{"id":111,"date":"2020-09-03T16:39:49","date_gmt":"2020-09-03T13:39:49","guid":{"rendered":"http:\/\/acikkitap.com.tr\/oaek\/chapter\/bolum-24-kurumsal-benimsemeye-dair-zorluklarin-ele-alinmasi\/"},"modified":"2020-09-03T16:39:49","modified_gmt":"2020-09-03T13:39:49","slug":"bolum-24-kurumsal-benimsemeye-dair-zorluklarin-ele-alinmasi","status":"publish","type":"chapter","link":"https:\/\/acikkitap.com.tr\/oaek\/chapter\/bolum-24-kurumsal-benimsemeye-dair-zorluklarin-ele-alinmasi\/","title":{"raw":"B\u00f6l\u00fcm 24 Kurumsal Benimsemeye Dair Zorluklar\u0131n Ele Al\u0131nmas\u0131","rendered":"B\u00f6l\u00fcm 24 Kurumsal Benimsemeye Dair Zorluklar\u0131n Ele Al\u0131nmas\u0131"},"content":{"raw":"\n

Cassandra Colvin1<\/sup>, Shane Dawson1<\/sup>, Alexandra Wade2<\/sup>, Dragan Ga\u0161evi\u01073<\/sup><\/span><\/span><\/p>\n

1<\/sup>\u00d6\u011fretim \u0130novasyon Birimi, G\u00fcney Avustralya \u00dcniversitesi, Avustralya <\/span><\/span><\/p>\n

2<\/sup>Sa\u011fl\u0131k Bilimleri Y\u00fcksekokulu, G\u00fcney Avustralya \u00dcniversitesi, Avustralya <\/span><\/span><\/p>\n

3<\/sup>E\u011fitim ve Bili\u015fim Okullar\u0131, Edinburgh \u00dcniversitesi, Birle\u015fik Krall\u0131k<\/span><\/span><\/p>\n

DOI: 10.18608\/hla17.024<\/span><\/span><\/p>\n\n

\u00d6Z<\/h2>\n

Artan fon olanaklar\u0131, ara\u015ft\u0131rma ve kurumsal yat\u0131r\u0131mlara ra\u011fmen, y\u00fcksek\u00f6\u011frenimde \u00f6\u011frenme analiti\u011fi stratejileri ve faaliyetlerinin ger\u00e7ekle\u015fen geni\u015f \u00f6l\u00e7ekli uygulamalar\u0131 \u00e7ok azd\u0131r. Kurumsal \u00f6rneklerin bulunmay\u0131\u015f\u0131, sekt\u00f6r\u00fcn zaman i\u00e7indeki \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131n getirdi\u011fi g\u00fc\u00e7l\u00fck ve k\u0131s\u0131tlamalar hakk\u0131nda geni\u015f ve incelikli bir anlay\u0131\u015fa ula\u015fmas\u0131n\u0131 engellemektedir. Bu b\u00f6l\u00fcm, b\u00fcy\u00fck \u00f6l\u00e7ekli \u00f6\u011frenme analiti\u011fi projelerinin benimsenmesi ile ilgili \u00e7e\u015fitli modelleri incelemektedir. Bunu yaparken, mevcut \u00e7al\u0131\u015fman\u0131n s\u0131n\u0131rlar\u0131 vurgulanmakta ve \u00f6l\u00e7eklendirmede \u00f6\u011frenme analitiklerini benimsemeyi etkileyen karma\u015f\u0131k ve i\u00e7 i\u00e7e ge\u00e7mi\u015f boyutlar\u0131 belirlemek i\u00e7in daha deneysel bir yakla\u015f\u0131m \u00f6nermektedir.<\/span><\/span><\/p>\n

Anahtar Kelimeler<\/span>: \u00d6\u011frenme analiti\u011fi benimsenmesi, \u00f6\u011frenme analiti\u011fi \u00f6z\u00fcmsenmesi, liderlik<\/span><\/span><\/p>\n

\u00d6\u011frenme ve \u00f6\u011fretme prati\u011fi i\u00e7in verilerin ve analitiklerin \u00f6nemi, e\u011fitim politikas\u0131 ve ara\u015ft\u0131rma literat\u00fcr\u00fcnde g\u00fc\u00e7l\u00fc bir \u015fekilde tart\u0131\u015f\u0131lmaktad\u0131r (Daniel, 2015; Siemens, Dawson ve Lynch, 2013). \u00d6\u011frenme analitiklerinin g\u00fcc\u00fc d\u00e2hilindeki \u00f6\u011fretmeye, \u00f6\u011frenmeye, \u00f6\u011frenci deneyimine ve y\u00f6netim etkinliklerine ili\u015fkin i\u00e7g\u00f6r\u00fcler \u00f6l\u00e7ek, karma\u015f\u0131kl\u0131k ve etki bak\u0131m\u0131ndan hi\u00e7 olmad\u0131\u011f\u0131 kadar dile getirilmektedir (Baker ve Inventado, 2014). \u00d6\u011frenme analiti\u011fi yaln\u0131zca kurumlar i\u00e7inde ger\u00e7ekle\u015fen uygulama ve etkinliklerin etkin bir \u015fekilde anla\u015f\u0131lmas\u0131n\u0131 sa\u011flama kapasitesine sahip olmakla kalmaz, ayn\u0131 zamanda kestirimci modelleme, \u00f6\u011frenmenin ki\u015fiselle\u015ftirilmesi ve \u00f6neri sistemlerinde oldu\u011fu gibi etkinliklere ba\u015ftan sona arac\u0131l\u0131k etme ve onlar\u0131 bi\u00e7imlendirme yani gelecekteki hallerini s\u00fcre\u00e7 i\u00e7inde de\u011fi\u015ftirebilme potansiyeline de sahiptir (Conde ve Hern\u00e1ndez-Garc\u00eda, 2015).<\/span><\/p>\n

Artan fon imk\u00e2nlar\u0131, ara\u015ft\u0131rma ve kurumsal yat\u0131r\u0131mlara ra\u011fmen, y\u00fcksek\u00f6\u011frenimde \u00f6\u011frenme analiti\u011fi stratejileri ve faaliyetlerinin geni\u015f \u00f6l\u00e7ekli uygulamalar\u0131nda yetersizlik devam etmektedir (Ferguson vd., 2015), dolay\u0131s\u0131yla sekt\u00f6r zaman i\u00e7indeki \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131n getirdi\u011fi faydalar ve k\u0131s\u0131tlamalar hakk\u0131nda geni\u015f ve incelikli bir anlay\u0131\u015fa ula\u015famamaktad\u0131r. Kurumsal \u00f6rneklerin eksikli\u011fine ili\u015fkin a\u00e7\u0131klamalar\u0131n bir k\u0131sm\u0131, bir disiplin olarak \u00f6\u011frenme analiti\u011finin g\u00f6rece yeni ortaya \u00e7\u0131k\u0131\u015f\u0131na ve \u00f6\u011frenme analiti\u011fi program ve uygulamalar\u0131n\u0131n tamamen geli\u015fmesi ve olgunla\u015fmas\u0131na ayr\u0131lan zaman\u0131n hissedilir bi\u00e7imde yetersizli\u011fine dayanabilir. Bununla birlikte, bu a\u00e7\u0131klama, \u00f6\u011frenme analiti\u011finin sistemik kavranmas\u0131yla ilgili sorunlar\u0131n karma\u015f\u0131kl\u0131\u011f\u0131n\u0131 yeterince ortaya koyamamaktad\u0131r (Arnold, Lynch vd., 2014; Ferguson vd., 2015; Macfadyen, Dawson, Pardo ve Ga\u0161evi\u0107, 2014). Her ne kadar \u00f6\u011frenme analiti\u011fi, y\u00fcksek\u00f6\u011frenim i\u00e7in nispeten yeni olsa da bu t\u00fcr etkinliklerin kurum \u00e7ap\u0131nda bir e\u011fitime getirebilece\u011fi kolayl\u0131klar\u0131 farketmek i\u00e7in zaman ve kaynak olarak yeterli yat\u0131r\u0131mlar\u0131n yap\u0131lmas\u0131n\u0131 \u00f6neriyoruz. Asl\u0131nda, \u00e7ok az say\u0131da kurum, \u00f6\u011fretme ve \u00f6\u011frenme kazan\u0131mlar\u0131 \u00fczerinde g\u00f6zle g\u00f6r\u00fcl\u00fcr bir etkiye sahip b\u00fcy\u00fck \u00f6l\u00e7ekli \u00f6\u011frenme analiti\u011fi programlar\u0131n\u0131 uygulayabilmi\u015ftir (Ferguson vd., 2015). Bununla birlikte, bu \u00f6rnekler, \u00e7ok say\u0131da kurum i\u00e7in, \u00f6\u011frenme analiti\u011finin \u00f6rg\u00fctsel olarak benimsenmesinin ya kavramsal, anla\u015f\u0131lamam\u0131\u015f bir \u00f6zlem olarak kald\u0131\u011f\u0131 ya da i\u015flevselle\u015ftirildi\u011finde, kapsam ve etki bak\u0131m\u0131ndan genellikle dar ve s\u0131n\u0131rl\u0131 oldu\u011fu bir sekt\u00f6rde istisna olmaya devam etmektedir (Ferguson vd., 2015). Bu literat\u00fcr, \u00f6\u011frenme analiti\u011finin benimsenmesine arac\u0131l\u0131k etmek \u00fczere boyutlar ve s\u00fcre\u00e7lerle ilgili i\u00e7g\u00f6r\u00fcleri yakalamak ve ortaya \u00e7\u0131karmak amac\u0131yla \u00e7oklu uygulama \u00e7at\u0131lar\u0131 (frameworks) sunmaktad\u0131r. Kavramsal anlamaya yard\u0131mc\u0131 olmas\u0131n\u0131n yan\u0131 s\u0131ra, bu literat\u00fcr ayn\u0131 zamanda kurumlar\u0131 uygulama a\u015famalar\u0131 ve de\u011ferlendirmeler boyunca y\u00f6nlendiren sezgisel bir de\u011fere sahiptir. \u00d6\u011frenme analiti\u011finin etkin d\u00fczenlenmesini\/kullan\u0131m\u0131n\u0131 ara\u015ft\u0131ran s\u0131n\u0131rl\u0131 deneysel ara\u015ft\u0131rma g\u00f6z \u00f6n\u00fcne al\u0131nd\u0131\u011f\u0131nda (Ferguson vd., 2015), bir\u00e7ok y\u00f6neticinin \u00f6\u011frenme analiti\u011fi giri\u015fimlerini planlarken ve uygularken ilham ve i\u00e7g\u00f6r\u00fc almak i\u00e7in kavramsal literat\u00fcr\u00fcn bu k\u00fc\u00e7\u00fck taraf\u0131na y\u00f6nelmesi muhtemeldir. Bu b\u00f6l\u00fcm, alan yaz\u0131n\u0131n bu yan\u0131n\u0131 sadece \u00f6\u011frenme analitiklerinin etkili kurumsal uygulamalar\u0131 i\u00e7in \u00f6nemli olan boyutlar ve s\u00fcre\u00e7ler olarak neleri tan\u0131mlad\u0131\u011f\u0131n\u0131 \u00f6ng\u00f6rmekle kalmay\u0131p ayn\u0131 zamanda kurumsal y\u00f6neticiler i\u00e7in modellerin k\u0131lavuz olarak de\u011ferini \u00f6l\u00e7meyi de ele almaktad\u0131r. Ard\u0131ndan, bu alan yaz\u0131n incelemesinin bulgular\u0131 ile Avustralya \u00fcniversitelerinden olu\u015fan b\u00fcy\u00fck bir toplulu\u011fun1<\/a><\/sup> mevcut \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131 inceleyen g\u00fcncel bir \u00e7al\u0131\u015fman\u0131n bulgular\u0131n\u0131 kar\u015f\u0131la\u015ft\u0131rarak bu uygulamalar\u0131 bi\u00e7imlendiren s\u00fcre\u00e7ler ve etkenler \u00fczerine deneysel bir anlay\u0131\u015f sunduk (Colvin vd., 2015).<\/span><\/p>\n\n

\u00d6\u011eRENME ANAL\u0130T\u0130\u011e\u0130 DA\u011eITIMINDA G\u00dcNCEL MODELLER\u0130N \u0130NCELENMES\u0130<\/h2>\n

G\u00fcncelli\u011fini koruyan \u00f6\u011frenme analiti\u011fi uygulama modellerinin ve uygulama \u00e7at\u0131lar\u0131n\u0131n incelenmesi, \u00fc\u00e7 ana literat\u00fcr grubunu ortaya \u00e7\u0131karm\u0131\u015ft\u0131r: 1) \u00f6\u011frenme analiti\u011fi \u00e7\u0131kt\u0131lar\u0131n\u0131n (kazan\u0131mlar\u0131n\u0131n) \u00f6nc\u00fcllerine odaklananlar (\u00f6\u011frenme analiti\u011fi girdi modelleri); 2) \u00f6\u011frenme analiti\u011finin \u00e7\u0131kt\u0131lar\u0131na odaklananlar (\u00f6\u011frenme analiti\u011fi \u00e7\u0131kt\u0131 modelleri) ve 3) \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131 destekleyen g\u00f6revleri s\u0131ral\u0131 bir \u015fekilde haritalayan ve i\u015fleten s\u00fcre\u00e7 modelleri. Bu farkl\u0131 modellere genel bir bak\u0131\u015f ve bunlar\u0131n kurumsal \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131 \u015fekillendiren fakt\u00f6rleri anlamadaki kavramsal ve deneysel katk\u0131lar\u0131 a\u015fa\u011f\u0131daki gibidir.<\/span><\/p>\n\n

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          \u00d6\u011frenme Analiti\u011fi Girdi Modelleri<\/h4>\n<\/li>\n<\/ol>\n<\/li>\n<\/ol>\n<\/li>\n<\/ol>\n<\/li>\n<\/ol>\n

          Literat\u00fcr\u00fcn bu taraf\u0131ndaki uygulama \u00e7at\u0131lar\u0131, \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131 liderlik, y\u00f6neti\u015fim, teknoloji, kapasite ve k\u00fclt\u00fcr gibi boyutlar\u0131 i\u00e7eren \u00f6nceki ili\u015fkilerin bir sonucu olarak sunma e\u011filimindedir. Bu literat\u00fcrde dikkat \u00e7eken kurulu\u015f ABD merkezli EDUCAUSE Analiz ve Ara\u015ft\u0131rma Merkezi'dir (EAAM; bk. EAAM, 2015) Y\u00fcksek \u00d6\u011frenim i\u00e7in Analitik Olgunluk Endeksi (Bichsel, 2012). Kulland\u0131klar\u0131 model, anketler ve end\u00fcstri uzmanlar\u0131yla yap\u0131lan odak grup g\u00f6r\u00fc\u015fmeleri yoluyla ortaya \u00e7\u0131kar\u0131lan verilere dayanan bir model olarak, \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131 k\u00fclt\u00fcr, s\u00fcre\u00e7, veri \/ raporlama \/ ara\u00e7lar, yat\u0131r\u0131m, uzmanl\u0131k ve y\u00f6neti\u015fim \/ altyap\u0131 olmak \u00fczere alt\u0131 faaliyet boyutunda i\u015flevsel hale getirir. Her girdi boyutu, kurumlar\u0131n her bir seviyedeki ilerleme d\u00fczeylerini belirlemelerine yard\u0131mc\u0131 olmak i\u00e7in tasarlanm\u0131\u015f kesintisiz be\u015f olgunluk seviyesi boyunca yap\u0131land\u0131r\u0131l\u0131r. Ba\u015far\u0131l\u0131 bir \u00f6\u011frenme analiti\u011fi uygulamas\u0131 i\u00e7in her girdi boyutunun kritik oldu\u011fu varsay\u0131lmaktad\u0131r.<\/span><\/p>\n

          EAAM modeline benzemekle birlikte kurumlara analitik uygulamalar i\u00e7in \u201chaz\u0131rl\u0131k\u201d d\u00fczeylerini de\u011ferlendirmelerine yard\u0131mc\u0131 olmaya y\u00f6nelik bir ara\u00e7 olarak tasarlanan di\u011fer bir model ise \u00d6\u011frenme Analiti\u011fi Haz\u0131rl\u0131k Arac\u0131'd\u0131r (\u00d6AHA); (Arnold, Lonn ve Pistilli, 2014; Oster, Lonn, Pistilli ve Brown, 2016). Her ne kadar ba\u015flang\u0131\u00e7ta nas\u0131l belirlendi\u011fi a\u00e7\u0131k olmasa da bu arac\u0131n orijinal s\u00fcr\u00fcm\u00fc (Arnold, Lonn ve Pistilli, 2014) \u201c\u00f6\u011frenme analiti\u011fi ba\u015far\u0131s\u0131 i\u00e7in en uygun ortam\u0131\u201d (s.2) elde etmeye y\u00f6nelik be\u015f boyut tan\u0131mlam\u0131\u015ft\u0131r: 1) yetenek, 2) veri, 3) k\u00fclt\u00fcr ve s\u00fcre\u00e7, 4) \"y\u00f6neti\u015fim ve altyap\u0131\" ve genel 5) haz\u0131rl\u0131k alg\u0131lar\u0131. \u00d6AHA'y\u0131 rafine etmek i\u00e7in toplam 24 kurum 560 kat\u0131l\u0131mc\u0131dan elde edilen anket verilerine uygulanan daha g\u00fcncel bir fakt\u00f6r analizi kullan\u0131lm\u0131\u015ft\u0131r. Be\u015f boyut hafif\u00e7e de\u011fi\u015ftirilerek g\u00f6receli belirginlikleri\/farklar\u0131 ortaya \u00e7\u0131kar\u0131lm\u0131\u015ft\u0131r. Ancak bu belirginlik kat\u0131l\u0131mc\u0131n\u0131n alg\u0131s\u0131na g\u00f6re \u00f6l\u00e7\u00fclmesine kar\u015f\u0131n \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131n sonu\u00e7lar\u0131na kar\u015f\u0131 \u00f6l\u00e7\u00fclmemi\u015ftir.<\/span><\/p>\n

          \u00d6rg\u00fctsel Kapasite Analiti\u011fi Uygulama \u00c7er\u00e7evesi (Norris ve Baer, 2013), analitiklerin benimsenmesini bi\u00e7imlendirmede \u00f6nemli oldu\u011funu d\u00fc\u015f\u00fcnd\u00fckleri boyutlar konusunda \u00f6\u011frenme analiti\u011fi uzmanlar\u0131ndan toplanan bilgiler\/i\u00e7g\u00f6r\u00fcler \u00fczerine kuruludur. Yazarlar, Amerika Birle\u015fik Devletleri'ndeki 40 kurumun y\u00f6neticileriyle r\u00f6portaj yapm\u0131\u015f ve bu r\u00f6portajlar yoluyla toplanan veriler kritik kurumsal kapasite fakt\u00f6rleri olarak kabul edilen be\u015f boyutun olu\u015fturulmas\u0131na yol a\u00e7m\u0131\u015ft\u0131r. Bu boyutlar 1) teknoloji altyap\u0131s\u0131, 2) s\u00fcre\u00e7ler ve pratik, 3) k\u00fclt\u00fcr ve davran\u0131\u015flar, 4) beceri ve de\u011ferler ve 5) liderlikti. Ortaya koyduklar\u0131 \u201cAnalitik i\u00e7in \u00d6rg\u00fctsel Kapasite\u201d adl\u0131 \u00e7al\u0131\u015fmalar\u0131nda \u201cUygulama \u00c7at\u0131s\u0131\u201dn\u0131n boyutlar\u0131n birbirine ba\u011fl\u0131 ve \u00f6rt\u00fc\u015fen olarak sunulmas\u0131 ve dolay\u0131s\u0131yla birbirine ba\u011f\u0131ml\u0131 do\u011falar\u0131n\u0131n vurgulanmas\u0131 kayda de\u011ferdir (Norris ve Baer, 2013, s. 31). Uygulama \u00e7at\u0131s\u0131, her bir boyut i\u00e7in \u00fc\u00e7 olgunluk seviyesini i\u015flevsel hale getirirken, boyutlar\u0131n g\u00f6reli belirginliklerini incelememektedir.<\/span><\/p>\n

          Son olarak, Drachsler ve Greller\u2019\u0131n modeli (yazarlar taraf\u0131ndan ontoloji olarak belirtilir; Drachsler ve Greller, 2012; Greller ve Drachsler, 2012) ayr\u0131ca \u00f6\u011frenme analiti\u011fi uygulamalar\u0131na arac\u0131l\u0131k eden boyutlar\u0131n birbirine ba\u011f\u0131ml\u0131 ve \u00f6zyinelemeli do\u011fas\u0131n\u0131 da yakalar. Medya taramas\u0131, k\u0131demli uzmanlarla g\u00f6r\u00fc\u015fmeler ve bili\u015fsel haritalama \u00e7al\u0131\u015fmalar\u0131ndan elde edilen verilere genel morfolojik analiz (bk. Ritchey, 2011, Greller ve Drachsler, 2012) uygulanm\u0131\u015ft\u0131r. Bu model \u201c\u00f6\u011frenme analiti\u011finin uygun \u015fekilde kullan\u0131lmas\u0131n\u0131 sa\u011flamak\u201d i\u00e7in alt\u0131 temel faaliyet alan\u0131n\u0131 \u201ckritik\u201d olarak tan\u0131mlamaktad\u0131r (Drachsler ve Greller, 2012, s. 120): 1) yeterlilikler 2) k\u0131s\u0131tlamalar (gizlilik\/etik), 3) teknolojiler 4) e\u011fitim verileri, 5) hedefler ve 6) payda\u015flar. Drachsler ve Greller (2012) bu alt\u0131 boyutun her birini \u201ckritik\u201d olarak g\u00f6r\u00fcrken, belirginliklerinin benzer olmad\u0131\u011f\u0131n\u0131 g\u00f6zlemleyip, \u201cbaz\u0131 boyutlar\u0131n di\u011ferlerinden daha belirsiz oldu\u011funa\u201d dikkat \u00e7ekmektedirler (s. 44).<\/span><\/p>\n

          Bir\u00e7ok girdi modeli i\u00e7in ortak olan, \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131n kavramsalla\u015ft\u0131r\u0131lmas\u0131n\u0131n do\u011frusal olmamas\u0131, \u00e7oklu ve birbirine ba\u011fl\u0131 girdi boyutlar\u0131n\u0131n kar\u015f\u0131l\u0131kl\u0131 etkile\u015fimi olarak ortaya \u00e7\u0131kar\u0131lmas\u0131d\u0131r. Odak grup ve anket y\u00f6ntemleri arac\u0131l\u0131\u011f\u0131yla \u0131srarla belirtilen g\u00f6r\u00fc\u015flerle de s\u0131k\u00e7a bilgilendirilmekle birlikte (Drachsler ve Greller, 2012; Greller ve Drachsler, 2012; Norris ve Baer, 2013; Oster vd., 2016), bu modeller asl\u0131nda kavramsald\u0131r. Kurumsal temsilcilerin alg\u0131lad\u0131\u011f\u0131, etkili bir \u00f6\u011frenme analiti\u011fi uygulamas\u0131 olu\u015fturmak i\u00e7in g\u00f6z \u00f6n\u00fcnde bulundurulmas\u0131 gereken boyutlar\u0131 tan\u0131mlarlar ancak boyutlar\u0131 ger\u00e7ek \u00f6\u011frenme analiti\u011fi uygulamalar\u0131na kar\u015f\u0131 deneysel olarak sorgulamazlar. Benzer \u015fekilde, girdi modelleri \u00f6nc\u00fcl boyutlar aras\u0131nda ili\u015fki oldu\u011funu \u00f6ne s\u00fcrerken, bu ili\u015fkilerin do\u011fas\u0131 ve bunlar\u0131n \u00f6\u011frenme analiti\u011fi uygulama \u00e7\u0131kt\u0131lar\u0131 \u00fczerindeki etkileri de deneysel olarak ara\u015ft\u0131r\u0131lmam\u0131\u015ft\u0131r. Bu nedenle, modeller kendi kurumlar\u0131nda \u00f6\u011frenme analiti\u011fi yaz\u0131l\u0131mlar\u0131n\u0131 uygulama ile g\u00f6revli liderlere bu uygulamay\u0131 ger\u00e7ekle\u015ftirmek i\u00e7in gerekli \u00f6nc\u00fcl boyutlara y\u00f6nelik \u00f6ng\u00f6r\u00fcler sunarken, uygulamalar\u0131n ger\u00e7ekte nas\u0131l \u00e7al\u0131\u015ft\u0131\u011f\u0131 konusunda \u00e7ok az rehberlik sunmaktad\u0131r. Ayr\u0131ca, modellerdeki her bir boyutun g\u00f6receli belirginli\u011finin ara\u015ft\u0131r\u0131lmam\u0131\u015f olmas\u0131, kurumlar\u0131n eylemleri ve kaynaklar\u0131 en iyi nas\u0131l \u00f6nceliklendirebilece\u011fi konusundaki kavray\u0131\u015flar\u0131n\u0131 s\u0131n\u0131rland\u0131rmaktad\u0131r (bununla birlikte s\u0131n\u0131rl\u0131 say\u0131da model her boyutta olgunluk seviyeleri sa\u011flar; Arnold, Lonn ve Pistilli, 2014; Bichsel, 2012; Norris ve Baer, 2013).<\/span><\/p>\n\n

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                  \u00d6\u011frenme Analiti\u011fi \u00c7\u0131kt\u0131 Modelleri<\/h4>\n<\/li>\n<\/ol>\n<\/li>\n<\/ol>\n<\/li>\n<\/ol>\n<\/li>\n<\/ol>\n

                  \u00d6\u011frenme analiti\u011fi modelleri ve uygulama \u00e7at\u0131lar\u0131n\u0131n ikinci aya\u011f\u0131, \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131 zaman i\u00e7inde ortaya \u00e7\u0131kan ve farkl\u0131 haz\u0131rl\u0131k ve olgunluk seviyeleri i\u00e7eren do\u011frusal bir s\u00fcre\u00e7 olarak tan\u0131mlar ve temsil eder. Bu literat\u00fcrdeki erken bir model olmas\u0131na ra\u011fmen h\u00e2l\u00e2 sekt\u00f6rde bir \u00f6neme, paya sahip g\u00f6r\u00fcnen Davenport ve Harris\u2019in (2007) Analitik Uygulama \u00c7at\u0131s\u0131, analitikleri sorgulama ve raporlama uygulamalar\u0131ndan tahmin ve kestirimci modelleme gibi resm\u00ee analitik fonksiyonlara kadar olgunla\u015fan bir s\u00fcre\u00e7 olarak kavramsalla\u015ft\u0131r\u0131r. Siemens, Dawson ve Lynch'in (2013) Sofistike Model \u00d6\u011frenme Analiti\u011fi yetene\u011fi ve analitik sistemler artan olgunluk bir s\u00fcreklilik boyunca da\u011f\u0131t\u0131m b\u00fct\u00fcnle\u015ftirir. Be\u015f olgunluk a\u015famas\u0131 tan\u0131mlanm\u0131\u015f, bunlar\u0131n her biri ayr\u0131ca \u00f6rnek te\u015fkil edecek bi\u00e7imde i\u015flevselle\u015ftirilmi\u015ftir. \u00d6rne\u011fin, erken a\u015famadaki bir da\u011f\u0131t\u0131m sistemi \u00f6zellik olarak, temel raporlar\u0131 ve kay\u0131t g\u00fcnl\u00fc\u011f\u00fcn\u00fc i\u00e7erirken, olgun bir da\u011f\u0131t\u0131m ise kestirimci modelleri ve ki\u015fiselle\u015ftirilmi\u015f \u00f6\u011frenmeyi de i\u00e7ermektedir.<\/span><\/p>\n

                  \u00c7\u0131kt\u0131 modellerinin birincil yarar\u0131, kurumlara, faaliyetlerinin ve i\u015flemlerinin olgunlu\u011funu (veya kapasitesini) istenen kazan\u0131mlar\u0131n matrisine kar\u015f\u0131 objektif olarak de\u011ferlendirmeleri i\u00e7in bir ara\u00e7 sa\u011flamalar\u0131d\u0131r. Bununla birlikte, bir\u00e7ok \u00e7\u0131kt\u0131 modeli kapsam a\u00e7\u0131s\u0131ndan s\u0131n\u0131rl\u0131l\u0131klara sahiptir ve genel olarak tek veya \u00e7ift boyutlu kavramsal merceklere (kullan\u0131lan analitik tekniklerin geli\u015fkinli\u011fi gibi) dayan\u0131r. \u00c7\u0131kt\u0131 modelleri, \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131n kazan\u0131mlar\u0131na y\u00f6nelik bir vizyonunu savunurken, asl\u0131nda savunduklar\u0131 bu kazan\u0131mlar\u0131 olu\u015fturmak i\u00e7in gerekli t\u00fcm boyutlar\u0131 ya da mekanizmalar\u0131 tan\u0131mlamakta ya da ele\u015ftirel olarak incelemekte ba\u015far\u0131s\u0131z olurlar. Son olarak, bir\u00e7ok \u00e7\u0131kt\u0131 modelindeki risk, bu modellerin ilerlemeyi genel olarak sadece teorik, ba\u011flamdan kopar\u0131lm\u0131\u015f, muhtemelen varsay\u0131lan bir evrenselli\u011fe dayand\u0131r\u0131lm\u0131\u015f ve belirli bir kurumun i\u015f g\u00f6rme ba\u011flam\u0131nda neyin m\u00fcmk\u00fcn veya arzu edilebilir oldu\u011funu yakalamayan bir tarzda temellendirmeleri, hatta; \u201c\u00fctopik\u201d bir \u00f6\u011frenme analiti\u011fi vizyonuyla do\u011frusal olarak ve a\u015famal\u0131 bir s\u00fcre\u00e7 bi\u00e7iminde kavramsalla\u015ft\u0131rmalar\u0131d\u0131r.<\/span><\/p>\n\n

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                          S\u00fcre\u00e7 Modelleri<\/h4>\n<\/li>\n<\/ol>\n<\/li>\n<\/ol>\n<\/li>\n<\/ol>\n<\/li>\n<\/ol>\n

                          Literat\u00fcr\u00fcn (Foreman, 2013a, 2013b; Norris ve Baer, 2013) bu \u00fc\u00e7\u00fcnc\u00fc aya\u011f\u0131, s\u0131ral\u0131 olarak temel s\u00fcre\u00e7leri veya \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131 destekleyen \u201cad\u0131mlar\u0131\u201d haritalar. Kazan\u0131mlar\u0131n neye benzemesi gerekti\u011fi (\u00e7\u0131kt\u0131 modeli) veya neyi i\u00e7ermesi gerekti\u011fi (girdiler modeli) yerine bir \u00f6\u011frenme analiti\u011fi program\u0131n\u0131n nas\u0131l uygulanaca\u011f\u0131na odaklan\u0131r. S\u00fcre\u00e7 modelleri hem do\u011frusal (Foreman, 2013a, 2013b) hem de dolayl\u0131d\u0131r (Norris ve Baer'in Analitik Eylem Plan\u0131, 2013) ve genel olarak daha geni\u015f bir \u00f6\u011frenme analiti\u011fi uygulamas\u0131 [\u00f6rne\u011fin, bir \u00f6\u011frenme y\u00f6netim sisteminin uygulanmas\u0131 (\u00d6YS; Foreman, 2013a, 2013b) veya strateji geli\u015ftirme (bk. Norris ve Baer\u2019\u0131n Analitik Eylem Plan\u0131, 2013)] i\u00e7indeki belirli \u00f6gelere odaklan\u0131r. Bununla birlikte, ortaya \u00e7\u0131kan literat\u00fcr (Ferguson vd., 2015), bu kavramsalla\u015ft\u0131rman\u0131n sa\u011flad\u0131\u011f\u0131 i\u00e7g\u00f6r\u00fcn\u00fcn \u201cgeni\u015f \u00f6l\u00e7ekte\u201d \u00f6\u011frenme analiti\u011fi uygulamak isteyen kurumlar i\u00e7in kritik \u00f6neme sahip oldu\u011funu \u00f6ne s\u00fcrerek \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131n geni\u015fli\u011fini ve karma\u015f\u0131kl\u0131\u011f\u0131n\u0131 daha iyi yans\u0131tan s\u00fcre\u00e7 modelleri sunar. Ferguson ve meslekta\u015flar\u0131n\u0131n (2015) \u00f6\u011frenme analiti\u011fi uygulamas\u0131 i\u00e7in RAPID Kazan\u0131m Haritalama Yakla\u015f\u0131m\u0131'n\u0131n (KHY) benimsenmesini savunmalar\u0131 dikkat \u00e7ekicidir. Bu model girdi boyutlar\u0131n\u0131 ba\u015flang\u0131\u00e7taki hedeflerin olu\u015fturulmas\u0131ndan son de\u011ferlendirmeye kadar yedi \u00f6nemli ad\u0131mdan olu\u015fan i\u015flemsel bir dizilimde sunar. Bununla birlikte, Ferguson\u2019un modeli \u00f6z\u00fcnde kavramsal olarak \u00fcretilmi\u015ftir. Model, deneysel ge\u00e7erlili\u011fi hakk\u0131nda \u00e7ok az kan\u0131t olmas\u0131na ra\u011fmen, yazarlar taraf\u0131ndan modelin potansiyel k\u0131lavuzlu\u011funu g\u00f6stermek ve kurumlara \u201cg\u00fcven\u201d vermek i\u00e7in savunulmu\u015f, Avustralya ve Birle\u015fik Krall\u0131k'taki \u00fcniversitelerde \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131 tan\u0131mlamak i\u00e7in bir mercek olarak kullan\u0131lm\u0131\u015ft\u0131r (Ferguson vd., 2015).<\/span><\/p>\n\n

                          MODELLER B\u0130ZE NE ANLATIR?<\/h2>\n

                          Bu modelleri g\u00f6zden ge\u00e7irmek, \u00f6\u011frenme analiti\u011fi da\u011f\u0131t\u0131mlar\u0131na arac\u0131l\u0131k eden boyutlar ve s\u00fcre\u00e7ler hakk\u0131nda fikir verirken, modellerin kavramsal ve \u00e7al\u0131\u015fma s\u0131n\u0131rlamalar\u0131n\u0131 da ortaya koymaktad\u0131r. Bu s\u0131n\u0131rlamalar modellerin karma\u015f\u0131k, \u00e7ok boyutlu olgular\u0131n incelenmesi i\u00e7in s\u0131n\u0131rl\u0131 veya tek boyutlu mercekleri benimsemelerini; \u00f6nc\u00fcl boyutlar\u0131 ve sonu\u00e7lar\u0131 tek bir modelde b\u00fct\u00fcnle\u015ftirememelerini ve tan\u0131mlanm\u0131\u015f arac\u0131l\u0131k boyutlar\u0131n\u0131n her birinin nispi belirginli\u011fi veya kritikli\u011fi konusundaki i\u00e7g\u00f6r\u00fclerinin s\u0131n\u0131rl\u0131l\u0131\u011f\u0131n\u0131 kapsar. Basit\u00e7e s\u00f6ylemek gerekirse, modeller i\u00e7g\u00f6r\u00fc kazan\u0131rken, \u00d6A uygulamalar\u0131n\u0131 \u015fekillendiren fakt\u00f6rlerin geni\u015fli\u011fini tam olarak yakalamamaktalar, bu nedenle y\u00f6neticilere \u00f6\u011frenme analiti\u011fi uygulamalar\u0131 konusunda rehberlik etmek i\u00e7in ihtiya\u00e7 duyulan ince, yerle\u015fik, detayl\u0131 i\u00e7g\u00f6r\u00fcler sunma yetenekleri k\u0131s\u0131tlanmaktad\u0131r.<\/span><\/p>\n

                          Bununla birlikte, \u00e7o\u011fu modelde belirgin olduklar\u0131 izlenimiyle birlikte bir\u00e7ok arac\u0131 boyutun veya elemanlar\u0131n\u0131n ortak oldu\u011fu g\u00f6r\u00fclm\u00fc\u015ft\u00fcr. Bunlar teknolojik haz\u0131rl\u0131klar\u0131, liderlik, \u00f6rg\u00fct k\u00fclt\u00fcr\u00fc, insan kaynaklar\u0131 ve kurumsal kapasiteyi ve stratejiyi kapsamaktad\u0131r. Tart\u0131\u015fmalar bu boyutlar\u0131n modellerde nas\u0131l i\u015fletildi\u011fi \u00e7er\u00e7evesinde devam etmektedir.<\/span><\/p>\n\n

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                                  Teknolojik Haz\u0131r Bulunu\u015fluk<\/h4>\n<\/li>\n<\/ol>\n<\/li>\n<\/ol>\n<\/li>\n<\/ol>\n<\/li>\n<\/ol>\n

                                  \u00d6\u011frenme analiti\u011fi temel olarak, elektronik verilere eri\u015fim ve i\u00e7g\u00f6r\u00fc sunmak i\u00e7in teknoloji sa\u011flanmas\u0131na dayand\u0131\u011f\u0131ndan, \u00d6A uygulama literat\u00fcr\u00fcnde teknolojinin \u201ctemel unsur\u201d olarak sunulmas\u0131 \u015fa\u015f\u0131rt\u0131c\u0131 de\u011fildir (Arnold, Lynch vd., 2014, s. 258; ayr\u0131ca bk. Greller ve Drachsler, 2012; Siemens ve Long, 2011). Bununla birlikte, teknolojik haz\u0131rl\u0131klar olarak tan\u0131mlanan boyutlar\u0131n i\u015flemselle\u015ftirilmesi modellere g\u00f6re de\u011fi\u015fmektedir. \u00d6rne\u011fin, baz\u0131 modeller veri toplayabilen, depolayabilen ve d\u00f6n\u00fc\u015ft\u00fcrebilen sa\u011flam bir teknoloji altyap\u0131s\u0131na duyulan ihtiyac\u0131 vurgulamakta iken (Arnold, Lynch vd., 2014, s. 258), baz\u0131lar\u0131 ise b\u00fct\u00fcnle\u015fik sistemlere, (Dawson, Heathcote ve Poole, 2010; Siemens ve Long, 2011), uygun analiz ara\u00e7lar\u0131na (Norris ve Baer, 2013), g\u00fcvenlik ve gizlilik kontrol ve s\u00fcre\u00e7lerine (\u00f6r. Bichsel'deki Y\u00fcksek \u00d6\u011fretim Modeli i\u00e7in EAAM Analitik Olgunluk Endeksi, 2012) olan ihtiyac\u0131 g\u00fc\u00e7lendirir. Deneysel olarak, teknolojinin \u00f6\u011frenme analiti\u011fi uygulamalar\u0131nda k\u0131s\u0131tlay\u0131c\u0131 bir unsur olarak potansiyel engelleyici rol\u00fc, Dawson vd., taraf\u0131ndan yap\u0131lan \u00e7al\u0131\u015fmalarda vurgulanm\u0131\u015ft\u0131r (Dawson vd., 2010; Macfadyen ve Dawson, 2012).<\/span><\/p>\n\n

                                  Liderlik<\/h3>\n

                                  Geni\u015f \u00f6l\u00e7ekli \u00f6\u011frenme analiti\u011finin s\u00fcrd\u00fcr\u00fclebilir uygulamalar\u0131 i\u00e7in liderli\u011fin \u00f6nemi kavramsal (Arnold, Lonn ve Pistilli, 2014; Arnold, Lynch vd., 2014; Laferriere, Hamel ve Searson, 2013; Norris ve Baer, 2013; Siemens vd., 2013) ve deneysel (Graham, Woodfield ve Harrison, 2013; Norris ve Baer, 2013) olarak iyi bilinmektedir. Bu literat\u00fcr, anlama ve b\u00fct\u00fcnle\u015fmeyi kolayla\u015ft\u0131rmak i\u00e7in \u00f6\u011frenme analiti\u011finin \u201cderin bilimsel anlay\u0131\u015f\u0131\u201dnda \u201cadanm\u0131\u015f\u201d ve \u201cbilgilendirilmi\u015f\u201d liderlik temelinin \u00f6nemini savunmaktad\u0131r (Arnold, Lynch vd., 2014, s. 260). \u00d6zellikle \u00f6l\u00e7ekli ve karma\u015f\u0131k projelerde kararl\u0131 \u00fcst d\u00fczey liderli\u011fe a\u00e7\u0131k bir bi\u00e7imde ihtiya\u00e7 olmas\u0131na ra\u011fmen (Norris ve Baer, 2013), b\u00f6yle bir liderli\u011fin nas\u0131l kavramsalla\u015ft\u0131r\u0131ld\u0131\u011f\u0131 konusunda yorum farkl\u0131l\u0131klar\u0131 vard\u0131r ve fikir birli\u011fi olu\u015fmam\u0131\u015ft\u0131r. \u00d6rne\u011fin, Laferriere vd. (2013) tek bak\u0131\u015fl\u0131 s\u0131n\u0131rl\u0131 boyutsall\u0131k mercekleri arac\u0131l\u0131\u011f\u0131yla liderli\u011fi i\u015flevselle\u015ftirilmi\u015ftir. Aksine, Arnold, Lynch vd. (2014) liderli\u011fi \u00e7ok katmanl\u0131, \u00e7ok boyutlu bir fenomen olarak kabul etmektedir. Liderlik ayn\u0131 zamanda literat\u00fcrde liderlik tarz\u0131 (Owston, 2013) veya liderlik davran\u0131\u015f\u0131 ve etkisi (Laferriere vd., 2013) olarak i\u015flevselle\u015ftirilirken, literat\u00fcr\u00fcn di\u011fer taraf\u0131 liderli\u011fin yap\u0131s\u0131na (Accard, 2015; Carbonell, Dailey \u2013 Hebert ve Gijselaers, 2013) ve (bk. Kotter ve Schlesinger, 2008, Arnold, Lynch vd., 2014) g\u00fcc\u00fcne at\u0131fta bulunur. Analitiklerin uygulanmas\u0131na ve anla\u015f\u0131lmas\u0131na yard\u0131mc\u0131 olmak i\u00e7in ara\u015ft\u0131rma destekli karma\u015f\u0131kl\u0131k (Hazy ve Uhl \u2013 Bien, 2014) veya da\u011f\u0131t\u0131lm\u0131\u015f liderlik modelleri (Bolden, 2011) alanda ivme kazanmaktad\u0131r.<\/span><\/p>\n\n

                                  Organizasyon K\u00fclt\u00fcr\u00fc<\/h3>\n

                                  Bir kurumun \u201cnormlar\u0131, inan\u00e7lar\u0131 ve de\u011ferleri\u201d olarak tan\u0131mlanan \u00f6rg\u00fct k\u00fclt\u00fcr\u00fc (Carbonell vd., 2013, s. 30), ayn\u0131 zamanda analitik uygulamalar\u0131n\u0131n \u00f6\u011frenilmesinde de kilit bir arac\u0131 olarak tan\u0131mlanm\u0131\u015ft\u0131r (Arnold, Lonn ve Pistilli, 2014; Carbonell vd., 2013; Greller ve Drachsler, 2012; Macfadyen ve Dawson, 2012). Personeldeki \u201cverilerle ilgili fark\u0131ndal\u0131k ve kabulleni\u015f\u201d (Arnold, Lonn ve Pistilli, 2014, s. 164), bir kurumun \u201ctarihsel pedagojik [ve] sosyo-k\u00fclt\u00fcrel varsay\u0131mlar\u0131n\u0131n\u201d potansiyel engelleyici etkisinin tan\u0131nmas\u0131, y\u00fcz y\u00fcze e\u011fitim uygulamalar\u0131 (Arnold, Lynch vd., 2014, s. 259), \u00f6rg\u00fctsel \u201crutinler\u201d (Carbonell vd., 2013, s. 29) ve hatta \u00f6rg\u00fctsel, pedagojik ve e\u011fitsel (BT ile ilgili) de\u011fi\u015fikliklere y\u00f6nelik personel kayg\u0131s\u0131 (Houchin ve MacLean, 2005) gibi konular bu literat\u00fcrde \u00f6ne \u00e7\u0131kmaktad\u0131r. Macfadyen ve Dawson\u2019\u0131n (2012) Kanada'daki b\u00fcy\u00fck bir \u00fcniversitesinde ba\u015far\u0131s\u0131z bir uygulamaya y\u00f6nelik ara\u015ft\u0131rmalar\u0131nda yeterince haz\u0131rlanmam\u0131\u015f ve yeni fikirlere a\u00e7\u0131k olmayan bir \u00f6rg\u00fctsel k\u00fclt\u00fcr\u00fcn etkisine dair deneysel i\u00e7g\u00f6r\u00fc sunulmu\u015ftur. Ara\u015ft\u0131rmac\u0131lar, kurumun \u00f6\u011frenme analiti\u011finin potansiyeli ile ilgili olarak, istekli ve yeni fikirlere bir \u015fekilde takdir, kavray\u0131\u015f geli\u015ftirmedeki ba\u015far\u0131s\u0131zl\u0131\u011f\u0131n\u0131n, kurumun tutarl\u0131 ve ba\u015far\u0131l\u0131 bir \u00f6\u011frenme analiti\u011fi stratejisi olu\u015fturamamas\u0131n\u0131n kilit bir nedeni oldu\u011funu g\u00f6zlemlemi\u015ftir.<\/span><\/p>\n\n

                                  Personel ve Kurumsal Kapasite<\/h3>\n

                                  \u201c\u0130deal\u201d (Greller ve Drachsler, 2012, s. 51) \u00f6\u011frenme analiti\u011fi kazan\u0131mlar\u0131, personelin analitik zek\u00e2y\u0131 etkili bir \u015fekilde analiz etme, yorumlama ve anlaml\u0131 \u015fekilde kar\u015f\u0131lama yetene\u011fine ba\u011fl\u0131d\u0131r (Bichsel, 2012; Norris ve Baer, 2013). Bununla birlikte, payda\u015flar\u0131n \u00f6\u011frenme analiti\u011fi i\u00e7in talep edilen gerekli analitik veya yorumlay\u0131c\u0131 veri becerilerine sahip oldu\u011fu varsay\u0131lamaz. Norris ve Baer (2013) \u201cbir\u00e7ok kurumsal liderin, i\u015fletmelerinin veri, bilgi ve analitik konusundaki kapasitesine oldu\u011fundan daha fazla de\u011fer bi\u00e7ti\u011fini\u201d g\u00f6zlemlemektedir (s. 40). Drachsler ve Greller\u2019in (2012) \u00f6\u011frenme analiti\u011fi uygulamalar\u0131nda gerekli olan boyutlara y\u00f6nelik ara\u015ft\u0131rmas\u0131nda, boyutlar sert ve yumu\u015fak boyutlar olarak ayr\u0131l\u0131r: yumu\u015fak boyutlar, \u00f6zellikle \u201cyeterlilikler ve kabullenme\u201d gibi \u00f6\u011frenme analiti\u011finin etkinli\u011fini \u015fekillendiren \u201cinsan fakt\u00f6rlerini\u201d(s. 43); \u201csert\u201d boyutlar, ise teknoloji, veri ve algoritmalar d\u00e2hil, insana \u00f6zg\u00fc olmayan, daha az \u00f6znel unsurlar\u0131 ifade eder. Sert ve yumu\u015fak boyutlar\u0131 birbirinden ay\u0131rmak, kurumlar\u0131n \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131 teknik ve altyap\u0131 sorunlar\u0131n\u0131n \u00f6tesinde, sosyo-k\u00fclt\u00fcrel kayg\u0131lar\u0131 da i\u00e7erecek \u015fekilde g\u00f6rmelerine duyulan ihtiyac\u0131 vurgulamaktad\u0131r. \u00d6\u011frenme analiti\u011finin ba\u015far\u0131l\u0131 bir \u015fekilde benimsenmesi, bu iki alanda kapasite geli\u015ftirmeyi gerektirir.<\/span><\/p>\n

                                  \u00d6\u011frenme Analiti\u011fine Haz\u0131rl\u0131k Arac\u0131 (\u00d6AHA; Arnold, Lonn ve Pistilli, 2014) kapasitenin farkl\u0131 bir \u015fekilde kavramsalla\u015ft\u0131r\u0131lmas\u0131n\u0131 ortaya koyuyor: kurumsal haz\u0131rl\u0131k ba\u015fka bir deyi\u015fle bir kurumun \u00f6\u011frenme analiti\u011fi giri\u015fimini uygulamak i\u00e7in ne kadar \"haz\u0131r\" oldu\u011funun \u00f6l\u00e7\u00fcs\u00fc. Haz\u0131rl\u0131\u011f\u0131 be\u015f boyutta i\u015flevselle\u015ftirirler: 1) yetenek, 2) veri, 3) k\u00fclt\u00fcr ve s\u00fcre\u00e7, 4) y\u00f6neti\u015fim ve altyap\u0131 ve 5) genel haz\u0131r olma alg\u0131s\u0131. Kavramsalla\u015ft\u0131rmalar\u0131, kapasitenin \u00e7ok katmanl\u0131 do\u011fas\u0131n\u0131 vurgulamakta, kapasitenin makro (yani geni\u015f, kurumun tamam\u0131) ve mikro (bireysel payda\u015flar\u0131n seviyesi) seviyelerde \u00e7al\u0131\u015ft\u0131\u011f\u0131n\u0131 belirtmektedir. Son olarak, teknik, kritik ve yorumlay\u0131c\u0131 kapasiteye odaklanman\u0131n aksine, Siemens, Dawson ve Lynch (2013), personelin pedagoji ve analitik aras\u0131nda etkili bir \u201cba\u011f kurabilme\u201d yetene\u011finin de kapasitenin kapsam\u0131nda oldu\u011funu \u00f6ne s\u00fcrerek bize \u00f6\u011frenme analiti\u011fi ile \u00f6\u011fretme ve \u00f6\u011frenme prati\u011fi aras\u0131ndaki ili\u015fkiyi hat\u0131rlat\u0131r.<\/span><\/p>\n\n

                                  Strateji<\/h3>\n

                                  Kavramsal literat\u00fcr, politika ve prosed\u00fcrlerin geli\u015ftirilmesi yoluyla a\u00e7\u0131k bir vizyon ve \u00f6\u011frenme analiti\u011fi amac\u0131n\u0131n geli\u015ftirilmesini savunur. \u00d6rne\u011fin, Arnold, Lonn ve Pistilli'nin (2014) kavramsal olarak geli\u015ftirilen \u00d6\u011frenme Analiti\u011fi Haz\u0131rl\u0131k Arac\u0131 (\u00d6AHA), politikalar\u0131 y\u00f6neti\u015fim ve altyap\u0131 etiketli daha geni\u015f bir arac\u0131 boyutlar kategorisine yerle\u015ftirmektedir. Ayr\u0131ca, Norris and Baer'in \u201cAnalitik \u0130\u00e7in Kurumsal Kapasite\u201d modeli (2013), \u201cS\u00fcre\u00e7ler ve Uygulamalar\u201d\u0131 \u00d6A i\u00e7in \u00f6rg\u00fctsel kapasitenin be\u015f temel arac\u0131 boyutundan biri olarak tan\u0131mlar ve onu analiti\u011fi, eylemleri ve m\u00fcdahaleleri g\u00fc\u00e7lendirmek [..] \u00fczere \u201crutinle\u015fmi\u015f s\u00fcre\u00e7ler ve i\u015f ak\u0131\u015flar\u0131 olarak i\u015fler hale getirilir\u201d (s. 31). Bununla birlikte, aksine, deneysel \u00e7al\u0131\u015fmalar strateji belirlemenin \u00f6nemini vurgular ve uyumla\u015ft\u0131r\u0131lm\u0131\u015f politika ve hedeflere olan ihtiyac\u0131 (Macfadyen ve Dawson, 2012; Owston, 2013) vurgular ki; ba\u015far\u0131s\u0131z olmu\u015f bir \u00f6\u011frenme analiti\u011fi program\u0131 analizlerinde Macfadyen ve Dawson (2012), \u00f6\u011frenme analiti\u011fi uygulamalar\u0131nda \u00f6rg\u00fctsel bir strateji ve vizyonun olu\u015fturulmas\u0131n\u0131n \u201ckritik\u201d (s. 150) oldu\u011funu belirtmektedirler.<\/span><\/p>\n\n

                                  K\u0131saca<\/h3>\n

                                  Bu k\u0131sa literat\u00fcr taramas\u0131, \u00f6\u011frenme analiti\u011fi modellerinin, y\u00f6neticilere \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131 \u015fekillendiren s\u00fcre\u00e7ler ve boyutlar hakk\u0131nda de\u011ferli bilgiler sa\u011flayabilece\u011fini ortaya koymu\u015ftur. \u00d6\u011frenme analiti\u011fi uygulama kazan\u0131mlar\u0131 \u00fczerinde etkisi olan \u00f6zellikle be\u015f boyut, bir\u00e7ok uygulama \u00e7at\u0131s\u0131nda s\u0131k\u00e7a vurgulanm\u0131\u015ft\u0131r: teknolojik haz\u0131rl\u0131k, liderlik, kurum k\u00fclt\u00fcr\u00fc, insan kayna\u011f\u0131 ve \u00f6\u011frenme analiti\u011fi i\u00e7in kurumsal kapasite ve \u00f6\u011frenme analiti\u011fi stratejisi. Bununla birlikte, daha \u00f6nce belirtti\u011fimiz gibi, bu boyutlar\u0131n i\u015flevselle\u015fmesi literat\u00fcrde \u00e7e\u015fitlilik g\u00f6stermi\u015ftir. Ayr\u0131ca, modeller boyutlar\u0131n g\u00f6receli belirginli\u011fi veya kritikli\u011fi hakk\u0131nda \u00e7ok az fikir vermi\u015ftir. Literat\u00fcrde boyutlarla ilgili belirtilen farkl\u0131 kavramsalla\u015ft\u0131rmalar\u0131n ve i\u015flevselle\u015ftirmelerinin, kurumlar\u0131n kendileri i\u00e7in mevcut olan bir\u00e7ok \u00f6\u011frenme analiti\u011fi uygulama \u00e7at\u0131lar\u0131yla nas\u0131l etkile\u015fimde bulunacaklar\u0131 ve onlar\u0131 nas\u0131l yorumlayacaklar\u0131na dair arac\u0131l\u0131k etme potansiyeli oldu\u011funu \u00f6ne s\u00fcr\u00fcyoruz.<\/span><\/p>\n

                                  Ayr\u0131ca ve \u00f6nemli \u00f6l\u00e7\u00fcde, bu incelmede sunulan literat\u00fcr a\u011f\u0131rl\u0131kl\u0131 olarak kavramsald\u0131r. \u00d6\u011frenme analiti\u011fi uygulamalar\u0131na y\u00f6nelik deneysel ara\u015ft\u0131rma eksikli\u011finin, onlara arac\u0131l\u0131k eden s\u00fcre\u00e7ler ve boyutlar konusundaki anlay\u0131\u015f\u0131m\u0131z\u0131 engelledi\u011fini savunuyoruz. Kavramsal literat\u00fcr, i\u00e7g\u00f6r\u00fc kazanmas\u0131na ra\u011fmen, kendi karma\u015f\u0131kl\u0131\u011f\u0131n\u0131 ve n\u00fcans\u0131n\u0131 tam olarak yakalayamayacak ideal bir \u00f6\u011frenme analiti\u011fi modeli sunma riski ta\u015f\u0131yor. Deneysel tekniklerin kullan\u0131ld\u0131\u011f\u0131 yerlerde (\u00f6r. anketler ve odak gruplar\u0131 yoluyla veri toplama gibi), yap\u0131sal ge\u00e7erlili\u011fi \u00e7evreleyen \u00e7ok az ayr\u0131nt\u0131 vard\u0131r. Buna g\u00f6re, modellerdeki farkl\u0131 boyutlar aras\u0131ndaki ili\u015fkilerin b\u00fcy\u00fck \u00f6l\u00e7\u00fcde denenmemi\u015f oldu\u011fu g\u00f6r\u00fclmektedir. Bu b\u00f6l\u00fcmde daha \u00f6nce g\u00f6r\u00fcld\u00fc\u011f\u00fc gibi, y\u00fcksek\u00f6\u011fretim kurumlar\u0131ndaki \u00f6\u011frenme analiti\u011fi programlar\u0131n\u0131n nispi olgunla\u015fmam\u0131\u015fl\u0131\u011f\u0131 k\u0131smen \u00f6\u011frenme analiti\u011fini \u00e7evreleyen bu deneysel yetersizli\u011fe katk\u0131da bulunur. Bununla birlikte, y\u00fcksek\u00f6\u011fretim kurumlar\u0131nda bulunan uygulamalar\u0131n her ne kadar yeni geli\u015fmekte olsalar da \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131n \u015fu anda ba\u011flamda nas\u0131l i\u015fletildi\u011fini ve y\u00f6nlendirildi\u011fini deneysel olarak derinlemesine incelemek i\u00e7in bir f\u0131rsat sundu\u011funu savunuyoruz.<\/span><\/p>\n\n

                                  G\u00d6ZLEME DAYALI OLANI SUNMAK<\/h2>\n

                                  Avustralya'da yap\u0131lan son \u00e7al\u0131\u015fmalar, bu ara\u015ft\u0131rma eksikli\u011fini gidermeye \u00e7al\u0131\u015fm\u0131\u015ft\u0131r. Colvin vd. (2015), Avustralya y\u00fcksek\u00f6\u011frenim sekt\u00f6r\u00fcnde \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131 ara\u015ft\u0131ran geni\u015f bir ulusal \u00e7al\u0131\u015fma ger\u00e7ekle\u015ftirmi\u015ftir. Veriler, 32 \u00fcniversitede \u00f6\u011frenme analitiklerini uygulama sorumlulu\u011funu \u00fcstlenen \u00fcst d\u00fczey liderlerle yap\u0131lan nitel g\u00f6r\u00fc\u015fmeler yoluyla toplanm\u0131\u015ft\u0131r. Bir karma y\u00f6ntem metodolojisini kullanan bu \u00e7al\u0131\u015fma, \u00f6\u011frenme analiti\u011fi uygulamalar\u0131nda istatistiksel olarak anlaml\u0131 bir etkiye sahip ve t\u00fcmevar\u0131msal olarak olu\u015fturulmu\u015f alt\u0131 boyut (verilerde tan\u0131mlanan 27 boyut i\u00e7inden) tan\u0131mlam\u0131\u015ft\u0131r. B\u00fcy\u00fck \u00f6l\u00e7\u00fcde \u00f6nceki literat\u00fcrden yans\u0131makla birlikte, etkide bulunan boyutlar\u0131n d\u00f6rd\u00fc etkili ve dengeli payda\u015f<\/i><\/span> kat\u0131l\u0131m\u0131, teknolojik kapasite, a\u00e7\u0131k vizyon<\/i><\/span> ve strateji<\/i><\/span> ile etkili liderli\u011fi<\/i><\/span> i\u00e7ermektedir.\nOrtaya \u00e7\u0131kan di\u011fer iki boyut ise kurumsal ba\u011flam (bir kurumun \u00f6\u011frencisi ve kurumsal profil d\u00e2hil) ve kavramsalla\u015ft\u0131rmad\u0131r (bir kurumun \u00f6\u011frenme analiti\u011fini nas\u0131l olu\u015fturdu\u011fu ve anlad\u0131\u011f\u0131). Bu boyutlardan ilki olan kurumsal ba\u011flam, bize \u00f6\u011frenme analiti\u011finin, her kurumun ba\u011flam\u0131na \u00f6zg\u00fc olarak sosyal ve kurumsal alanda bir dizi yap\u0131sal unsur taraf\u0131ndan \u015fekillendirilmi\u015f pratikte bulundu\u011funu hat\u0131rlat\u0131r. Buna kar\u015f\u0131l\u0131k, \u201ckavramsalla\u015ft\u0131rma\u201d boyutu bir kurumun \u00f6\u011frenme analiti\u011fi uygulamalar\u0131na ili\u015fkin temel epistemolojik ve ontolojik konumuyla ba\u011flant\u0131l\u0131d\u0131r. Kurumlar \u00f6\u011frenme analiti\u011fi ile ilgili olarak farkl\u0131 anlay\u0131\u015f, \u00f6zlem ve vizyonlara sahip olsalar da \u00f6\u011frenme analitiklerinin bir kurum taraf\u0131ndan nas\u0131l kavramsalla\u015ft\u0131r\u0131ld\u0131\u011f\u0131 ve ger\u00e7ekte nas\u0131l uyguland\u0131\u011f\u0131 aras\u0131nda ili\u015fkiler bulunmu\u015ftur. Basit\u00e7e, bu \u00e7al\u0131\u015fman\u0131n bulgular\u0131, \u00f6\u011frenme analiti\u011finin anla\u015f\u0131lma \u015fekli ve ona y\u00fcklenen anlam\u0131n, \u00f6\u011frenme analiti\u011finin uygulanmas\u0131n\u0131 nas\u0131l \u015fekillendirdi\u011fini g\u00f6stermektedir. Ayr\u0131ca ara\u015ft\u0131rmada yap\u0131lan k\u00fcmeleme analizi, Avustralya y\u00fcksek\u00f6\u011frenim ba\u011flam\u0131nda iki \u00f6\u011frenme analiti\u011fi uygulama y\u00f6r\u00fcngesinin ortaya \u00e7\u0131kmas\u0131n\u0131 \u00f6nermi\u015ftir. K\u00fcmelerin her birinde, kavramsalla\u015ft\u0131rma, haz\u0131r bulunu\u015fluk (\u00f6nc\u00fcl) ve uygulama boyutlar\u0131n\u0131n kurumlar aras\u0131nda nas\u0131l uyguland\u0131\u011f\u0131 ve tecr\u00fcbe edildi\u011fi konusunda bir uyum mevcuttur. Bir k\u00fcmeleme etkili bir kavramsalla\u015ft\u0131rmay\u0131 ve elde tutma (\u00f6\u011frenci ba\u015far\u0131s\u0131n\u0131 s\u00fcrd\u00fcrme), riskli \u00f6\u011frenci tabanl\u0131 \u00f6\u011frenme analiti\u011fi i\u015flevselle\u015ftirmesini daha ayr\u0131cal\u0131kl\u0131 k\u0131lar g\u00f6r\u00fcnmekteydi. Buna kar\u015f\u0131l\u0131k, ikinci k\u00fcmelenmedeki kurumlar da elde tutma-odakl\u0131 (\u00f6\u011freneni) \u00f6\u011frenme analiti\u011fi faaliyetine yat\u0131r\u0131m yapm\u0131\u015f ancak bunu i\u00e7g\u00f6r\u00fc kazand\u0131rma ama\u00e7l\u0131 etkinlik ve \u00f6\u011fretme-\u00f6\u011frenme s\u00fcrecine y\u00f6nelik bilgilendirme ile desteklemi\u015ftir. Colvin vd.nin (2015) Avustralya'da y\u00fcksek\u00f6\u011frenim ba\u011flam\u0131nda \u00f6\u011frenme analiti\u011finin iki farkl\u0131 uygulama \u00f6r\u00fcnt\u00fcs\u00fcn\u00fcn ortaya \u00e7\u0131kt\u0131makta oldu\u011fu g\u00f6r\u00fcnen bulundu\u011funa y\u00f6nelik bulgusu, bir\u00e7ok mevcut \u00f6\u011frenme analiti\u011fi uygulama \u00e7er\u00e7evesinin temelini olu\u015fturan b\u00fcy\u00fck \u00f6l\u00e7\u00fcde \u00f6zc\u00fc ve pozitivist ontolojik ve epistemolojik varsay\u0131mlara meydan okumaktad\u0131r (bk. Davenport ve Harris, 2007).<\/span><\/p>\n\n

                                  Yinelemeli, Dinamik ve S\u00fcrd\u00fcr\u00fclebilir Olarak \u00d6\u011frenme Analiti\u011fi Uygulamalar\u0131<\/h3>\n

                                  \u015eekil 24.1, Colvin vd. (2015), dinamik olarak birbirine ba\u011fl\u0131 ve ge\u00e7ici olan olguyu temsil eden karma\u015f\u0131k Stratejik Beceri modeline dayanan \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131 sunmakta ve \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131n fiil\u00ee performans\u0131n\u0131n gelecekteki kapasiteyi olu\u015fturaca\u011f\u0131n\u0131 \u00f6ne s\u00fcrmektedirler.<\/span><\/p>\n

                                  \"\"<\/p>\n<\/a> \u015eekil 24.1. Stratejik Beceri Modeli (Colvin vd., 2015, s. 28).<\/i><\/span><\/span>\n

                                  \u015eekil 24.1, Colvin vd., karma\u015f\u0131k, dinamik olarak birbirine ba\u011fl\u0131 ve ge\u00e7ici olan olguyu temsil eden Stratejik Beceri \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131 sunmaktad\u0131r ve \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131n fiil\u00ee performans\u0131n\u0131n gelecekteki kapasite \u00fcretece\u011fini \u00f6ne s\u00fcrmektedir. Bu bak\u0131mdan, yazarlar taraf\u0131ndan da g\u00f6zlemlendi\u011fi gibi Minimal Uygulanabilir \u00dcr\u00fcn (MU\u00dc) (Munch vd., 2013) ve H\u0131zl\u0131 \u0130novasyon D\u00f6ng\u00fcs\u00fc (Kaski, Alamaki ve Moisio, 2014) ilkeleri ile bu ilkelerin savundu\u011fu \u00fcr\u00fcn geli\u015ftirme ve b\u00fct\u00fcnle\u015ftirmesindeki devaml\u0131, yinelemeli, \u00f6zyinelemeli, s\u00fcre\u00e7 yakla\u015f\u0131m\u0131 hem \u00f6\u011frenme analiti\u011fi uygulama alan\u0131nda bir a\u011f\u0131rl\u0131\u011fa sahiptir hem de kurumsal liderlere olas\u0131 uygulama paradigmalar\u0131 olarak \u00f6nerilmektedir.<\/span><\/p>\n\n

                                  SONU\u00c7<\/h2>\n

                                  Colvin vd.nin (2015) \u00e7al\u0131\u015fmas\u0131, \u00f6\u011frenme analiti\u011fi uygulamalar\u0131na ili\u015fkin ara\u015ft\u0131rma literat\u00fcr\u00fcne \u00f6nemli deneysel ve metodolojik katk\u0131lar yapar. \u00d6ncelikle, \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131n \u00f6nc\u00fclleri (sa\u011flay\u0131c\u0131lar\u0131) ve kazan\u0131mlar\u0131 (yani nas\u0131l g\u00f6r\u00fcnd\u00fckleri<\/i><\/span>) aras\u0131ndaki ili\u015fkilere dair deneysel i\u00e7g\u00f6r\u00fcler sa\u011flar. \u00d6\u011frenme analiti\u011finin ve \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131n ger\u00e7ek anlamlar\u0131na dair kat\u0131l\u0131mc\u0131lardan fikirlerinin, niyetlerinin, alg\u0131lay\u0131\u015flar\u0131n\u0131n istenmesi sayesinde kurumsal liderlerin \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131 kavramsalla\u015ft\u0131rma yollar\u0131na dair ince ve ayr\u0131nt\u0131l\u0131 i\u00e7g\u00f6r\u00fcler kazan\u0131lm\u0131\u015f, bu kavramsalla\u015ft\u0131rmalar ile mevcut i\u015flevselle\u015ftirmeler aras\u0131ndaki ili\u015fkilerin ortaya \u00e7\u0131kmas\u0131 sa\u011flanm\u0131\u015ft\u0131r.<\/span><\/p>\n

                                  \u00c7ok boyutlu bir olgu olarak Colvin vd.nin (2015) yapt\u0131klar\u0131 ara\u015ft\u0131rmadaki \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131n kavramsalla\u015ft\u0131r\u0131lmas\u0131 ve analizi, ortaya \u00e7\u0131kan \u00f6\u011frenme analiti\u011fi uygulama literat\u00fcr\u00fcn\u00fcn ilkeleriyle uyumludur (bk. Ferguson vd., 2015; Greller ve Drachsler, 2012) ve onlar\u0131n ara\u015ft\u0131rmalar\u0131 sonucu olu\u015fturulan Stratejik Beceri Modeli \u00e7oklu, kesi\u015fen, birbirine ba\u011f\u0131ml\u0131 fakt\u00f6rlerin ge\u00e7ici, yerle\u015fik, dinamik bir sonucu olarak \u00f6\u011frenme analitiklerinin zengin, b\u00fct\u00fcnsel, sistemik bir kavramsalla\u015ft\u0131rmas\u0131n\u0131 sunmaktad\u0131r. Yine de \u00f6zellikle \u00f6nemli olan, \u00f6\u011frenme analiti\u011fi uygulamalar\u0131na arac\u0131l\u0131k eden birincil sosyok\u00fclt\u00fcrel, teknik ve yap\u0131sal fakt\u00f6rlerin g\u00f6reli belirginli\u011fine dair Colvin vd.nin (2015) sa\u011flad\u0131\u011f\u0131 deneysel i\u00e7g\u00f6r\u00fcd\u00fcr.<\/span><\/p>\n

                                  Colvin vd.nin (2015) \u00f6\u011frenme analiti\u011fi sunumu, \u00f6\u011frenme analiti\u011fini genellikle do\u011frusal ve\/veya tek boyutlu bir olgu olarak \u00e7er\u00e7eveleyen bir\u00e7ok mevcut modelden ayr\u0131l\u0131r. Bu son kavramsalla\u015ft\u0131rmalar\u0131n, indirgemeci y\u00f6nelimleriyle, \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131n karma\u015f\u0131kl\u0131\u011f\u0131n\u0131, geni\u015fli\u011fini veya bozulmas\u0131n\u0131 tam olarak yakalama potansiyeline sahip olmad\u0131\u011f\u0131n\u0131 ve s\u00fcrd\u00fcr\u00fclebilir ve etkili \u00f6\u011frenme analiti\u011fi uygulama ve stratejilerinin benimsenmesine ve geli\u015ftirilmesine kar\u015f\u0131 istenmeden engelleyici olabilece\u011fini \u00f6ne s\u00fcr\u00fcyoruz. Buna kar\u015f\u0131l\u0131k, Colvin vd.nin (2015) bulgular\u0131 bize \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131n karma\u015f\u0131k oldu\u011funu, birbirine ba\u011f\u0131ml\u0131 \u201cyumu\u015fak ve sert\u201d boyutlarla \u015fekillendirildi\u011fini hat\u0131rlatmaktad\u0131r (Greller ve Drachsler, 2012) ve bu bulgular ayn\u0131 zamanda \u00fcniversitelerdeki geleneksel y\u00f6netim ve \u00f6rg\u00fctsel yap\u0131lara meydan okuyup par\u00e7alama potansiyeline de sahiptir. Ara\u015ft\u0131rmalar\u0131, \u00f6\u011frenme analiti\u011fi y\u00f6neticilerine, \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131n karma\u015f\u0131kl\u0131\u011f\u0131n\u0131 vurgulayan, ba\u011flam\u0131n arac\u0131 rol\u00fcn\u00fc tan\u0131yan, kurum i\u00e7i ve kurumlar aras\u0131 \u00f6\u011frenme analiti\u011fi stratejileri ve \u00f6nceliklerinin de\u011ferlendirmesini kolayla\u015ft\u0131rabilen deneysel olarak t\u00fcretilmi\u015f kavramsal bir \u00e7er\u00e7eve sa\u011flar.<\/span><\/p>\n

                                  Colvin vd.nin (2015) ara\u015ft\u0131rmas\u0131n\u0131n s\u0131n\u0131rl\u0131l\u0131klar\u0131 oldu\u011fu belirtilmelidir: verileri \u00f6ncelikli olarak nitelikseldir ve bir y\u00fcksek\u00f6\u011fretim ba\u011flam\u0131nda (Avustralya) bulunan nispeten k\u00fc\u00e7\u00fck bir kurum kat\u0131l\u0131mc\u0131s\u0131 \u00f6rne\u011finden (n = 32) derlenmi\u015ftir. Bu nedenle, bulgular\u0131n alternatif y\u00fcksek\u00f6\u011fretim ba\u011flamlar\u0131na do\u011frudan uygulanmas\u0131 durumunda, daha dikkatli davran\u0131lmal\u0131d\u0131r. Ayr\u0131ca, \u00e7o\u011fu kurum \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131n \u00e7ok erken a\u015famalarda yer ald\u0131lar: programlar\u0131 hen\u00fcz iptidai ve hala geli\u015ftirilmekteydi. \u00d6nc\u00fcl boyutlar ve kazan\u0131mlar aras\u0131nda bildirilen ili\u015fkiler bu nedenle bu ge\u00e7ici s\u0131n\u0131rlamalar i\u00e7inde yorumlanmal\u0131d\u0131r. \u00d6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131n deneysel analizlerinin bu kritik alana daha ayr\u0131nt\u0131l\u0131 bir bak\u0131\u015f a\u00e7\u0131s\u0131 sa\u011flayacak \u015fekilde zaman i\u00e7erisinde yap\u0131lmas\u0131 tavsiye edilir. Bununla birlikte, Colvin vd. (2015) \u00e7al\u0131\u015fmalar\u0131, daha geni\u015f analitik toplulu\u011fu ile uyumlu olmas\u0131 beklenen \u00e7ok boyutluluk ve karma\u015f\u0131kl\u0131k ilkeleri d\u00e2hilinde \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131 temel alan bir analitik \u00e7er\u00e7eve sunmaktad\u0131r.<\/span><\/p>\n\n

                                  KAYNAK\u00c7A<\/h2>\nAccard, P. (2015). Complex hierarchy: The strategic advantages of a trade-off between hierarchical supervision and self-organizing. European Management Journal, 33<\/i>(2), 89\u2013103. <\/span><\/span>\n\nArnold, K. E., Lonn, S., & Pistilli, M. D. (2014). An exercise in institutional reflection: The learning analytics readiness instrument (LARI). Proceedings of the 4th International Conference on Learning Analytics and Knowledge <\/i>(LAK\u201914), 24\u201328 March 2014, Indianapolis, IN, USA (pp. 163\u2013167). New York: ACM. <\/span><\/span>\n\nArnold, K. E., Lynch, G., Huston, D., Wong, L., Jorn, L., & Olsen, C. W. (2014). Building institutional capacities and competencies for systemic learning analytics initiatives. Proceedings of the 4th International Conference on Learning Analytics and Knowledge <\/i>(LAK\u201914), 24\u201328 March 2014, Indianapolis, IN, USA (pp. 257\u2013260). New York: ACM. <\/span><\/span>\n\nBaker, R., & Inventado, P. (2014). Educational data mining and learning analytics. In J. A. Larusson & B. White (Eds.), Learning analytics <\/i>(pp. 61\u201375). New York: Springer. <\/span><\/span>\n\nBichsel, J. (2012). Analytics in higher education: Benefits, barriers, progress and recommendations. Louisville, CO: EDUCAUSE Center for Applied Research. <\/span><\/span>\n\nBolden, R. (2011). Distributed leadership in organizations: A review of theory and research. International Journal of Management Reviews, 13<\/i>(3), 251\u2013269. <\/span><\/span>\n\nCarbonell, K. B., Dailey-Hebert, A., & Gijselaers, W. (2013). Unleashing the creative potential of faculty to create blended learning. The Internet and Higher Education, 18<\/i>, 29\u201337. <\/span><\/span>\n\nColvin, C., Rogers, T., Wade, A., Dawson, S., Ga\u0161evi\u0107, D., Buckingham Shum, S., . . . Fisher, J. (2015). Student retention and learning analytics: A snapshot of Australian practices and a framework for advancement. <\/i>Canberra, ACT: Australian Government Office for Learning and Teaching. <\/span><\/span>\n\nConde, M. \u00c1., & Hern\u00e1ndez-Garc\u00eda, \u00c1. (2015). Learning analytics for educational decision making. Computers in Human Behavior, 47<\/i>, 1\u20133. <\/span><\/span>\n\nDaniel, B. (2015). Big data and analytics in higher education: Opportunities and challenges. British Journal of Educational Technology, 46<\/i>(5), 904\u2013920. <\/span><\/span>\n\nDavenport, T. H., & Harris, J. G. (2007). Competing on analytics: The new science of winning<\/i>. Boston, MA: Harvard Business School Press. <\/span><\/span>\n\nDawson, S., Heathcote, L., & Poole, G. (2010). Harnessing ICT potential. International Journal of Educational Management, 24<\/i>(2), 116\u2013128. <\/span><\/span>\n\nDrachsler, H., & Greller, W. (2012). The pulse of learning analytics understandings and expectations from the stakeholders. Proceedings of the 2nd International Conference on Learning Analytics and Knowledge <\/i>(LAK\u201912), 29 April\u20132 May 2012, Vancouver, BC, Canada (pp. 120\u2013129). New York: ACM. <\/span><\/span>\n\nECAR-ANALYTICS Working Group. (2015). The predictive learning analytics revolution: Leveraging learning data for student success ECAR working group paper. Louisville, CO: EDUCAUSE. <\/span><\/span>\n\nFerguson, R., Macfadyen, L., Clow, D., Tynan, B., Alexander, S., & Dawson, S. (2015). Setting learning analytics in context: Overcoming the barriers to large-scale adoption. Journal of Learning Analytics, 1<\/i>(3), 120\u2013144. <\/span><\/span>\n\nForeman, S. (2013a). Five steps to evaluate and select an LMS: Proven practices. Learning Solutions Magazine<\/i>. http:\/\/www.learningsolutionsmag.com\/articles\/1181\/five-steps-to-evaluate-and-select-an-lms-proven-practices. <\/span><\/span>\n\nForeman, S. (2013b). The six proven steps for successful LMS implementation. Learning Solutions Magazine<\/i>. http:\/\/www.learningsolutionsmag.com\/articles\/1214\/the-six-proven-steps-for-successful-lms-implementation-part-1-of-2. <\/span><\/span>\n\nGraham, C. R., Woodfield, W., & Harrison, J. B. (2013). A framework for institutional adoption and implementation of blended learning in higher education. The Internet and Higher Education, 18<\/i>, 4\u201314. <\/span><\/span>\n\nGreller, W., & Drachsler, H. (2012). Translating learning into numbers: A generic framework for learning analytics. Journal of Educational Technology & Society, 15<\/i>(3), 42\u201357. <\/span><\/span>\n\nHazy, J. K., & Uhl-Bien, M. (2014). Changing the rules: The implications of complexity science for leadership research and practice. In D. V. Day (Ed.), Oxford Handbook of Leadership and Organizations<\/i>. Oxford, UK: Oxford University Press. <\/span><\/span>\n\nHouchin, K., & MacLean, D. (2005). Complexity theory and strategic change: An empirically informed critique. British Journal of Management, 16<\/i>(2), 149\u2013166. <\/span><\/span>\n\nKaski, T., Alam\u00e4ki, A., & Moisio, A. (2014). A multi-discipline rapid innovation method. Interdisciplinary Studies Journal, 3<\/i>(4), 163. <\/span><\/span>\n\nKotter, J. P., & Schlesinger, L. A. (2008). Leading Change<\/i>. Boston, MA: Harvard Business Review Press. <\/span><\/span>\n\nLaferri\u00e8re, T., Hamel, C., & Searson, M. (2013). Barriers to successful implementation of technology integration in educational settings: A case study. Journal of Computer Assisted Learning, 29<\/i>(5), 463\u2013473. <\/span><\/span>\n\nMacfadyen, L., & Dawson, S. (2012). Numbers are not enough. Why e-learning analytics failed to inform an institutional strategic plan. Educational Technology & Society, 15<\/i>(3), 149\u2013163. <\/span><\/span>\n\nMacfadyen, L., Dawson, S., Pardo, A., & Ga\u0161evi\u0107, D. (2014). Embracing big data in complex educational systems: The learning analytics imperative and the policy challenge. Research & Practice in Assessment, 9<\/i>(2), 17\u201328. <\/span><\/span>\n\nM\u00fcnch, J., Fagerholm, F., Johnson, P., Pirttilahti, J., Torkkel, J., & J\u00e4arvinen, J. (2013). Creating minimum viable products in industry-academia collaborations. In B. Fitzgerald, K. Conboy, K. Power, R. Valerdi, L. Morgan, & K.-J. Stol (Eds.), Lean Enterprise Software and Systems <\/i>(Vol. 167, pp. 137\u2013151). Springer Berlin Heidelberg. <\/span><\/span>\n\nNorris, D., Baer, L., Leonard, J., Pugliese, L., & Lefrere, P. (2008). Action analytics: Measuring and improving performance that matters in higher education. EDUCAUSE Review, 43<\/i>(1), 42.<\/span><\/span>\n\nNorris, D. M., & Baer, L. L. (2013). Building organizational capacity for analytics<\/i>. Louisville, CO: EDUCAUSE. <\/span><\/span>\n\nOster, M., Lonn, S., Pistilli, M. D., & Brown, M. G. (2016). The learning analytics readiness instrument. Proceedings of the 6th International Conference on Learning Analytics and Knowledge <\/i>(LAK\u201916), 25\u201329 April 2016, Edinburgh, UK (pp. 173\u2013182). New York: ACM. <\/span><\/span>\n\nOwston, R. (2013). Blended learning policy and implementation: Introduction to the special issue. The Internet and Higher Education, 18<\/i>, 1\u20133. <\/span><\/span>\n\nRitchey, T. (2011). General morphological analysis: A general method for non-quantified modelling. In T. Ritchey (Ed.), Wicked Problems: Social Messes<\/i>. http:\/\/www.swemorph.com\/pdf\/gma.pdf <\/span><\/span>\n\nSiemens, G., Dawson, S., & Lynch, G. (2013). Improving the quality and productivity of the higher education sector: Policy and strategy for systems-level deployment of learning analytics. Sydney, Australia: Australian Government Office for Teaching and Learning. <\/span><\/span>\n\nSiemens, G., & Long, P. (2011). Penetrating the fog: Analytics in learning and education. EDUCAUSE Review, 46<\/i>(5), 30.<\/span><\/span>\n\n
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                                  1<\/a> cohort<\/span><\/span><\/p>\n\n<\/div>\n","rendered":"

                                  Cassandra Colvin1<\/sup>, Shane Dawson1<\/sup>, Alexandra Wade2<\/sup>, Dragan Ga\u0161evi\u01073<\/sup><\/span><\/span><\/p>\n

                                  1<\/sup>\u00d6\u011fretim \u0130novasyon Birimi, G\u00fcney Avustralya \u00dcniversitesi, Avustralya <\/span><\/span><\/p>\n

                                  2<\/sup>Sa\u011fl\u0131k Bilimleri Y\u00fcksekokulu, G\u00fcney Avustralya \u00dcniversitesi, Avustralya <\/span><\/span><\/p>\n

                                  3<\/sup>E\u011fitim ve Bili\u015fim Okullar\u0131, Edinburgh \u00dcniversitesi, Birle\u015fik Krall\u0131k<\/span><\/span><\/p>\n

                                  DOI: 10.18608\/hla17.024<\/span><\/span><\/p>\n

                                  \u00d6Z<\/h2>\n

                                  Artan fon olanaklar\u0131, ara\u015ft\u0131rma ve kurumsal yat\u0131r\u0131mlara ra\u011fmen, y\u00fcksek\u00f6\u011frenimde \u00f6\u011frenme analiti\u011fi stratejileri ve faaliyetlerinin ger\u00e7ekle\u015fen geni\u015f \u00f6l\u00e7ekli uygulamalar\u0131 \u00e7ok azd\u0131r. Kurumsal \u00f6rneklerin bulunmay\u0131\u015f\u0131, sekt\u00f6r\u00fcn zaman i\u00e7indeki \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131n getirdi\u011fi g\u00fc\u00e7l\u00fck ve k\u0131s\u0131tlamalar hakk\u0131nda geni\u015f ve incelikli bir anlay\u0131\u015fa ula\u015fmas\u0131n\u0131 engellemektedir. Bu b\u00f6l\u00fcm, b\u00fcy\u00fck \u00f6l\u00e7ekli \u00f6\u011frenme analiti\u011fi projelerinin benimsenmesi ile ilgili \u00e7e\u015fitli modelleri incelemektedir. Bunu yaparken, mevcut \u00e7al\u0131\u015fman\u0131n s\u0131n\u0131rlar\u0131 vurgulanmakta ve \u00f6l\u00e7eklendirmede \u00f6\u011frenme analitiklerini benimsemeyi etkileyen karma\u015f\u0131k ve i\u00e7 i\u00e7e ge\u00e7mi\u015f boyutlar\u0131 belirlemek i\u00e7in daha deneysel bir yakla\u015f\u0131m \u00f6nermektedir.<\/span><\/span><\/p>\n

                                  Anahtar Kelimeler<\/span>: \u00d6\u011frenme analiti\u011fi benimsenmesi, \u00f6\u011frenme analiti\u011fi \u00f6z\u00fcmsenmesi, liderlik<\/span><\/span><\/p>\n

                                  \u00d6\u011frenme ve \u00f6\u011fretme prati\u011fi i\u00e7in verilerin ve analitiklerin \u00f6nemi, e\u011fitim politikas\u0131 ve ara\u015ft\u0131rma literat\u00fcr\u00fcnde g\u00fc\u00e7l\u00fc bir \u015fekilde tart\u0131\u015f\u0131lmaktad\u0131r (Daniel, 2015; Siemens, Dawson ve Lynch, 2013). \u00d6\u011frenme analitiklerinin g\u00fcc\u00fc d\u00e2hilindeki \u00f6\u011fretmeye, \u00f6\u011frenmeye, \u00f6\u011frenci deneyimine ve y\u00f6netim etkinliklerine ili\u015fkin i\u00e7g\u00f6r\u00fcler \u00f6l\u00e7ek, karma\u015f\u0131kl\u0131k ve etki bak\u0131m\u0131ndan hi\u00e7 olmad\u0131\u011f\u0131 kadar dile getirilmektedir (Baker ve Inventado, 2014). \u00d6\u011frenme analiti\u011fi yaln\u0131zca kurumlar i\u00e7inde ger\u00e7ekle\u015fen uygulama ve etkinliklerin etkin bir \u015fekilde anla\u015f\u0131lmas\u0131n\u0131 sa\u011flama kapasitesine sahip olmakla kalmaz, ayn\u0131 zamanda kestirimci modelleme, \u00f6\u011frenmenin ki\u015fiselle\u015ftirilmesi ve \u00f6neri sistemlerinde oldu\u011fu gibi etkinliklere ba\u015ftan sona arac\u0131l\u0131k etme ve onlar\u0131 bi\u00e7imlendirme yani gelecekteki hallerini s\u00fcre\u00e7 i\u00e7inde de\u011fi\u015ftirebilme potansiyeline de sahiptir (Conde ve Hern\u00e1ndez-Garc\u00eda, 2015).<\/span><\/p>\n

                                  Artan fon imk\u00e2nlar\u0131, ara\u015ft\u0131rma ve kurumsal yat\u0131r\u0131mlara ra\u011fmen, y\u00fcksek\u00f6\u011frenimde \u00f6\u011frenme analiti\u011fi stratejileri ve faaliyetlerinin geni\u015f \u00f6l\u00e7ekli uygulamalar\u0131nda yetersizlik devam etmektedir (Ferguson vd., 2015), dolay\u0131s\u0131yla sekt\u00f6r zaman i\u00e7indeki \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131n getirdi\u011fi faydalar ve k\u0131s\u0131tlamalar hakk\u0131nda geni\u015f ve incelikli bir anlay\u0131\u015fa ula\u015famamaktad\u0131r. Kurumsal \u00f6rneklerin eksikli\u011fine ili\u015fkin a\u00e7\u0131klamalar\u0131n bir k\u0131sm\u0131, bir disiplin olarak \u00f6\u011frenme analiti\u011finin g\u00f6rece yeni ortaya \u00e7\u0131k\u0131\u015f\u0131na ve \u00f6\u011frenme analiti\u011fi program ve uygulamalar\u0131n\u0131n tamamen geli\u015fmesi ve olgunla\u015fmas\u0131na ayr\u0131lan zaman\u0131n hissedilir bi\u00e7imde yetersizli\u011fine dayanabilir. Bununla birlikte, bu a\u00e7\u0131klama, \u00f6\u011frenme analiti\u011finin sistemik kavranmas\u0131yla ilgili sorunlar\u0131n karma\u015f\u0131kl\u0131\u011f\u0131n\u0131 yeterince ortaya koyamamaktad\u0131r (Arnold, Lynch vd., 2014; Ferguson vd., 2015; Macfadyen, Dawson, Pardo ve Ga\u0161evi\u0107, 2014). Her ne kadar \u00f6\u011frenme analiti\u011fi, y\u00fcksek\u00f6\u011frenim i\u00e7in nispeten yeni olsa da bu t\u00fcr etkinliklerin kurum \u00e7ap\u0131nda bir e\u011fitime getirebilece\u011fi kolayl\u0131klar\u0131 farketmek i\u00e7in zaman ve kaynak olarak yeterli yat\u0131r\u0131mlar\u0131n yap\u0131lmas\u0131n\u0131 \u00f6neriyoruz. Asl\u0131nda, \u00e7ok az say\u0131da kurum, \u00f6\u011fretme ve \u00f6\u011frenme kazan\u0131mlar\u0131 \u00fczerinde g\u00f6zle g\u00f6r\u00fcl\u00fcr bir etkiye sahip b\u00fcy\u00fck \u00f6l\u00e7ekli \u00f6\u011frenme analiti\u011fi programlar\u0131n\u0131 uygulayabilmi\u015ftir (Ferguson vd., 2015). Bununla birlikte, bu \u00f6rnekler, \u00e7ok say\u0131da kurum i\u00e7in, \u00f6\u011frenme analiti\u011finin \u00f6rg\u00fctsel olarak benimsenmesinin ya kavramsal, anla\u015f\u0131lamam\u0131\u015f bir \u00f6zlem olarak kald\u0131\u011f\u0131 ya da i\u015flevselle\u015ftirildi\u011finde, kapsam ve etki bak\u0131m\u0131ndan genellikle dar ve s\u0131n\u0131rl\u0131 oldu\u011fu bir sekt\u00f6rde istisna olmaya devam etmektedir (Ferguson vd., 2015). Bu literat\u00fcr, \u00f6\u011frenme analiti\u011finin benimsenmesine arac\u0131l\u0131k etmek \u00fczere boyutlar ve s\u00fcre\u00e7lerle ilgili i\u00e7g\u00f6r\u00fcleri yakalamak ve ortaya \u00e7\u0131karmak amac\u0131yla \u00e7oklu uygulama \u00e7at\u0131lar\u0131 (frameworks) sunmaktad\u0131r. Kavramsal anlamaya yard\u0131mc\u0131 olmas\u0131n\u0131n yan\u0131 s\u0131ra, bu literat\u00fcr ayn\u0131 zamanda kurumlar\u0131 uygulama a\u015famalar\u0131 ve de\u011ferlendirmeler boyunca y\u00f6nlendiren sezgisel bir de\u011fere sahiptir. \u00d6\u011frenme analiti\u011finin etkin d\u00fczenlenmesini\/kullan\u0131m\u0131n\u0131 ara\u015ft\u0131ran s\u0131n\u0131rl\u0131 deneysel ara\u015ft\u0131rma g\u00f6z \u00f6n\u00fcne al\u0131nd\u0131\u011f\u0131nda (Ferguson vd., 2015), bir\u00e7ok y\u00f6neticinin \u00f6\u011frenme analiti\u011fi giri\u015fimlerini planlarken ve uygularken ilham ve i\u00e7g\u00f6r\u00fc almak i\u00e7in kavramsal literat\u00fcr\u00fcn bu k\u00fc\u00e7\u00fck taraf\u0131na y\u00f6nelmesi muhtemeldir. Bu b\u00f6l\u00fcm, alan yaz\u0131n\u0131n bu yan\u0131n\u0131 sadece \u00f6\u011frenme analitiklerinin etkili kurumsal uygulamalar\u0131 i\u00e7in \u00f6nemli olan boyutlar ve s\u00fcre\u00e7ler olarak neleri tan\u0131mlad\u0131\u011f\u0131n\u0131 \u00f6ng\u00f6rmekle kalmay\u0131p ayn\u0131 zamanda kurumsal y\u00f6neticiler i\u00e7in modellerin k\u0131lavuz olarak de\u011ferini \u00f6l\u00e7meyi de ele almaktad\u0131r. Ard\u0131ndan, bu alan yaz\u0131n incelemesinin bulgular\u0131 ile Avustralya \u00fcniversitelerinden olu\u015fan b\u00fcy\u00fck bir toplulu\u011fun1<\/a><\/sup> mevcut \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131 inceleyen g\u00fcncel bir \u00e7al\u0131\u015fman\u0131n bulgular\u0131n\u0131 kar\u015f\u0131la\u015ft\u0131rarak bu uygulamalar\u0131 bi\u00e7imlendiren s\u00fcre\u00e7ler ve etkenler \u00fczerine deneysel bir anlay\u0131\u015f sunduk (Colvin vd., 2015).<\/span><\/p>\n

                                  \u00d6\u011eRENME ANAL\u0130T\u0130\u011e\u0130 DA\u011eITIMINDA G\u00dcNCEL MODELLER\u0130N \u0130NCELENMES\u0130<\/h2>\n

                                  G\u00fcncelli\u011fini koruyan \u00f6\u011frenme analiti\u011fi uygulama modellerinin ve uygulama \u00e7at\u0131lar\u0131n\u0131n incelenmesi, \u00fc\u00e7 ana literat\u00fcr grubunu ortaya \u00e7\u0131karm\u0131\u015ft\u0131r: 1) \u00f6\u011frenme analiti\u011fi \u00e7\u0131kt\u0131lar\u0131n\u0131n (kazan\u0131mlar\u0131n\u0131n) \u00f6nc\u00fcllerine odaklananlar (\u00f6\u011frenme analiti\u011fi girdi modelleri); 2) \u00f6\u011frenme analiti\u011finin \u00e7\u0131kt\u0131lar\u0131na odaklananlar (\u00f6\u011frenme analiti\u011fi \u00e7\u0131kt\u0131 modelleri) ve 3) \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131 destekleyen g\u00f6revleri s\u0131ral\u0131 bir \u015fekilde haritalayan ve i\u015fleten s\u00fcre\u00e7 modelleri. Bu farkl\u0131 modellere genel bir bak\u0131\u015f ve bunlar\u0131n kurumsal \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131 \u015fekillendiren fakt\u00f6rleri anlamadaki kavramsal ve deneysel katk\u0131lar\u0131 a\u015fa\u011f\u0131daki gibidir.<\/span><\/p>\n

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                                          \u00d6\u011frenme Analiti\u011fi Girdi Modelleri<\/h4>\n<\/li>\n<\/ol>\n<\/li>\n<\/ol>\n<\/li>\n<\/ol>\n<\/li>\n<\/ol>\n

                                          Literat\u00fcr\u00fcn bu taraf\u0131ndaki uygulama \u00e7at\u0131lar\u0131, \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131 liderlik, y\u00f6neti\u015fim, teknoloji, kapasite ve k\u00fclt\u00fcr gibi boyutlar\u0131 i\u00e7eren \u00f6nceki ili\u015fkilerin bir sonucu olarak sunma e\u011filimindedir. Bu literat\u00fcrde dikkat \u00e7eken kurulu\u015f ABD merkezli EDUCAUSE Analiz ve Ara\u015ft\u0131rma Merkezi’dir (EAAM; bk. EAAM, 2015) Y\u00fcksek \u00d6\u011frenim i\u00e7in Analitik Olgunluk Endeksi (Bichsel, 2012). Kulland\u0131klar\u0131 model, anketler ve end\u00fcstri uzmanlar\u0131yla yap\u0131lan odak grup g\u00f6r\u00fc\u015fmeleri yoluyla ortaya \u00e7\u0131kar\u0131lan verilere dayanan bir model olarak, \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131 k\u00fclt\u00fcr, s\u00fcre\u00e7, veri \/ raporlama \/ ara\u00e7lar, yat\u0131r\u0131m, uzmanl\u0131k ve y\u00f6neti\u015fim \/ altyap\u0131 olmak \u00fczere alt\u0131 faaliyet boyutunda i\u015flevsel hale getirir. Her girdi boyutu, kurumlar\u0131n her bir seviyedeki ilerleme d\u00fczeylerini belirlemelerine yard\u0131mc\u0131 olmak i\u00e7in tasarlanm\u0131\u015f kesintisiz be\u015f olgunluk seviyesi boyunca yap\u0131land\u0131r\u0131l\u0131r. Ba\u015far\u0131l\u0131 bir \u00f6\u011frenme analiti\u011fi uygulamas\u0131 i\u00e7in her girdi boyutunun kritik oldu\u011fu varsay\u0131lmaktad\u0131r.<\/span><\/p>\n

                                          EAAM modeline benzemekle birlikte kurumlara analitik uygulamalar i\u00e7in \u201chaz\u0131rl\u0131k\u201d d\u00fczeylerini de\u011ferlendirmelerine yard\u0131mc\u0131 olmaya y\u00f6nelik bir ara\u00e7 olarak tasarlanan di\u011fer bir model ise \u00d6\u011frenme Analiti\u011fi Haz\u0131rl\u0131k Arac\u0131’d\u0131r (\u00d6AHA); (Arnold, Lonn ve Pistilli, 2014; Oster, Lonn, Pistilli ve Brown, 2016). Her ne kadar ba\u015flang\u0131\u00e7ta nas\u0131l belirlendi\u011fi a\u00e7\u0131k olmasa da bu arac\u0131n orijinal s\u00fcr\u00fcm\u00fc (Arnold, Lonn ve Pistilli, 2014) \u201c\u00f6\u011frenme analiti\u011fi ba\u015far\u0131s\u0131 i\u00e7in en uygun ortam\u0131\u201d (s.2) elde etmeye y\u00f6nelik be\u015f boyut tan\u0131mlam\u0131\u015ft\u0131r: 1) yetenek, 2) veri, 3) k\u00fclt\u00fcr ve s\u00fcre\u00e7, 4) “y\u00f6neti\u015fim ve altyap\u0131” ve genel 5) haz\u0131rl\u0131k alg\u0131lar\u0131. \u00d6AHA’y\u0131 rafine etmek i\u00e7in toplam 24 kurum 560 kat\u0131l\u0131mc\u0131dan elde edilen anket verilerine uygulanan daha g\u00fcncel bir fakt\u00f6r analizi kullan\u0131lm\u0131\u015ft\u0131r. Be\u015f boyut hafif\u00e7e de\u011fi\u015ftirilerek g\u00f6receli belirginlikleri\/farklar\u0131 ortaya \u00e7\u0131kar\u0131lm\u0131\u015ft\u0131r. Ancak bu belirginlik kat\u0131l\u0131mc\u0131n\u0131n alg\u0131s\u0131na g\u00f6re \u00f6l\u00e7\u00fclmesine kar\u015f\u0131n \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131n sonu\u00e7lar\u0131na kar\u015f\u0131 \u00f6l\u00e7\u00fclmemi\u015ftir.<\/span><\/p>\n

                                          \u00d6rg\u00fctsel Kapasite Analiti\u011fi Uygulama \u00c7er\u00e7evesi (Norris ve Baer, 2013), analitiklerin benimsenmesini bi\u00e7imlendirmede \u00f6nemli oldu\u011funu d\u00fc\u015f\u00fcnd\u00fckleri boyutlar konusunda \u00f6\u011frenme analiti\u011fi uzmanlar\u0131ndan toplanan bilgiler\/i\u00e7g\u00f6r\u00fcler \u00fczerine kuruludur. Yazarlar, Amerika Birle\u015fik Devletleri’ndeki 40 kurumun y\u00f6neticileriyle r\u00f6portaj yapm\u0131\u015f ve bu r\u00f6portajlar yoluyla toplanan veriler kritik kurumsal kapasite fakt\u00f6rleri olarak kabul edilen be\u015f boyutun olu\u015fturulmas\u0131na yol a\u00e7m\u0131\u015ft\u0131r. Bu boyutlar 1) teknoloji altyap\u0131s\u0131, 2) s\u00fcre\u00e7ler ve pratik, 3) k\u00fclt\u00fcr ve davran\u0131\u015flar, 4) beceri ve de\u011ferler ve 5) liderlikti. Ortaya koyduklar\u0131 \u201cAnalitik i\u00e7in \u00d6rg\u00fctsel Kapasite\u201d adl\u0131 \u00e7al\u0131\u015fmalar\u0131nda \u201cUygulama \u00c7at\u0131s\u0131\u201dn\u0131n boyutlar\u0131n birbirine ba\u011fl\u0131 ve \u00f6rt\u00fc\u015fen olarak sunulmas\u0131 ve dolay\u0131s\u0131yla birbirine ba\u011f\u0131ml\u0131 do\u011falar\u0131n\u0131n vurgulanmas\u0131 kayda de\u011ferdir (Norris ve Baer, 2013, s. 31). Uygulama \u00e7at\u0131s\u0131, her bir boyut i\u00e7in \u00fc\u00e7 olgunluk seviyesini i\u015flevsel hale getirirken, boyutlar\u0131n g\u00f6reli belirginliklerini incelememektedir.<\/span><\/p>\n

                                          Son olarak, Drachsler ve Greller\u2019\u0131n modeli (yazarlar taraf\u0131ndan ontoloji olarak belirtilir; Drachsler ve Greller, 2012; Greller ve Drachsler, 2012) ayr\u0131ca \u00f6\u011frenme analiti\u011fi uygulamalar\u0131na arac\u0131l\u0131k eden boyutlar\u0131n birbirine ba\u011f\u0131ml\u0131 ve \u00f6zyinelemeli do\u011fas\u0131n\u0131 da yakalar. Medya taramas\u0131, k\u0131demli uzmanlarla g\u00f6r\u00fc\u015fmeler ve bili\u015fsel haritalama \u00e7al\u0131\u015fmalar\u0131ndan elde edilen verilere genel morfolojik analiz (bk. Ritchey, 2011, Greller ve Drachsler, 2012) uygulanm\u0131\u015ft\u0131r. Bu model \u201c\u00f6\u011frenme analiti\u011finin uygun \u015fekilde kullan\u0131lmas\u0131n\u0131 sa\u011flamak\u201d i\u00e7in alt\u0131 temel faaliyet alan\u0131n\u0131 \u201ckritik\u201d olarak tan\u0131mlamaktad\u0131r (Drachsler ve Greller, 2012, s. 120): 1) yeterlilikler 2) k\u0131s\u0131tlamalar (gizlilik\/etik), 3) teknolojiler 4) e\u011fitim verileri, 5) hedefler ve 6) payda\u015flar. Drachsler ve Greller (2012) bu alt\u0131 boyutun her birini \u201ckritik\u201d olarak g\u00f6r\u00fcrken, belirginliklerinin benzer olmad\u0131\u011f\u0131n\u0131 g\u00f6zlemleyip, \u201cbaz\u0131 boyutlar\u0131n di\u011ferlerinden daha belirsiz oldu\u011funa\u201d dikkat \u00e7ekmektedirler (s. 44).<\/span><\/p>\n

                                          Bir\u00e7ok girdi modeli i\u00e7in ortak olan, \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131n kavramsalla\u015ft\u0131r\u0131lmas\u0131n\u0131n do\u011frusal olmamas\u0131, \u00e7oklu ve birbirine ba\u011fl\u0131 girdi boyutlar\u0131n\u0131n kar\u015f\u0131l\u0131kl\u0131 etkile\u015fimi olarak ortaya \u00e7\u0131kar\u0131lmas\u0131d\u0131r. Odak grup ve anket y\u00f6ntemleri arac\u0131l\u0131\u011f\u0131yla \u0131srarla belirtilen g\u00f6r\u00fc\u015flerle de s\u0131k\u00e7a bilgilendirilmekle birlikte (Drachsler ve Greller, 2012; Greller ve Drachsler, 2012; Norris ve Baer, 2013; Oster vd., 2016), bu modeller asl\u0131nda kavramsald\u0131r. Kurumsal temsilcilerin alg\u0131lad\u0131\u011f\u0131, etkili bir \u00f6\u011frenme analiti\u011fi uygulamas\u0131 olu\u015fturmak i\u00e7in g\u00f6z \u00f6n\u00fcnde bulundurulmas\u0131 gereken boyutlar\u0131 tan\u0131mlarlar ancak boyutlar\u0131 ger\u00e7ek \u00f6\u011frenme analiti\u011fi uygulamalar\u0131na kar\u015f\u0131 deneysel olarak sorgulamazlar. Benzer \u015fekilde, girdi modelleri \u00f6nc\u00fcl boyutlar aras\u0131nda ili\u015fki oldu\u011funu \u00f6ne s\u00fcrerken, bu ili\u015fkilerin do\u011fas\u0131 ve bunlar\u0131n \u00f6\u011frenme analiti\u011fi uygulama \u00e7\u0131kt\u0131lar\u0131 \u00fczerindeki etkileri de deneysel olarak ara\u015ft\u0131r\u0131lmam\u0131\u015ft\u0131r. Bu nedenle, modeller kendi kurumlar\u0131nda \u00f6\u011frenme analiti\u011fi yaz\u0131l\u0131mlar\u0131n\u0131 uygulama ile g\u00f6revli liderlere bu uygulamay\u0131 ger\u00e7ekle\u015ftirmek i\u00e7in gerekli \u00f6nc\u00fcl boyutlara y\u00f6nelik \u00f6ng\u00f6r\u00fcler sunarken, uygulamalar\u0131n ger\u00e7ekte nas\u0131l \u00e7al\u0131\u015ft\u0131\u011f\u0131 konusunda \u00e7ok az rehberlik sunmaktad\u0131r. Ayr\u0131ca, modellerdeki her bir boyutun g\u00f6receli belirginli\u011finin ara\u015ft\u0131r\u0131lmam\u0131\u015f olmas\u0131, kurumlar\u0131n eylemleri ve kaynaklar\u0131 en iyi nas\u0131l \u00f6nceliklendirebilece\u011fi konusundaki kavray\u0131\u015flar\u0131n\u0131 s\u0131n\u0131rland\u0131rmaktad\u0131r (bununla birlikte s\u0131n\u0131rl\u0131 say\u0131da model her boyutta olgunluk seviyeleri sa\u011flar; Arnold, Lonn ve Pistilli, 2014; Bichsel, 2012; Norris ve Baer, 2013).<\/span><\/p>\n

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                                                  \u00d6\u011frenme Analiti\u011fi \u00c7\u0131kt\u0131 Modelleri<\/h4>\n<\/li>\n<\/ol>\n<\/li>\n<\/ol>\n<\/li>\n<\/ol>\n<\/li>\n<\/ol>\n

                                                  \u00d6\u011frenme analiti\u011fi modelleri ve uygulama \u00e7at\u0131lar\u0131n\u0131n ikinci aya\u011f\u0131, \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131 zaman i\u00e7inde ortaya \u00e7\u0131kan ve farkl\u0131 haz\u0131rl\u0131k ve olgunluk seviyeleri i\u00e7eren do\u011frusal bir s\u00fcre\u00e7 olarak tan\u0131mlar ve temsil eder. Bu literat\u00fcrdeki erken bir model olmas\u0131na ra\u011fmen h\u00e2l\u00e2 sekt\u00f6rde bir \u00f6neme, paya sahip g\u00f6r\u00fcnen Davenport ve Harris\u2019in (2007) Analitik Uygulama \u00c7at\u0131s\u0131, analitikleri sorgulama ve raporlama uygulamalar\u0131ndan tahmin ve kestirimci modelleme gibi resm\u00ee analitik fonksiyonlara kadar olgunla\u015fan bir s\u00fcre\u00e7 olarak kavramsalla\u015ft\u0131r\u0131r. Siemens, Dawson ve Lynch’in (2013) Sofistike Model \u00d6\u011frenme Analiti\u011fi yetene\u011fi ve analitik sistemler artan olgunluk bir s\u00fcreklilik boyunca da\u011f\u0131t\u0131m b\u00fct\u00fcnle\u015ftirir. Be\u015f olgunluk a\u015famas\u0131 tan\u0131mlanm\u0131\u015f, bunlar\u0131n her biri ayr\u0131ca \u00f6rnek te\u015fkil edecek bi\u00e7imde i\u015flevselle\u015ftirilmi\u015ftir. \u00d6rne\u011fin, erken a\u015famadaki bir da\u011f\u0131t\u0131m sistemi \u00f6zellik olarak, temel raporlar\u0131 ve kay\u0131t g\u00fcnl\u00fc\u011f\u00fcn\u00fc i\u00e7erirken, olgun bir da\u011f\u0131t\u0131m ise kestirimci modelleri ve ki\u015fiselle\u015ftirilmi\u015f \u00f6\u011frenmeyi de i\u00e7ermektedir.<\/span><\/p>\n

                                                  \u00c7\u0131kt\u0131 modellerinin birincil yarar\u0131, kurumlara, faaliyetlerinin ve i\u015flemlerinin olgunlu\u011funu (veya kapasitesini) istenen kazan\u0131mlar\u0131n matrisine kar\u015f\u0131 objektif olarak de\u011ferlendirmeleri i\u00e7in bir ara\u00e7 sa\u011flamalar\u0131d\u0131r. Bununla birlikte, bir\u00e7ok \u00e7\u0131kt\u0131 modeli kapsam a\u00e7\u0131s\u0131ndan s\u0131n\u0131rl\u0131l\u0131klara sahiptir ve genel olarak tek veya \u00e7ift boyutlu kavramsal merceklere (kullan\u0131lan analitik tekniklerin geli\u015fkinli\u011fi gibi) dayan\u0131r. \u00c7\u0131kt\u0131 modelleri, \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131n kazan\u0131mlar\u0131na y\u00f6nelik bir vizyonunu savunurken, asl\u0131nda savunduklar\u0131 bu kazan\u0131mlar\u0131 olu\u015fturmak i\u00e7in gerekli t\u00fcm boyutlar\u0131 ya da mekanizmalar\u0131 tan\u0131mlamakta ya da ele\u015ftirel olarak incelemekte ba\u015far\u0131s\u0131z olurlar. Son olarak, bir\u00e7ok \u00e7\u0131kt\u0131 modelindeki risk, bu modellerin ilerlemeyi genel olarak sadece teorik, ba\u011flamdan kopar\u0131lm\u0131\u015f, muhtemelen varsay\u0131lan bir evrenselli\u011fe dayand\u0131r\u0131lm\u0131\u015f ve belirli bir kurumun i\u015f g\u00f6rme ba\u011flam\u0131nda neyin m\u00fcmk\u00fcn veya arzu edilebilir oldu\u011funu yakalamayan bir tarzda temellendirmeleri, hatta; \u201c\u00fctopik\u201d bir \u00f6\u011frenme analiti\u011fi vizyonuyla do\u011frusal olarak ve a\u015famal\u0131 bir s\u00fcre\u00e7 bi\u00e7iminde kavramsalla\u015ft\u0131rmalar\u0131d\u0131r.<\/span><\/p>\n

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                                                          S\u00fcre\u00e7 Modelleri<\/h4>\n<\/li>\n<\/ol>\n<\/li>\n<\/ol>\n<\/li>\n<\/ol>\n<\/li>\n<\/ol>\n

                                                          Literat\u00fcr\u00fcn (Foreman, 2013a, 2013b; Norris ve Baer, 2013) bu \u00fc\u00e7\u00fcnc\u00fc aya\u011f\u0131, s\u0131ral\u0131 olarak temel s\u00fcre\u00e7leri veya \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131 destekleyen \u201cad\u0131mlar\u0131\u201d haritalar. Kazan\u0131mlar\u0131n neye benzemesi gerekti\u011fi (\u00e7\u0131kt\u0131 modeli) veya neyi i\u00e7ermesi gerekti\u011fi (girdiler modeli) yerine bir \u00f6\u011frenme analiti\u011fi program\u0131n\u0131n nas\u0131l uygulanaca\u011f\u0131na odaklan\u0131r. S\u00fcre\u00e7 modelleri hem do\u011frusal (Foreman, 2013a, 2013b) hem de dolayl\u0131d\u0131r (Norris ve Baer’in Analitik Eylem Plan\u0131, 2013) ve genel olarak daha geni\u015f bir \u00f6\u011frenme analiti\u011fi uygulamas\u0131 [\u00f6rne\u011fin, bir \u00f6\u011frenme y\u00f6netim sisteminin uygulanmas\u0131 (\u00d6YS; Foreman, 2013a, 2013b) veya strateji geli\u015ftirme (bk. Norris ve Baer\u2019\u0131n Analitik Eylem Plan\u0131, 2013)] i\u00e7indeki belirli \u00f6gelere odaklan\u0131r. Bununla birlikte, ortaya \u00e7\u0131kan literat\u00fcr (Ferguson vd., 2015), bu kavramsalla\u015ft\u0131rman\u0131n sa\u011flad\u0131\u011f\u0131 i\u00e7g\u00f6r\u00fcn\u00fcn \u201cgeni\u015f \u00f6l\u00e7ekte\u201d \u00f6\u011frenme analiti\u011fi uygulamak isteyen kurumlar i\u00e7in kritik \u00f6neme sahip oldu\u011funu \u00f6ne s\u00fcrerek \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131n geni\u015fli\u011fini ve karma\u015f\u0131kl\u0131\u011f\u0131n\u0131 daha iyi yans\u0131tan s\u00fcre\u00e7 modelleri sunar. Ferguson ve meslekta\u015flar\u0131n\u0131n (2015) \u00f6\u011frenme analiti\u011fi uygulamas\u0131 i\u00e7in RAPID Kazan\u0131m Haritalama Yakla\u015f\u0131m\u0131’n\u0131n (KHY) benimsenmesini savunmalar\u0131 dikkat \u00e7ekicidir. Bu model girdi boyutlar\u0131n\u0131 ba\u015flang\u0131\u00e7taki hedeflerin olu\u015fturulmas\u0131ndan son de\u011ferlendirmeye kadar yedi \u00f6nemli ad\u0131mdan olu\u015fan i\u015flemsel bir dizilimde sunar. Bununla birlikte, Ferguson\u2019un modeli \u00f6z\u00fcnde kavramsal olarak \u00fcretilmi\u015ftir. Model, deneysel ge\u00e7erlili\u011fi hakk\u0131nda \u00e7ok az kan\u0131t olmas\u0131na ra\u011fmen, yazarlar taraf\u0131ndan modelin potansiyel k\u0131lavuzlu\u011funu g\u00f6stermek ve kurumlara \u201cg\u00fcven\u201d vermek i\u00e7in savunulmu\u015f, Avustralya ve Birle\u015fik Krall\u0131k’taki \u00fcniversitelerde \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131 tan\u0131mlamak i\u00e7in bir mercek olarak kullan\u0131lm\u0131\u015ft\u0131r (Ferguson vd., 2015).<\/span><\/p>\n

                                                          MODELLER B\u0130ZE NE ANLATIR?<\/h2>\n

                                                          Bu modelleri g\u00f6zden ge\u00e7irmek, \u00f6\u011frenme analiti\u011fi da\u011f\u0131t\u0131mlar\u0131na arac\u0131l\u0131k eden boyutlar ve s\u00fcre\u00e7ler hakk\u0131nda fikir verirken, modellerin kavramsal ve \u00e7al\u0131\u015fma s\u0131n\u0131rlamalar\u0131n\u0131 da ortaya koymaktad\u0131r. Bu s\u0131n\u0131rlamalar modellerin karma\u015f\u0131k, \u00e7ok boyutlu olgular\u0131n incelenmesi i\u00e7in s\u0131n\u0131rl\u0131 veya tek boyutlu mercekleri benimsemelerini; \u00f6nc\u00fcl boyutlar\u0131 ve sonu\u00e7lar\u0131 tek bir modelde b\u00fct\u00fcnle\u015ftirememelerini ve tan\u0131mlanm\u0131\u015f arac\u0131l\u0131k boyutlar\u0131n\u0131n her birinin nispi belirginli\u011fi veya kritikli\u011fi konusundaki i\u00e7g\u00f6r\u00fclerinin s\u0131n\u0131rl\u0131l\u0131\u011f\u0131n\u0131 kapsar. Basit\u00e7e s\u00f6ylemek gerekirse, modeller i\u00e7g\u00f6r\u00fc kazan\u0131rken, \u00d6A uygulamalar\u0131n\u0131 \u015fekillendiren fakt\u00f6rlerin geni\u015fli\u011fini tam olarak yakalamamaktalar, bu nedenle y\u00f6neticilere \u00f6\u011frenme analiti\u011fi uygulamalar\u0131 konusunda rehberlik etmek i\u00e7in ihtiya\u00e7 duyulan ince, yerle\u015fik, detayl\u0131 i\u00e7g\u00f6r\u00fcler sunma yetenekleri k\u0131s\u0131tlanmaktad\u0131r.<\/span><\/p>\n

                                                          Bununla birlikte, \u00e7o\u011fu modelde belirgin olduklar\u0131 izlenimiyle birlikte bir\u00e7ok arac\u0131 boyutun veya elemanlar\u0131n\u0131n ortak oldu\u011fu g\u00f6r\u00fclm\u00fc\u015ft\u00fcr. Bunlar teknolojik haz\u0131rl\u0131klar\u0131, liderlik, \u00f6rg\u00fct k\u00fclt\u00fcr\u00fc, insan kaynaklar\u0131 ve kurumsal kapasiteyi ve stratejiyi kapsamaktad\u0131r. Tart\u0131\u015fmalar bu boyutlar\u0131n modellerde nas\u0131l i\u015fletildi\u011fi \u00e7er\u00e7evesinde devam etmektedir.<\/span><\/p>\n

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                                                                  Teknolojik Haz\u0131r Bulunu\u015fluk<\/h4>\n<\/li>\n<\/ol>\n<\/li>\n<\/ol>\n<\/li>\n<\/ol>\n<\/li>\n<\/ol>\n

                                                                  \u00d6\u011frenme analiti\u011fi temel olarak, elektronik verilere eri\u015fim ve i\u00e7g\u00f6r\u00fc sunmak i\u00e7in teknoloji sa\u011flanmas\u0131na dayand\u0131\u011f\u0131ndan, \u00d6A uygulama literat\u00fcr\u00fcnde teknolojinin \u201ctemel unsur\u201d olarak sunulmas\u0131 \u015fa\u015f\u0131rt\u0131c\u0131 de\u011fildir (Arnold, Lynch vd., 2014, s. 258; ayr\u0131ca bk. Greller ve Drachsler, 2012; Siemens ve Long, 2011). Bununla birlikte, teknolojik haz\u0131rl\u0131klar olarak tan\u0131mlanan boyutlar\u0131n i\u015flemselle\u015ftirilmesi modellere g\u00f6re de\u011fi\u015fmektedir. \u00d6rne\u011fin, baz\u0131 modeller veri toplayabilen, depolayabilen ve d\u00f6n\u00fc\u015ft\u00fcrebilen sa\u011flam bir teknoloji altyap\u0131s\u0131na duyulan ihtiyac\u0131 vurgulamakta iken (Arnold, Lynch vd., 2014, s. 258), baz\u0131lar\u0131 ise b\u00fct\u00fcnle\u015fik sistemlere, (Dawson, Heathcote ve Poole, 2010; Siemens ve Long, 2011), uygun analiz ara\u00e7lar\u0131na (Norris ve Baer, 2013), g\u00fcvenlik ve gizlilik kontrol ve s\u00fcre\u00e7lerine (\u00f6r. Bichsel’deki Y\u00fcksek \u00d6\u011fretim Modeli i\u00e7in EAAM Analitik Olgunluk Endeksi, 2012) olan ihtiyac\u0131 g\u00fc\u00e7lendirir. Deneysel olarak, teknolojinin \u00f6\u011frenme analiti\u011fi uygulamalar\u0131nda k\u0131s\u0131tlay\u0131c\u0131 bir unsur olarak potansiyel engelleyici rol\u00fc, Dawson vd., taraf\u0131ndan yap\u0131lan \u00e7al\u0131\u015fmalarda vurgulanm\u0131\u015ft\u0131r (Dawson vd., 2010; Macfadyen ve Dawson, 2012).<\/span><\/p>\n

                                                                  Liderlik<\/h3>\n

                                                                  Geni\u015f \u00f6l\u00e7ekli \u00f6\u011frenme analiti\u011finin s\u00fcrd\u00fcr\u00fclebilir uygulamalar\u0131 i\u00e7in liderli\u011fin \u00f6nemi kavramsal (Arnold, Lonn ve Pistilli, 2014; Arnold, Lynch vd., 2014; Laferriere, Hamel ve Searson, 2013; Norris ve Baer, 2013; Siemens vd., 2013) ve deneysel (Graham, Woodfield ve Harrison, 2013; Norris ve Baer, 2013) olarak iyi bilinmektedir. Bu literat\u00fcr, anlama ve b\u00fct\u00fcnle\u015fmeyi kolayla\u015ft\u0131rmak i\u00e7in \u00f6\u011frenme analiti\u011finin \u201cderin bilimsel anlay\u0131\u015f\u0131\u201dnda \u201cadanm\u0131\u015f\u201d ve \u201cbilgilendirilmi\u015f\u201d liderlik temelinin \u00f6nemini savunmaktad\u0131r (Arnold, Lynch vd., 2014, s. 260). \u00d6zellikle \u00f6l\u00e7ekli ve karma\u015f\u0131k projelerde kararl\u0131 \u00fcst d\u00fczey liderli\u011fe a\u00e7\u0131k bir bi\u00e7imde ihtiya\u00e7 olmas\u0131na ra\u011fmen (Norris ve Baer, 2013), b\u00f6yle bir liderli\u011fin nas\u0131l kavramsalla\u015ft\u0131r\u0131ld\u0131\u011f\u0131 konusunda yorum farkl\u0131l\u0131klar\u0131 vard\u0131r ve fikir birli\u011fi olu\u015fmam\u0131\u015ft\u0131r. \u00d6rne\u011fin, Laferriere vd. (2013) tek bak\u0131\u015fl\u0131 s\u0131n\u0131rl\u0131 boyutsall\u0131k mercekleri arac\u0131l\u0131\u011f\u0131yla liderli\u011fi i\u015flevselle\u015ftirilmi\u015ftir. Aksine, Arnold, Lynch vd. (2014) liderli\u011fi \u00e7ok katmanl\u0131, \u00e7ok boyutlu bir fenomen olarak kabul etmektedir. Liderlik ayn\u0131 zamanda literat\u00fcrde liderlik tarz\u0131 (Owston, 2013) veya liderlik davran\u0131\u015f\u0131 ve etkisi (Laferriere vd., 2013) olarak i\u015flevselle\u015ftirilirken, literat\u00fcr\u00fcn di\u011fer taraf\u0131 liderli\u011fin yap\u0131s\u0131na (Accard, 2015; Carbonell, Dailey \u2013 Hebert ve Gijselaers, 2013) ve (bk. Kotter ve Schlesinger, 2008, Arnold, Lynch vd., 2014) g\u00fcc\u00fcne at\u0131fta bulunur. Analitiklerin uygulanmas\u0131na ve anla\u015f\u0131lmas\u0131na yard\u0131mc\u0131 olmak i\u00e7in ara\u015ft\u0131rma destekli karma\u015f\u0131kl\u0131k (Hazy ve Uhl \u2013 Bien, 2014) veya da\u011f\u0131t\u0131lm\u0131\u015f liderlik modelleri (Bolden, 2011) alanda ivme kazanmaktad\u0131r.<\/span><\/p>\n

                                                                  Organizasyon K\u00fclt\u00fcr\u00fc<\/h3>\n

                                                                  Bir kurumun \u201cnormlar\u0131, inan\u00e7lar\u0131 ve de\u011ferleri\u201d olarak tan\u0131mlanan \u00f6rg\u00fct k\u00fclt\u00fcr\u00fc (Carbonell vd., 2013, s. 30), ayn\u0131 zamanda analitik uygulamalar\u0131n\u0131n \u00f6\u011frenilmesinde de kilit bir arac\u0131 olarak tan\u0131mlanm\u0131\u015ft\u0131r (Arnold, Lonn ve Pistilli, 2014; Carbonell vd., 2013; Greller ve Drachsler, 2012; Macfadyen ve Dawson, 2012). Personeldeki \u201cverilerle ilgili fark\u0131ndal\u0131k ve kabulleni\u015f\u201d (Arnold, Lonn ve Pistilli, 2014, s. 164), bir kurumun \u201ctarihsel pedagojik [ve] sosyo-k\u00fclt\u00fcrel varsay\u0131mlar\u0131n\u0131n\u201d potansiyel engelleyici etkisinin tan\u0131nmas\u0131, y\u00fcz y\u00fcze e\u011fitim uygulamalar\u0131 (Arnold, Lynch vd., 2014, s. 259), \u00f6rg\u00fctsel \u201crutinler\u201d (Carbonell vd., 2013, s. 29) ve hatta \u00f6rg\u00fctsel, pedagojik ve e\u011fitsel (BT ile ilgili) de\u011fi\u015fikliklere y\u00f6nelik personel kayg\u0131s\u0131 (Houchin ve MacLean, 2005) gibi konular bu literat\u00fcrde \u00f6ne \u00e7\u0131kmaktad\u0131r. Macfadyen ve Dawson\u2019\u0131n (2012) Kanada’daki b\u00fcy\u00fck bir \u00fcniversitesinde ba\u015far\u0131s\u0131z bir uygulamaya y\u00f6nelik ara\u015ft\u0131rmalar\u0131nda yeterince haz\u0131rlanmam\u0131\u015f ve yeni fikirlere a\u00e7\u0131k olmayan bir \u00f6rg\u00fctsel k\u00fclt\u00fcr\u00fcn etkisine dair deneysel i\u00e7g\u00f6r\u00fc sunulmu\u015ftur. Ara\u015ft\u0131rmac\u0131lar, kurumun \u00f6\u011frenme analiti\u011finin potansiyeli ile ilgili olarak, istekli ve yeni fikirlere bir \u015fekilde takdir, kavray\u0131\u015f geli\u015ftirmedeki ba\u015far\u0131s\u0131zl\u0131\u011f\u0131n\u0131n, kurumun tutarl\u0131 ve ba\u015far\u0131l\u0131 bir \u00f6\u011frenme analiti\u011fi stratejisi olu\u015fturamamas\u0131n\u0131n kilit bir nedeni oldu\u011funu g\u00f6zlemlemi\u015ftir.<\/span><\/p>\n

                                                                  Personel ve Kurumsal Kapasite<\/h3>\n

                                                                  \u201c\u0130deal\u201d (Greller ve Drachsler, 2012, s. 51) \u00f6\u011frenme analiti\u011fi kazan\u0131mlar\u0131, personelin analitik zek\u00e2y\u0131 etkili bir \u015fekilde analiz etme, yorumlama ve anlaml\u0131 \u015fekilde kar\u015f\u0131lama yetene\u011fine ba\u011fl\u0131d\u0131r (Bichsel, 2012; Norris ve Baer, 2013). Bununla birlikte, payda\u015flar\u0131n \u00f6\u011frenme analiti\u011fi i\u00e7in talep edilen gerekli analitik veya yorumlay\u0131c\u0131 veri becerilerine sahip oldu\u011fu varsay\u0131lamaz. Norris ve Baer (2013) \u201cbir\u00e7ok kurumsal liderin, i\u015fletmelerinin veri, bilgi ve analitik konusundaki kapasitesine oldu\u011fundan daha fazla de\u011fer bi\u00e7ti\u011fini\u201d g\u00f6zlemlemektedir (s. 40). Drachsler ve Greller\u2019in (2012) \u00f6\u011frenme analiti\u011fi uygulamalar\u0131nda gerekli olan boyutlara y\u00f6nelik ara\u015ft\u0131rmas\u0131nda, boyutlar sert ve yumu\u015fak boyutlar olarak ayr\u0131l\u0131r: yumu\u015fak boyutlar, \u00f6zellikle \u201cyeterlilikler ve kabullenme\u201d gibi \u00f6\u011frenme analiti\u011finin etkinli\u011fini \u015fekillendiren \u201cinsan fakt\u00f6rlerini\u201d(s. 43); \u201csert\u201d boyutlar, ise teknoloji, veri ve algoritmalar d\u00e2hil, insana \u00f6zg\u00fc olmayan, daha az \u00f6znel unsurlar\u0131 ifade eder. Sert ve yumu\u015fak boyutlar\u0131 birbirinden ay\u0131rmak, kurumlar\u0131n \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131 teknik ve altyap\u0131 sorunlar\u0131n\u0131n \u00f6tesinde, sosyo-k\u00fclt\u00fcrel kayg\u0131lar\u0131 da i\u00e7erecek \u015fekilde g\u00f6rmelerine duyulan ihtiyac\u0131 vurgulamaktad\u0131r. \u00d6\u011frenme analiti\u011finin ba\u015far\u0131l\u0131 bir \u015fekilde benimsenmesi, bu iki alanda kapasite geli\u015ftirmeyi gerektirir.<\/span><\/p>\n

                                                                  \u00d6\u011frenme Analiti\u011fine Haz\u0131rl\u0131k Arac\u0131 (\u00d6AHA; Arnold, Lonn ve Pistilli, 2014) kapasitenin farkl\u0131 bir \u015fekilde kavramsalla\u015ft\u0131r\u0131lmas\u0131n\u0131 ortaya koyuyor: kurumsal haz\u0131rl\u0131k ba\u015fka bir deyi\u015fle bir kurumun \u00f6\u011frenme analiti\u011fi giri\u015fimini uygulamak i\u00e7in ne kadar “haz\u0131r” oldu\u011funun \u00f6l\u00e7\u00fcs\u00fc. Haz\u0131rl\u0131\u011f\u0131 be\u015f boyutta i\u015flevselle\u015ftirirler: 1) yetenek, 2) veri, 3) k\u00fclt\u00fcr ve s\u00fcre\u00e7, 4) y\u00f6neti\u015fim ve altyap\u0131 ve 5) genel haz\u0131r olma alg\u0131s\u0131. Kavramsalla\u015ft\u0131rmalar\u0131, kapasitenin \u00e7ok katmanl\u0131 do\u011fas\u0131n\u0131 vurgulamakta, kapasitenin makro (yani geni\u015f, kurumun tamam\u0131) ve mikro (bireysel payda\u015flar\u0131n seviyesi) seviyelerde \u00e7al\u0131\u015ft\u0131\u011f\u0131n\u0131 belirtmektedir. Son olarak, teknik, kritik ve yorumlay\u0131c\u0131 kapasiteye odaklanman\u0131n aksine, Siemens, Dawson ve Lynch (2013), personelin pedagoji ve analitik aras\u0131nda etkili bir \u201cba\u011f kurabilme\u201d yetene\u011finin de kapasitenin kapsam\u0131nda oldu\u011funu \u00f6ne s\u00fcrerek bize \u00f6\u011frenme analiti\u011fi ile \u00f6\u011fretme ve \u00f6\u011frenme prati\u011fi aras\u0131ndaki ili\u015fkiyi hat\u0131rlat\u0131r.<\/span><\/p>\n

                                                                  Strateji<\/h3>\n

                                                                  Kavramsal literat\u00fcr, politika ve prosed\u00fcrlerin geli\u015ftirilmesi yoluyla a\u00e7\u0131k bir vizyon ve \u00f6\u011frenme analiti\u011fi amac\u0131n\u0131n geli\u015ftirilmesini savunur. \u00d6rne\u011fin, Arnold, Lonn ve Pistilli’nin (2014) kavramsal olarak geli\u015ftirilen \u00d6\u011frenme Analiti\u011fi Haz\u0131rl\u0131k Arac\u0131 (\u00d6AHA), politikalar\u0131 y\u00f6neti\u015fim ve altyap\u0131 etiketli daha geni\u015f bir arac\u0131 boyutlar kategorisine yerle\u015ftirmektedir. Ayr\u0131ca, Norris and Baer’in \u201cAnalitik \u0130\u00e7in Kurumsal Kapasite\u201d modeli (2013), \u201cS\u00fcre\u00e7ler ve Uygulamalar\u201d\u0131 \u00d6A i\u00e7in \u00f6rg\u00fctsel kapasitenin be\u015f temel arac\u0131 boyutundan biri olarak tan\u0131mlar ve onu analiti\u011fi, eylemleri ve m\u00fcdahaleleri g\u00fc\u00e7lendirmek [..] \u00fczere \u201crutinle\u015fmi\u015f s\u00fcre\u00e7ler ve i\u015f ak\u0131\u015flar\u0131 olarak i\u015fler hale getirilir\u201d (s. 31). Bununla birlikte, aksine, deneysel \u00e7al\u0131\u015fmalar strateji belirlemenin \u00f6nemini vurgular ve uyumla\u015ft\u0131r\u0131lm\u0131\u015f politika ve hedeflere olan ihtiyac\u0131 (Macfadyen ve Dawson, 2012; Owston, 2013) vurgular ki; ba\u015far\u0131s\u0131z olmu\u015f bir \u00f6\u011frenme analiti\u011fi program\u0131 analizlerinde Macfadyen ve Dawson (2012), \u00f6\u011frenme analiti\u011fi uygulamalar\u0131nda \u00f6rg\u00fctsel bir strateji ve vizyonun olu\u015fturulmas\u0131n\u0131n \u201ckritik\u201d (s. 150) oldu\u011funu belirtmektedirler.<\/span><\/p>\n

                                                                  K\u0131saca<\/h3>\n

                                                                  Bu k\u0131sa literat\u00fcr taramas\u0131, \u00f6\u011frenme analiti\u011fi modellerinin, y\u00f6neticilere \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131 \u015fekillendiren s\u00fcre\u00e7ler ve boyutlar hakk\u0131nda de\u011ferli bilgiler sa\u011flayabilece\u011fini ortaya koymu\u015ftur. \u00d6\u011frenme analiti\u011fi uygulama kazan\u0131mlar\u0131 \u00fczerinde etkisi olan \u00f6zellikle be\u015f boyut, bir\u00e7ok uygulama \u00e7at\u0131s\u0131nda s\u0131k\u00e7a vurgulanm\u0131\u015ft\u0131r: teknolojik haz\u0131rl\u0131k, liderlik, kurum k\u00fclt\u00fcr\u00fc, insan kayna\u011f\u0131 ve \u00f6\u011frenme analiti\u011fi i\u00e7in kurumsal kapasite ve \u00f6\u011frenme analiti\u011fi stratejisi. Bununla birlikte, daha \u00f6nce belirtti\u011fimiz gibi, bu boyutlar\u0131n i\u015flevselle\u015fmesi literat\u00fcrde \u00e7e\u015fitlilik g\u00f6stermi\u015ftir. Ayr\u0131ca, modeller boyutlar\u0131n g\u00f6receli belirginli\u011fi veya kritikli\u011fi hakk\u0131nda \u00e7ok az fikir vermi\u015ftir. Literat\u00fcrde boyutlarla ilgili belirtilen farkl\u0131 kavramsalla\u015ft\u0131rmalar\u0131n ve i\u015flevselle\u015ftirmelerinin, kurumlar\u0131n kendileri i\u00e7in mevcut olan bir\u00e7ok \u00f6\u011frenme analiti\u011fi uygulama \u00e7at\u0131lar\u0131yla nas\u0131l etkile\u015fimde bulunacaklar\u0131 ve onlar\u0131 nas\u0131l yorumlayacaklar\u0131na dair arac\u0131l\u0131k etme potansiyeli oldu\u011funu \u00f6ne s\u00fcr\u00fcyoruz.<\/span><\/p>\n

                                                                  Ayr\u0131ca ve \u00f6nemli \u00f6l\u00e7\u00fcde, bu incelmede sunulan literat\u00fcr a\u011f\u0131rl\u0131kl\u0131 olarak kavramsald\u0131r. \u00d6\u011frenme analiti\u011fi uygulamalar\u0131na y\u00f6nelik deneysel ara\u015ft\u0131rma eksikli\u011finin, onlara arac\u0131l\u0131k eden s\u00fcre\u00e7ler ve boyutlar konusundaki anlay\u0131\u015f\u0131m\u0131z\u0131 engelledi\u011fini savunuyoruz. Kavramsal literat\u00fcr, i\u00e7g\u00f6r\u00fc kazanmas\u0131na ra\u011fmen, kendi karma\u015f\u0131kl\u0131\u011f\u0131n\u0131 ve n\u00fcans\u0131n\u0131 tam olarak yakalayamayacak ideal bir \u00f6\u011frenme analiti\u011fi modeli sunma riski ta\u015f\u0131yor. Deneysel tekniklerin kullan\u0131ld\u0131\u011f\u0131 yerlerde (\u00f6r. anketler ve odak gruplar\u0131 yoluyla veri toplama gibi), yap\u0131sal ge\u00e7erlili\u011fi \u00e7evreleyen \u00e7ok az ayr\u0131nt\u0131 vard\u0131r. Buna g\u00f6re, modellerdeki farkl\u0131 boyutlar aras\u0131ndaki ili\u015fkilerin b\u00fcy\u00fck \u00f6l\u00e7\u00fcde denenmemi\u015f oldu\u011fu g\u00f6r\u00fclmektedir. Bu b\u00f6l\u00fcmde daha \u00f6nce g\u00f6r\u00fcld\u00fc\u011f\u00fc gibi, y\u00fcksek\u00f6\u011fretim kurumlar\u0131ndaki \u00f6\u011frenme analiti\u011fi programlar\u0131n\u0131n nispi olgunla\u015fmam\u0131\u015fl\u0131\u011f\u0131 k\u0131smen \u00f6\u011frenme analiti\u011fini \u00e7evreleyen bu deneysel yetersizli\u011fe katk\u0131da bulunur. Bununla birlikte, y\u00fcksek\u00f6\u011fretim kurumlar\u0131nda bulunan uygulamalar\u0131n her ne kadar yeni geli\u015fmekte olsalar da \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131n \u015fu anda ba\u011flamda nas\u0131l i\u015fletildi\u011fini ve y\u00f6nlendirildi\u011fini deneysel olarak derinlemesine incelemek i\u00e7in bir f\u0131rsat sundu\u011funu savunuyoruz.<\/span><\/p>\n

                                                                  G\u00d6ZLEME DAYALI OLANI SUNMAK<\/h2>\n

                                                                  Avustralya’da yap\u0131lan son \u00e7al\u0131\u015fmalar, bu ara\u015ft\u0131rma eksikli\u011fini gidermeye \u00e7al\u0131\u015fm\u0131\u015ft\u0131r. Colvin vd. (2015), Avustralya y\u00fcksek\u00f6\u011frenim sekt\u00f6r\u00fcnde \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131 ara\u015ft\u0131ran geni\u015f bir ulusal \u00e7al\u0131\u015fma ger\u00e7ekle\u015ftirmi\u015ftir. Veriler, 32 \u00fcniversitede \u00f6\u011frenme analitiklerini uygulama sorumlulu\u011funu \u00fcstlenen \u00fcst d\u00fczey liderlerle yap\u0131lan nitel g\u00f6r\u00fc\u015fmeler yoluyla toplanm\u0131\u015ft\u0131r. Bir karma y\u00f6ntem metodolojisini kullanan bu \u00e7al\u0131\u015fma, \u00f6\u011frenme analiti\u011fi uygulamalar\u0131nda istatistiksel olarak anlaml\u0131 bir etkiye sahip ve t\u00fcmevar\u0131msal olarak olu\u015fturulmu\u015f alt\u0131 boyut (verilerde tan\u0131mlanan 27 boyut i\u00e7inden) tan\u0131mlam\u0131\u015ft\u0131r. B\u00fcy\u00fck \u00f6l\u00e7\u00fcde \u00f6nceki literat\u00fcrden yans\u0131makla birlikte, etkide bulunan boyutlar\u0131n d\u00f6rd\u00fc etkili ve dengeli payda\u015f<\/i><\/span> kat\u0131l\u0131m\u0131, teknolojik kapasite, a\u00e7\u0131k vizyon<\/i><\/span> ve strateji<\/i><\/span> ile etkili liderli\u011fi<\/i><\/span> i\u00e7ermektedir.
                                                                  \nOrtaya \u00e7\u0131kan di\u011fer iki boyut ise kurumsal ba\u011flam (bir kurumun \u00f6\u011frencisi ve kurumsal profil d\u00e2hil) ve kavramsalla\u015ft\u0131rmad\u0131r (bir kurumun \u00f6\u011frenme analiti\u011fini nas\u0131l olu\u015fturdu\u011fu ve anlad\u0131\u011f\u0131). Bu boyutlardan ilki olan kurumsal ba\u011flam, bize \u00f6\u011frenme analiti\u011finin, her kurumun ba\u011flam\u0131na \u00f6zg\u00fc olarak sosyal ve kurumsal alanda bir dizi yap\u0131sal unsur taraf\u0131ndan \u015fekillendirilmi\u015f pratikte bulundu\u011funu hat\u0131rlat\u0131r. Buna kar\u015f\u0131l\u0131k, \u201ckavramsalla\u015ft\u0131rma\u201d boyutu bir kurumun \u00f6\u011frenme analiti\u011fi uygulamalar\u0131na ili\u015fkin temel epistemolojik ve ontolojik konumuyla ba\u011flant\u0131l\u0131d\u0131r. Kurumlar \u00f6\u011frenme analiti\u011fi ile ilgili olarak farkl\u0131 anlay\u0131\u015f, \u00f6zlem ve vizyonlara sahip olsalar da \u00f6\u011frenme analitiklerinin bir kurum taraf\u0131ndan nas\u0131l kavramsalla\u015ft\u0131r\u0131ld\u0131\u011f\u0131 ve ger\u00e7ekte nas\u0131l uyguland\u0131\u011f\u0131 aras\u0131nda ili\u015fkiler bulunmu\u015ftur. Basit\u00e7e, bu \u00e7al\u0131\u015fman\u0131n bulgular\u0131, \u00f6\u011frenme analiti\u011finin anla\u015f\u0131lma \u015fekli ve ona y\u00fcklenen anlam\u0131n, \u00f6\u011frenme analiti\u011finin uygulanmas\u0131n\u0131 nas\u0131l \u015fekillendirdi\u011fini g\u00f6stermektedir. Ayr\u0131ca ara\u015ft\u0131rmada yap\u0131lan k\u00fcmeleme analizi, Avustralya y\u00fcksek\u00f6\u011frenim ba\u011flam\u0131nda iki \u00f6\u011frenme analiti\u011fi uygulama y\u00f6r\u00fcngesinin ortaya \u00e7\u0131kmas\u0131n\u0131 \u00f6nermi\u015ftir. K\u00fcmelerin her birinde, kavramsalla\u015ft\u0131rma, haz\u0131r bulunu\u015fluk (\u00f6nc\u00fcl) ve uygulama boyutlar\u0131n\u0131n kurumlar aras\u0131nda nas\u0131l uyguland\u0131\u011f\u0131 ve tecr\u00fcbe edildi\u011fi konusunda bir uyum mevcuttur. Bir k\u00fcmeleme etkili bir kavramsalla\u015ft\u0131rmay\u0131 ve elde tutma (\u00f6\u011frenci ba\u015far\u0131s\u0131n\u0131 s\u00fcrd\u00fcrme), riskli \u00f6\u011frenci tabanl\u0131 \u00f6\u011frenme analiti\u011fi i\u015flevselle\u015ftirmesini daha ayr\u0131cal\u0131kl\u0131 k\u0131lar g\u00f6r\u00fcnmekteydi. Buna kar\u015f\u0131l\u0131k, ikinci k\u00fcmelenmedeki kurumlar da elde tutma-odakl\u0131 (\u00f6\u011freneni) \u00f6\u011frenme analiti\u011fi faaliyetine yat\u0131r\u0131m yapm\u0131\u015f ancak bunu i\u00e7g\u00f6r\u00fc kazand\u0131rma ama\u00e7l\u0131 etkinlik ve \u00f6\u011fretme-\u00f6\u011frenme s\u00fcrecine y\u00f6nelik bilgilendirme ile desteklemi\u015ftir. Colvin vd.nin (2015) Avustralya’da y\u00fcksek\u00f6\u011frenim ba\u011flam\u0131nda \u00f6\u011frenme analiti\u011finin iki farkl\u0131 uygulama \u00f6r\u00fcnt\u00fcs\u00fcn\u00fcn ortaya \u00e7\u0131kt\u0131makta oldu\u011fu g\u00f6r\u00fcnen bulundu\u011funa y\u00f6nelik bulgusu, bir\u00e7ok mevcut \u00f6\u011frenme analiti\u011fi uygulama \u00e7er\u00e7evesinin temelini olu\u015fturan b\u00fcy\u00fck \u00f6l\u00e7\u00fcde \u00f6zc\u00fc ve pozitivist ontolojik ve epistemolojik varsay\u0131mlara meydan okumaktad\u0131r (bk. Davenport ve Harris, 2007).<\/span><\/p>\n

                                                                  Yinelemeli, Dinamik ve S\u00fcrd\u00fcr\u00fclebilir Olarak \u00d6\u011frenme Analiti\u011fi Uygulamalar\u0131<\/h3>\n

                                                                  \u015eekil 24.1, Colvin vd. (2015), dinamik olarak birbirine ba\u011fl\u0131 ve ge\u00e7ici olan olguyu temsil eden karma\u015f\u0131k Stratejik Beceri modeline dayanan \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131 sunmakta ve \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131n fiil\u00ee performans\u0131n\u0131n gelecekteki kapasiteyi olu\u015fturaca\u011f\u0131n\u0131 \u00f6ne s\u00fcrmektedirler.<\/span><\/p>\n

                                                                  \"\"<\/p>\n

                                                                  <\/a> \u015eekil 24.1. Stratejik Beceri Modeli (Colvin vd., 2015, s. 28).<\/i><\/span><\/span><\/p>\n

                                                                  \u015eekil 24.1, Colvin vd., karma\u015f\u0131k, dinamik olarak birbirine ba\u011fl\u0131 ve ge\u00e7ici olan olguyu temsil eden Stratejik Beceri \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131 sunmaktad\u0131r ve \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131n fiil\u00ee performans\u0131n\u0131n gelecekteki kapasite \u00fcretece\u011fini \u00f6ne s\u00fcrmektedir. Bu bak\u0131mdan, yazarlar taraf\u0131ndan da g\u00f6zlemlendi\u011fi gibi Minimal Uygulanabilir \u00dcr\u00fcn (MU\u00dc) (Munch vd., 2013) ve H\u0131zl\u0131 \u0130novasyon D\u00f6ng\u00fcs\u00fc (Kaski, Alamaki ve Moisio, 2014) ilkeleri ile bu ilkelerin savundu\u011fu \u00fcr\u00fcn geli\u015ftirme ve b\u00fct\u00fcnle\u015ftirmesindeki devaml\u0131, yinelemeli, \u00f6zyinelemeli, s\u00fcre\u00e7 yakla\u015f\u0131m\u0131 hem \u00f6\u011frenme analiti\u011fi uygulama alan\u0131nda bir a\u011f\u0131rl\u0131\u011fa sahiptir hem de kurumsal liderlere olas\u0131 uygulama paradigmalar\u0131 olarak \u00f6nerilmektedir.<\/span><\/p>\n

                                                                  SONU\u00c7<\/h2>\n

                                                                  Colvin vd.nin (2015) \u00e7al\u0131\u015fmas\u0131, \u00f6\u011frenme analiti\u011fi uygulamalar\u0131na ili\u015fkin ara\u015ft\u0131rma literat\u00fcr\u00fcne \u00f6nemli deneysel ve metodolojik katk\u0131lar yapar. \u00d6ncelikle, \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131n \u00f6nc\u00fclleri (sa\u011flay\u0131c\u0131lar\u0131) ve kazan\u0131mlar\u0131 (yani nas\u0131l g\u00f6r\u00fcnd\u00fckleri<\/i><\/span>) aras\u0131ndaki ili\u015fkilere dair deneysel i\u00e7g\u00f6r\u00fcler sa\u011flar. \u00d6\u011frenme analiti\u011finin ve \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131n ger\u00e7ek anlamlar\u0131na dair kat\u0131l\u0131mc\u0131lardan fikirlerinin, niyetlerinin, alg\u0131lay\u0131\u015flar\u0131n\u0131n istenmesi sayesinde kurumsal liderlerin \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131 kavramsalla\u015ft\u0131rma yollar\u0131na dair ince ve ayr\u0131nt\u0131l\u0131 i\u00e7g\u00f6r\u00fcler kazan\u0131lm\u0131\u015f, bu kavramsalla\u015ft\u0131rmalar ile mevcut i\u015flevselle\u015ftirmeler aras\u0131ndaki ili\u015fkilerin ortaya \u00e7\u0131kmas\u0131 sa\u011flanm\u0131\u015ft\u0131r.<\/span><\/p>\n

                                                                  \u00c7ok boyutlu bir olgu olarak Colvin vd.nin (2015) yapt\u0131klar\u0131 ara\u015ft\u0131rmadaki \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131n kavramsalla\u015ft\u0131r\u0131lmas\u0131 ve analizi, ortaya \u00e7\u0131kan \u00f6\u011frenme analiti\u011fi uygulama literat\u00fcr\u00fcn\u00fcn ilkeleriyle uyumludur (bk. Ferguson vd., 2015; Greller ve Drachsler, 2012) ve onlar\u0131n ara\u015ft\u0131rmalar\u0131 sonucu olu\u015fturulan Stratejik Beceri Modeli \u00e7oklu, kesi\u015fen, birbirine ba\u011f\u0131ml\u0131 fakt\u00f6rlerin ge\u00e7ici, yerle\u015fik, dinamik bir sonucu olarak \u00f6\u011frenme analitiklerinin zengin, b\u00fct\u00fcnsel, sistemik bir kavramsalla\u015ft\u0131rmas\u0131n\u0131 sunmaktad\u0131r. Yine de \u00f6zellikle \u00f6nemli olan, \u00f6\u011frenme analiti\u011fi uygulamalar\u0131na arac\u0131l\u0131k eden birincil sosyok\u00fclt\u00fcrel, teknik ve yap\u0131sal fakt\u00f6rlerin g\u00f6reli belirginli\u011fine dair Colvin vd.nin (2015) sa\u011flad\u0131\u011f\u0131 deneysel i\u00e7g\u00f6r\u00fcd\u00fcr.<\/span><\/p>\n

                                                                  Colvin vd.nin (2015) \u00f6\u011frenme analiti\u011fi sunumu, \u00f6\u011frenme analiti\u011fini genellikle do\u011frusal ve\/veya tek boyutlu bir olgu olarak \u00e7er\u00e7eveleyen bir\u00e7ok mevcut modelden ayr\u0131l\u0131r. Bu son kavramsalla\u015ft\u0131rmalar\u0131n, indirgemeci y\u00f6nelimleriyle, \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131n karma\u015f\u0131kl\u0131\u011f\u0131n\u0131, geni\u015fli\u011fini veya bozulmas\u0131n\u0131 tam olarak yakalama potansiyeline sahip olmad\u0131\u011f\u0131n\u0131 ve s\u00fcrd\u00fcr\u00fclebilir ve etkili \u00f6\u011frenme analiti\u011fi uygulama ve stratejilerinin benimsenmesine ve geli\u015ftirilmesine kar\u015f\u0131 istenmeden engelleyici olabilece\u011fini \u00f6ne s\u00fcr\u00fcyoruz. Buna kar\u015f\u0131l\u0131k, Colvin vd.nin (2015) bulgular\u0131 bize \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131n karma\u015f\u0131k oldu\u011funu, birbirine ba\u011f\u0131ml\u0131 \u201cyumu\u015fak ve sert\u201d boyutlarla \u015fekillendirildi\u011fini hat\u0131rlatmaktad\u0131r (Greller ve Drachsler, 2012) ve bu bulgular ayn\u0131 zamanda \u00fcniversitelerdeki geleneksel y\u00f6netim ve \u00f6rg\u00fctsel yap\u0131lara meydan okuyup par\u00e7alama potansiyeline de sahiptir. Ara\u015ft\u0131rmalar\u0131, \u00f6\u011frenme analiti\u011fi y\u00f6neticilerine, \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131n karma\u015f\u0131kl\u0131\u011f\u0131n\u0131 vurgulayan, ba\u011flam\u0131n arac\u0131 rol\u00fcn\u00fc tan\u0131yan, kurum i\u00e7i ve kurumlar aras\u0131 \u00f6\u011frenme analiti\u011fi stratejileri ve \u00f6nceliklerinin de\u011ferlendirmesini kolayla\u015ft\u0131rabilen deneysel olarak t\u00fcretilmi\u015f kavramsal bir \u00e7er\u00e7eve sa\u011flar.<\/span><\/p>\n

                                                                  Colvin vd.nin (2015) ara\u015ft\u0131rmas\u0131n\u0131n s\u0131n\u0131rl\u0131l\u0131klar\u0131 oldu\u011fu belirtilmelidir: verileri \u00f6ncelikli olarak nitelikseldir ve bir y\u00fcksek\u00f6\u011fretim ba\u011flam\u0131nda (Avustralya) bulunan nispeten k\u00fc\u00e7\u00fck bir kurum kat\u0131l\u0131mc\u0131s\u0131 \u00f6rne\u011finden (n = 32) derlenmi\u015ftir. Bu nedenle, bulgular\u0131n alternatif y\u00fcksek\u00f6\u011fretim ba\u011flamlar\u0131na do\u011frudan uygulanmas\u0131 durumunda, daha dikkatli davran\u0131lmal\u0131d\u0131r. Ayr\u0131ca, \u00e7o\u011fu kurum \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131n \u00e7ok erken a\u015famalarda yer ald\u0131lar: programlar\u0131 hen\u00fcz iptidai ve hala geli\u015ftirilmekteydi. \u00d6nc\u00fcl boyutlar ve kazan\u0131mlar aras\u0131nda bildirilen ili\u015fkiler bu nedenle bu ge\u00e7ici s\u0131n\u0131rlamalar i\u00e7inde yorumlanmal\u0131d\u0131r. \u00d6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131n deneysel analizlerinin bu kritik alana daha ayr\u0131nt\u0131l\u0131 bir bak\u0131\u015f a\u00e7\u0131s\u0131 sa\u011flayacak \u015fekilde zaman i\u00e7erisinde yap\u0131lmas\u0131 tavsiye edilir. Bununla birlikte, Colvin vd. (2015) \u00e7al\u0131\u015fmalar\u0131, daha geni\u015f analitik toplulu\u011fu ile uyumlu olmas\u0131 beklenen \u00e7ok boyutluluk ve karma\u015f\u0131kl\u0131k ilkeleri d\u00e2hilinde \u00f6\u011frenme analiti\u011fi uygulamalar\u0131n\u0131 temel alan bir analitik \u00e7er\u00e7eve sunmaktad\u0131r.<\/span><\/p>\n

                                                                  KAYNAK\u00c7A<\/h2>\n

                                                                  Accard, P. (2015). Complex hierarchy: The strategic advantages of a trade-off between hierarchical supervision and self-organizing. European Management Journal, 33<\/i>(2), 89\u2013103. <\/span><\/span><\/p>\n

                                                                  Arnold, K. E., Lonn, S., & Pistilli, M. D. (2014). An exercise in institutional reflection: The learning analytics readiness instrument (LARI). Proceedings of the 4th International Conference on Learning Analytics and Knowledge <\/i>(LAK\u201914), 24\u201328 March 2014, Indianapolis, IN, USA (pp. 163\u2013167). New York: ACM. <\/span><\/span><\/p>\n

                                                                  Arnold, K. E., Lynch, G., Huston, D., Wong, L., Jorn, L., & Olsen, C. W. (2014). Building institutional capacities and competencies for systemic learning analytics initiatives. Proceedings of the 4th International Conference on Learning Analytics and Knowledge <\/i>(LAK\u201914), 24\u201328 March 2014, Indianapolis, IN, USA (pp. 257\u2013260). New York: ACM. <\/span><\/span><\/p>\n

                                                                  Baker, R., & Inventado, P. (2014). Educational data mining and learning analytics. In J. A. Larusson & B. White (Eds.), Learning analytics <\/i>(pp. 61\u201375). New York: Springer. <\/span><\/span><\/p>\n

                                                                  Bichsel, J. (2012). Analytics in higher education: Benefits, barriers, progress and recommendations. Louisville, CO: EDUCAUSE Center for Applied Research. <\/span><\/span><\/p>\n

                                                                  Bolden, R. (2011). Distributed leadership in organizations: A review of theory and research. International Journal of Management Reviews, 13<\/i>(3), 251\u2013269. <\/span><\/span><\/p>\n

                                                                  Carbonell, K. B., Dailey-Hebert, A., & Gijselaers, W. (2013). Unleashing the creative potential of faculty to create blended learning. The Internet and Higher Education, 18<\/i>, 29\u201337. <\/span><\/span><\/p>\n

                                                                  Colvin, C., Rogers, T., Wade, A., Dawson, S., Ga\u0161evi\u0107, D., Buckingham Shum, S., . . . Fisher, J. (2015). Student retention and learning analytics: A snapshot of Australian practices and a framework for advancement. <\/i>Canberra, ACT: Australian Government Office for Learning and Teaching. <\/span><\/span><\/p>\n

                                                                  Conde, M. \u00c1., & Hern\u00e1ndez-Garc\u00eda, \u00c1. (2015). Learning analytics for educational decision making. Computers in Human Behavior, 47<\/i>, 1\u20133. <\/span><\/span><\/p>\n

                                                                  Daniel, B. (2015). Big data and analytics in higher education: Opportunities and challenges. British Journal of Educational Technology, 46<\/i>(5), 904\u2013920. <\/span><\/span><\/p>\n

                                                                  Davenport, T. H., & Harris, J. G. (2007). Competing on analytics: The new science of winning<\/i>. Boston, MA: Harvard Business School Press. <\/span><\/span><\/p>\n

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