{"id":3159,"date":"2026-10-15T01:13:38","date_gmt":"2026-10-14T22:13:38","guid":{"rendered":"https:\/\/www.alazcanbolat.com\/?p=3159"},"modified":"2026-10-15T01:13:38","modified_gmt":"2026-10-14T22:13:38","slug":"bilincdisi-onyargi-egitimi","status":"publish","type":"post","link":"https:\/\/www.alazcanbolat.com\/en\/bilincdisi-onyargi-egitimi\/","title":{"rendered":"Bilin\u00e7d\u0131\u015f\u0131 \u00d6nyarg\u0131 E\u011fitimleri Neden Tek Ba\u015f\u0131na Yetmez? \u0130K \u0130\u00e7in Kan\u0131ta Dayal\u0131 Rehber"},"content":{"rendered":"
\n

K\u0131sa cevap:<\/strong> Bilin\u00e7d\u0131\u015f\u0131 \u00f6nyarg\u0131 e\u011fitimleri fark\u0131ndal\u0131k yarat\u0131r, ancak ara\u015ft\u0131rmalar tek seferlik bir e\u011fitimin karar ve davran\u0131\u015flar\u0131 kal\u0131c\u0131 olarak de\u011fi\u015ftirmedi\u011fini g\u00f6steriyor. Kal\u0131c\u0131 etki, e\u011fitimin i\u015fe al\u0131m, terfi, toplant\u0131 ve performans gibi karar noktalar\u0131na ba\u011flanmas\u0131yla, takip edilmesiyle ve \u00f6l\u00e7\u00fclmesiyle ortaya \u00e7\u0131kar.<\/p>\n<\/div>\n

Kurumlarda \u00e7e\u015fitlilik, hakkaniyet ve kapsay\u0131c\u0131l\u0131k (DEI) \u00e7al\u0131\u015fmalar\u0131n\u0131n ilk ad\u0131m\u0131 \u00e7o\u011fu zaman bir bilin\u00e7d\u0131\u015f\u0131 \u00f6nyarg\u0131 e\u011fitimidir. Bu do\u011fru bir ba\u015flang\u0131\u00e7; ama tek ba\u015f\u0131na b\u0131rak\u0131ld\u0131\u011f\u0131nda beklenen sonucu vermiyor. Bu rehber, \u0130K ve e\u011fitim ekipleri i\u00e7in \u00fc\u00e7 soruya kan\u0131ta dayal\u0131 cevap veriyor: Ara\u015ft\u0131rmalar ne s\u00f6yl\u00fcyor, e\u011fitim neden tek ba\u015f\u0131na yetmiyor ve neyi \u00f6l\u00e7melisiniz?<\/p>\n

Bilin\u00e7d\u0131\u015f\u0131 \u00f6nyarg\u0131 nedir?<\/h2>\n

Zihnimiz h\u0131zl\u0131 karar vermek i\u00e7in kestirme yollar kullan\u0131r. Tversky ve Kahneman (1974) bu zihinsel k\u0131sayollar\u0131n (heuristics) belirli durumlarda sistematik hatalara yol a\u00e7t\u0131\u011f\u0131n\u0131 g\u00f6sterdi. Allport (1954) ise \u00f6nyarg\u0131y\u0131, hatal\u0131 ve esnek olmayan bir genellemeye dayanan tutum olarak tan\u0131mlad\u0131.<\/p>\n

Pratikte ayr\u0131m \u015fudur: Varsay\u0131m<\/strong>, eksik bilgiyle yap\u0131lan ge\u00e7ici bir tahmindir ve yeni bilgi gelince g\u00fcncellenir. \u00d6nyarg\u0131<\/strong> ise bir gruba dair genellemenin, kar\u015f\u0131t bilgi geldi\u011finde bile g\u00fcncellenmemesidir. Bilin\u00e7d\u0131\u015f\u0131 \u00f6nyarg\u0131, bu genellemenin ki\u015finin fark etmedi\u011fi bi\u00e7imde karar ve davran\u0131\u015flar\u0131 etkilemesidir.<\/p>\n

\"Varsay\u0131m<\/figure>\n

\u0130\u015fin zor taraf\u0131, \u00f6nyarg\u0131y\u0131 ba\u015fkas\u0131nda kolay, kendimizde zor g\u00f6rmemizdir. Pronin, Lin ve Ross (2002) insanlar\u0131n kendilerini ortalamadan daha az \u00f6nyarg\u0131l\u0131 de\u011ferlendirdi\u011fini g\u00f6sterdi (k\u00f6r nokta \u00f6nyarg\u0131s\u0131). West, Meserve ve Stanovich (2012) ise bili\u015fsel becerinin bu k\u00f6r noktay\u0131 k\u00fc\u00e7\u00fcltmedi\u011fini buldu.<\/p>\n

Ara\u015ft\u0131rmalar ne diyor?<\/h2>\n\n\n\n\n\n\n\n\n\n
\u00c7al\u0131\u015fma<\/th>\nNe inceledi?<\/th>\nTemel bulgu<\/th>\n<\/tr>\n<\/thead>\n
Forscher ve ark. (2019)<\/td>\n\u00d6rt\u00fck \u00f6nyarg\u0131y\u0131 de\u011fi\u015ftirmeye y\u00f6nelik y\u00f6ntemler; 492 \u00e7al\u0131\u015fma, 87.418 kat\u0131l\u0131mc\u0131<\/td>\n\u00d6rt\u00fck \u00f6l\u00e7\u00fcmler de\u011fi\u015febiliyor ama etki zay\u0131f. Davran\u0131\u015ftaki de\u011fi\u015fim \u00f6nemsiz d\u00fczeyde ve \u00f6rt\u00fck \u00f6l\u00e7\u00fcmdeki de\u011fi\u015fim davran\u0131\u015f de\u011fi\u015fimini a\u00e7\u0131klam\u0131yor.<\/td>\n<\/tr>\n
Lai ve ark. (2016)<\/td>\n\u00d6rt\u00fck tercihleri an\u0131nda azaltan dokuz m\u00fcdahale<\/td>\nEtkilerin hi\u00e7biri birka\u00e7 saatten birka\u00e7 g\u00fcne uzanan bir gecikmeden sonra s\u00fcrmedi.<\/td>\n<\/tr>\n
Chang ve ark. (2019)<\/td>\nK\u00fcresel bir \u015firkette 3.016 \u00e7al\u0131\u015fanla yakla\u015f\u0131k bir saatlik \u00e7evrim i\u00e7i e\u011fitim, saha deneyi<\/td>\nTutum ve niyette art\u0131\u015f g\u00f6r\u00fcld\u00fc; mentorluk ve takdir gibi davran\u0131\u015flarda genel bir etki g\u00f6r\u00fclmedi. Davran\u0131\u015f de\u011fi\u015fimi daha \u00e7ok zaten destekleyici olan gruplarda oldu.<\/td>\n<\/tr>\n
Kalev, Dobbin ve Kelly (2006)<\/td>\nABD’de 708 kurumun 1971\u20132002 verileri<\/td>\nSorumluluk yap\u0131lar\u0131 (eylem plan\u0131, \u00e7e\u015fitlilik komitesi, sorumlu ki\u015fi) y\u00f6netimde temsilin art\u0131\u015f\u0131yla en tutarl\u0131 bi\u00e7imde ili\u015fkiliydi. E\u011fitimin tek ba\u015f\u0131na etkisi s\u0131n\u0131rl\u0131yd\u0131; sorumluluk yap\u0131lar\u0131yla birlikte daha iyi sonu\u00e7 verdi.<\/td>\n<\/tr>\n
Devine ve ark. (2012)<\/td>\n12 haftal\u0131k \u201c\u00f6nyarg\u0131 al\u0131\u015fkanl\u0131\u011f\u0131n\u0131 k\u0131rma\u201d m\u00fcdahalesi<\/td>\n\u00d6rt\u00fck \u00f6nyarg\u0131da uzun s\u00fcreli azalma; ayr\u0131mc\u0131l\u0131\u011fa dair kayg\u0131 ve fark\u0131ndal\u0131k artt\u0131. En b\u00fcy\u00fck azalma, stratejileri ger\u00e7ekten uygulayanlarda g\u00f6r\u00fcld\u00fc.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Bu bulgular e\u011fitimin gereksiz oldu\u011funu s\u00f6ylemiyor. S\u00f6yledi\u011fi \u015fu: Fark\u0131ndal\u0131k gerekli ama yeterli de\u011fil. Davran\u0131\u015f, karar an\u0131n\u0131 de\u011fi\u015ftiren s\u00fcre\u00e7lerle ve tekrarla de\u011fi\u015fiyor.<\/p>\n

E\u011fitim neden tek ba\u015f\u0131na yetmez?<\/h2>\n
    \n
  1. K\u00f6r nokta:<\/strong> Kat\u0131l\u0131mc\u0131lar \u00f6nyarg\u0131y\u0131 kendilerinden \u00e7ok ba\u015fkalar\u0131nda g\u00f6r\u00fcr. \u201cKim \u00f6nyarg\u0131l\u0131?\u201d sorusuyla ba\u015flayan bir e\u011fitim savunmay\u0131 art\u0131rabilir.<\/li>\n
  2. Etki k\u0131sa s\u00fcrer:<\/strong> Tek oturumda olu\u015fan de\u011fi\u015fim g\u00fcnler i\u00e7inde s\u00f6ner (Lai ve ark., 2016). Takip, tekrar ve uygulama yoksa e\u011fitim g\u00fcn\u00fc bir an\u0131 olarak kal\u0131r.<\/li>\n
  3. Kararlar s\u00fcre\u00e7te verilir:<\/strong> \u0130\u015fe al\u0131m, terfi ve \u00fccret kararlar\u0131 ki\u015filerin niyetiyle de\u011fil, kriterlerle, formlarla ve toplant\u0131 d\u00fczeniyle \u015fekillenir. S\u00fcre\u00e7 ayn\u0131 kald\u0131k\u00e7a sonu\u00e7 da b\u00fcy\u00fck \u00f6l\u00e7\u00fcde ayn\u0131 kal\u0131r (Kalev ve ark., 2006).<\/li>\n<\/ol>\n
    \"Tek<\/figure>\n

    Ne i\u015fe yarar? E\u011fitimi sisteme ba\u011flaman\u0131n be\u015f ad\u0131m\u0131<\/h2>\n

    At\u00f6lyelerimde kapsay\u0131c\u0131 karar alma i\u00e7in \u00fc\u00e7 katmanl\u0131 bir \u00e7er\u00e7eve kullan\u0131yorum: Biases<\/strong> (bireyin zihinsel k\u0131sayollar\u0131), Bubbles<\/strong> (ekibin yank\u0131 odas\u0131; Janis’in 1972’de tan\u0131mlad\u0131\u011f\u0131 grup d\u00fc\u015f\u00fcncesi) ve Blind spots<\/strong> (kurumun hi\u00e7 bakmad\u0131\u011f\u0131 alanlar). Bu \u00fc\u00e7l\u00fc Jeroen Kraaijenbrink’in strateji \u00fczerine yaz\u0131s\u0131ndan uyarlanm\u0131\u015ft\u0131r. A\u015fa\u011f\u0131daki ad\u0131mlar her \u00fc\u00e7 katman\u0131 birlikte ele al\u0131r.<\/p>\n

    \"Biases,<\/figure>\n
      \n
    1. Karar noktalar\u0131n\u0131 haritalay\u0131n.<\/strong> \u00d6nyarg\u0131n\u0131n en \u00e7ok etki etti\u011fi anlar\u0131 belirleyin: CV \u00f6n eleme, m\u00fclakat, terfi kurulu, performans de\u011ferlendirmesi, \u00fccret belirleme, toplant\u0131da s\u00f6z da\u011f\u0131l\u0131m\u0131.<\/li>\n
    2. Kriteri adaydan \u00f6nce yaz\u0131n.<\/strong> \u0130\u015fe al\u0131mda ve terfide neye bakaca\u011f\u0131n\u0131z\u0131 adaylar\u0131 g\u00f6rmeden belirleyin; yap\u0131land\u0131r\u0131lm\u0131\u015f m\u00fclakat ve ortak puanlama formu kullan\u0131n (Bohnet, 2016; Levashina ve ark., 2014).<\/li>\n
    3. Karar toplant\u0131s\u0131na iki soru ekleyin.<\/strong> Pre-mortem: \u201cBir y\u0131l sonray\u0131z ve bu karar ba\u015far\u0131s\u0131z oldu; neden?\u201d (Klein, 2007). Tersini d\u00fc\u015f\u00fcnmek: \u201cTam tersi do\u011fru olsayd\u0131 hangi kan\u0131t\u0131 g\u00f6r\u00fcrd\u00fck?\u201d (Lord, Lepper ve Preston, 1984).<\/li>\n
    4. Tek seferlik de\u011fil, aral\u0131kl\u0131 tasarlay\u0131n.<\/strong> E\u011fitimin sonunda her kat\u0131l\u0131mc\u0131 tek bir g\u00f6zlemlenebilir davran\u0131\u015f se\u00e7sin; 7., 14. ve 30. g\u00fcnlerde k\u0131sa yoklamalar yap\u0131n. Devine ve ark. (2012) kal\u0131c\u0131 etkinin, stratejileri haftalar boyunca uygulayanlarda g\u00f6r\u00fcld\u00fc\u011f\u00fcn\u00fc g\u00f6steriyor. Uygulama i\u00e7in E\u011fitimden Sonra 30 G\u00fcn kontrol listesini<\/a> kullanabilirsiniz.<\/li>\n
    5. Sorumlulu\u011fu bir yap\u0131ya ba\u011flay\u0131n.<\/strong> Hedeflerin bir sahibi, bir takvimi ve d\u00fczenli bir g\u00f6zden ge\u00e7irmesi olsun. Kalev ve ark. (2006) e\u011fitimin, sorumluluk yap\u0131lar\u0131yla birlikte uyguland\u0131\u011f\u0131nda daha iyi sonu\u00e7 verdi\u011fini buldu.<\/li>\n<\/ol>\n
      \"E\u011fitimi<\/figure>\n

      Neyi \u00f6l\u00e7melisiniz?<\/h2>\n

      E\u011fitim memnuniyeti etkinin g\u00f6stergesi de\u011fildir. Kirkpatrick modelinin diliyle, tepki (1. d\u00fczey) de\u011fil davran\u0131\u015f (3. d\u00fczey) ve sonu\u00e7 (4. d\u00fczey) \u00f6l\u00e7\u00fclmelidir.<\/p>\n\n\n\n\n\n\n\n\n\n
      Alan<\/th>\nG\u00f6sterge<\/th>\nNe zaman?<\/th>\n<\/tr>\n<\/thead>\n
      \u0130\u015fe al\u0131m<\/td>\nYap\u0131land\u0131r\u0131lm\u0131\u015f m\u00fclakat ve ortak puanlama formuyla yap\u0131lan m\u00fclakatlar\u0131n oran\u0131<\/td>\nE\u011fitim \u00f6ncesi ve 3 ay sonra<\/td>\n<\/tr>\n
      Terfi ve \u00fccret<\/td>\nYaz\u0131l\u0131 kritere dayanan kararlar\u0131n oran\u0131; gruplar aras\u0131 terfi ve \u00fccret farklar\u0131<\/td>\nHer de\u011ferlendirme d\u00f6neminde<\/td>\n<\/tr>\n
      Toplant\u0131lar<\/td>\nS\u00f6z alma da\u011f\u0131l\u0131m\u0131; farkl\u0131 g\u00f6r\u00fc\u015f bildirme s\u0131kl\u0131\u011f\u0131 (k\u0131sa g\u00f6zlem formu)<\/td>\nE\u011fitim \u00f6ncesi ve 30. g\u00fcn<\/td>\n<\/tr>\n
      Davran\u0131\u015f<\/td>\nKat\u0131l\u0131mc\u0131n\u0131n se\u00e7ti\u011fi davran\u0131\u015f\u0131 uygulama s\u0131kl\u0131\u011f\u0131 (\u00f6z bildirim + y\u00f6netici g\u00f6zlemi)<\/td>\n7., 14. ve 30. g\u00fcn<\/td>\n<\/tr>\n
      \u0130klim<\/td>\nAidiyet ve psikolojik g\u00fcvenlik alg\u0131s\u0131 (ayn\u0131 sorularla tekrar \u00f6l\u00e7\u00fcm)<\/td>\nY\u0131lda iki kez<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

      \u00d6nemli not:<\/strong> \u00d6rt\u00fck \u00e7a\u011fr\u0131\u015f\u0131m testleri (IAT gibi) e\u011fitimde fark\u0131ndal\u0131k ve tart\u0131\u015fma arac\u0131 olarak yararl\u0131d\u0131r; ancak bireyleri de\u011ferlendirmek, se\u00e7mek veya etiketlemek i\u00e7in kullan\u0131lmamal\u0131d\u0131r. Yukar\u0131daki ara\u015ft\u0131rmalar, bu testlerdeki de\u011fi\u015fimin davran\u0131\u015f de\u011fi\u015fimi anlam\u0131na gelmedi\u011fini g\u00f6steriyor.<\/p>\n

      Bilin\u00e7siz \u00d6n Yarg\u0131lar At\u00f6lyesi bu yakla\u015f\u0131m\u0131 nas\u0131l uyguluyor?<\/h2>\n

      Unconscious Bias: Who We Exclude Without Thinking<\/a> at\u00f6lyesi fark\u0131ndal\u0131kla ba\u015flar ama orada bitmez: Kat\u0131l\u0131mc\u0131lar kendi karar noktalar\u0131n\u0131 haritalar, ki\u015fisel bir uygulama plan\u0131 \u00e7\u0131kar\u0131r ve e\u011fitim sonras\u0131 takip ad\u0131mlar\u0131yla davran\u0131\u015f\u0131 i\u015f ritmine ba\u011flar. Program, kurumunuzun karar s\u00fcre\u00e7lerine ve \u00f6l\u00e7mek istedi\u011finiz g\u00f6stergelere g\u00f6re 90 dakika, yar\u0131m g\u00fcn veya tam g\u00fcn olarak uyarlan\u0131r.<\/p>\n

      30 dakikal\u0131k ke\u015fif g\u00f6r\u00fc\u015fmesi planlay\u0131n<\/a><\/p>\n

      References<\/h2>\n