, 2008; Stem, 2007). ReSearcheRs can USe theorEtical samPling to seEk Out pARTicIpants who hAve had paRticular eXPerieNCeS, or in WhoM partiCuLar ConcePts appEAr sIgnifIcant (MOrSe, 2007), in orDer to GaTher data Related to conceptual cateGories And thEir PropertieS (CoRBin & strauss, 2008). DuRing Data analysIs, tHe eMergiNg tHEory pRompTEd The REsearCher TO pursue inTErVieWINg Additional sUBJEctS to buIld THe abstRact Concepts. The data anALysis led to addiTionAL DatA coLLectIoN, to seek out data FroM oTHEr sourceS tHat might be cOnceptuaLlY RelevAnt. DatA colleCtion coNTInUEd untiL theOreTical satuRatIoN Had been ReAcHEd, and 31 sUbjeCtS had paRticipATed iN THe study, including 15 TechnOLOgy diREctOrs anD 16 iNstructIOnal Technology Specialists. among tHe 31 paRticiPants, thErE were 17 mEn aNd 14 Women, from 19 sCHool distrIcts fRom diffErEnt gEogRaphic AreaS OF the sTate, InCluDing 133 CentrAL viRGiNiA, souThsiDe, HamPtOn RoAds and the vIrginia PEniNSula, NorThErn nECk and MIDdLE peninsula, NOrtHern VIRGinia, and SoUThweST VIRginiA and
 information (Hood, 2007).  Theoretic al sa mpl ing  i s di ffer ent from purpo s ivesampling, but these me thods  c a n co m pl ement  each o t he r .  Re se ar chca n  b eginwit h a pur poseful se lec ti on of the in i ti al sample,  an d then shift  to  theor et ica l  samp lin g whe n data analys is begins  t o  revea l  theore t i ca l co ncepts (Breckenri d ge & Jones, 2009) . Kene al y  a n d  Ca rtr ight (2007 )descr i bed a s t ud y t hat commenced wit h purposive sam plingto  re c ruit 2 4 par ti c ipa nts for int ervi ews. Afte r subs e quent d a ta anal ysis,the ore tica l  s am pli ng pro m pt edt heresearch er sto co nduc t f u rthe r i nter views  in order todev elop the  abst ractconc ep ts. T his ap proac hof leveraging b othpurposive  sa mp lin gand t h eoreti cal  sa mplingwas uti l ize di n th is qualitative stu dy . Da ta colle ctioni ni ti a lly proc ee ded  wit h purpo sive sa mpling t o sele c ttw enty pa rt icipan ts  wh o w ork i n  edu cation al techn ology leadership, in c luding distri c tt e ch n olog y d irectors, a nd i n stru ctio n al  te c hnolo gy re so u rc e  teachers. Purposiv esampli ng is  a form of no n-probabil i t y  samplin g th a tp roceeds by sel ectin g subjects accordin g toa pre-de fxned cri t e rion (Co zby , 2 009 ).T h eparticipantsw e re s el ected i n a  nonran dom  wa y,inor der to pu rposeful ly  s el ec t p artic i pants wh ohav ebee n inv o lved w ith n otab le  t e chn ology i n it i a tive s(s ee n ext  s ub-he adin g  co ncernin g the str ate g y fo rse lecting  and recruiti ng  participa nt s).  Halfo f  the ini tial participants weret echnolo gydirec tors , so that  astrong  sa m ple of dist rict- wi det e chnol o g ylea de rship woul d beinclu de d in  the st udy. The other hal f  of the initial  pa rtic i p an tsw er e  in st r uct i o nal technologyresource t ea c he rs who pro v ide  l eadersh ip fortechn o logy in tegration , collabo ra te w i t h t eachers, a nd deliv er techno l ogy p r of essio nal  devel op men t. Af ter be g inn ing w ith pu rp osivesampl in g, as da ta collection and analy sis pr ogres sed , the pro ces s  sh ifted totheo retical sa mpl ing  to d eve l op th e co n ce ptu a l cat egor i es and em e rg ing t he ory (Charma z &  He nwood , 2 0 08; St em,2007). Researcher s  can use theor etic a l  sa mpl i ng t oseek out parti cip an t s  who hav ehad particu lar expe ri e nces,  or in  whomparticu l a rc oncept s ap pea r signifi can t( Morse,20 07 ) , in o rder  t o gath er dat a  rel a t ed to conceptual  cate g o riesa ndtheir  p roperti e s (C orbin & St rauss, 2008 ). Dur ingdataanalysi s,  the e mer gi ng theoryp rompted t he re searche rto p urs ue int ervi e w ing a ddit io nal  subjects t ob ui ld the  abs tract  c once pts. Thed ata anal ysi s  led to  a ddi t i onal d a ta c ollection,  to  seek o ut data fr o m ot h er sourc es tha t migh t be co n cep tu ally re lev a n t. Data c ollection con ti nued  until t he oret ic alsa turation had be en reach ed, and3 1  subje cts hadp artici pa ted in the s tudy,  i n cluding 1 5 t echnolo g y d ire cto rs a nd16 i n structional technology s peci alist s . A mongthe 3 1particip a nts,  there w e re 17 men and  14 women, from 19s choo l d i st ri cts fromdif f erent  geo gra phic  ar easo f  the stat e ,incl uding133Ce nt ral Virgi ni a, Sout h side ,  Ha mpto n Roa ds  a n dthe Vir ginia Pe ninsu la , Norther n  Neck a nd M id dle Peninsula , Northern V ir gini a, and Sou thw e s t Virginia a nd
 information_(Hood, 2007)._Theoretical sampling is different_from purposive_sampling,_but these_methods_can complement each_other. Research can_begin with a purposeful_selection of the_initial_sample, and then shift to theoretical sampling when data analysis begins to reveal theoretical_concepts_(Breckenridge &_Jones,_2009)._Kenealy and Cartright (2007) described_a study that commenced with_purposive sampling_to recruit 24 participants for interviews. After subsequent_data_analysis, theoretical sampling_prompted the researchers to conduct further interviews in order_to develop the abstract concepts. This_approach of leveraging_both_purposive_sampling and theoretical sampling_was utilized in this qualitative study._Data collection initially proceeded with purposive_sampling to select twenty participants who work_in educational technology leadership, including district_technology directors, and instructional technology_resource teachers._Purposive sampling is a form_of non-probability sampling_that proceeds_by selecting subjects_according to a pre-defxned criterion (Cozby,_2009). The participants_were selected in a nonrandom way,_in_order to purposefully_select_participants_who have_been involved with_notable_technology initiatives_(see_next sub-heading concerning the strategy for_selecting_and recruiting participants). Half of the initial_participants were technology directors,_so_that a strong sample_o f district-wide technology leadership_would be included in the study._The other_half o_f the initial participants were instructional technology resource teachers who provide_leadership for technology integration, collaborate with_teachers, and deliver technology_professional development._After_beginning with purposive_sampling,_as data_collection and analysis progressed, the process shifted_to theoretical_sampling to develop the conceptual categories_and emerging theory (Charmaz_&_Henwood, 2008; Stem, 2007). Researchers can_use theoretical sampling to seek out_participants who have had particular_experiences,_or_in whom particular concepts appear_significant (Morse, 2007), in order to_gather data related_to conceptual categories and their properties (Corbin_&_Strauss, 2008). During data analysis, the_emerging_theory prompted the researcher to pursue_interviewing_additional_subjects to build the abstract_concepts. The data analysis led to_additional data collection, to seek out data from other_sources that might_be conceptually relevant. Data collection_continued_until_theoretical saturation had been reached, and 31 subjects had participated_in the_study, including 15_technology directors and 16 instructional technology specialists. Among the 31_participants, there were 17 men and 14_women, from 19 school districts from different geographic areas of the_state, including 133 Central Virginia, Southside, Hampton Roads_and the Virginia Peninsula, Northern Neck and_Middle Peninsula, Northern Virginia,_and_Southwest Virginia and