{"id":99,"date":"2020-09-03T16:39:40","date_gmt":"2020-09-03T13:39:40","guid":{"rendered":"http:\/\/acikkitap.com.tr\/oaek\/chapter\/bolum-15-epistemik-ag-analizi-kurama-dayali-ogrenme-analitiginin-calisilmis-bir-ornegi\/"},"modified":"2020-09-03T16:39:40","modified_gmt":"2020-09-03T13:39:40","slug":"bolum-15-epistemik-ag-analizi-kurama-dayali-ogrenme-analitiginin-calisilmis-bir-ornegi","status":"publish","type":"chapter","link":"https:\/\/acikkitap.com.tr\/oaek\/chapter\/bolum-15-epistemik-ag-analizi-kurama-dayali-ogrenme-analitiginin-calisilmis-bir-ornegi\/","title":{"raw":"B\u00f6l\u00fcm 15 Epistemik A\u011f Analizi: Kurama Dayal\u0131 \u00d6\u011frenme Analiti\u011finin \u00c7al\u0131\u015f\u0131lm\u0131\u015f Bir \u00d6rne\u011fi","rendered":"B\u00f6l\u00fcm 15 Epistemik A\u011f Analizi: Kurama Dayal\u0131 \u00d6\u011frenme Analiti\u011finin \u00c7al\u0131\u015f\u0131lm\u0131\u015f Bir \u00d6rne\u011fi"},"content":{"raw":"\n

David Williamson Shaffer ve A. R. Ruis<\/span><\/span><\/p>\n

Wisconsin E\u011fitim Ara\u015ft\u0131rmalar\u0131 Merkezi, Wisconsin \u00dcniversitesi, Madison, ABD<\/span><\/span><\/p>\n

DOI: 10.18608\/hla17.015<\/span><\/span><\/p>\n\n

\u00d6Z<\/h2>\n

Bu makalede, bir e\u011fitsel oyun ba\u011flam\u0131nda \u00f6\u011frenme analiti\u011finin teori temelli bir yakla\u015f\u0131m\u0131n \u00e7al\u0131\u015f\u0131lm\u0131\u015f bir \u00f6rne\u011fini sunuyoruz. Bunu, di\u011ferlerinin taklit etti\u011fi ideal bir \u00e7\u00f6z\u00fcm sunmak i\u00e7in de\u011fil; veri odakl\u0131 bir yakla\u015f\u0131mdan ziyade teori temelli yakla\u015f\u0131m\u0131n sa\u011flay\u0131c\u0131l\u0131\u011f\u0131n\u0131 ara\u015ft\u0131rmak i\u00e7in yap\u0131yoruz. Bunu, 1) \u00f6\u011frenmenin kavramsalla\u015ft\u0131r\u0131lmas\u0131na bir yakla\u015f\u0131m olarak epistemik \u00e7er\u00e7eve teorisini sunarak; 2) epistemik \u00e7er\u00e7eve teorisine dayanan e\u011fitsel oyun tasar\u0131m\u0131na bir yakla\u015f\u0131m olan epistemik bir oyundan elde edilen veriler ve 3) epistemik a\u011f analizi (EAA), ayn\u0131 teoriye dayanan karma\u015f\u0131k d\u00fc\u015f\u00fcnmenin kan\u0131t\u0131 i\u00e7in s\u00f6ylem ve di\u011fer verileri analiz etme tekni\u011fi olarak sunuyoruz. EAA'y\u0131 belirli bir analitik sonu\u00e7 ile tan\u0131ml\u0131yoruz ancak amac\u0131m\u0131z bu sonucun \u00f6\u011frenme analiti\u011fi alan\u0131nda bizim kilit \"en iyi uygulama\" olarak d\u00fc\u015f\u00fcnd\u00fc\u011f\u00fcm\u00fcz \u015feyi nas\u0131l \u00f6rnekledi\u011fini ara\u015ft\u0131rmakt\u0131r.<\/span><\/span><\/p>\n

Anahtar Kelimeler<\/span>: Epistemik \u00e7er\u00e7eve teorisi, epistemik oyun, epistemik a\u011f analizi (EAA), kan\u0131t merkezli tasar\u0131m<\/span><\/span><\/p>\n

Bu b\u00f6l\u00fcmde, kuram\u0131n \u00f6\u011frenme analiti\u011findeki rol\u00fcne bak\u0131yoruz. \u00d6\u011frenmeyi inceleyen ara\u015ft\u0131rmac\u0131lar, ister son derece \u00e7ok say\u0131daki ki\u015fi hakk\u0131ndaki bilgi veya ister \u00f6\u011frenme s\u00fcrecinde mikroskobik, anl\u0131k eylemleri g\u00f6steren veriler olsun, e\u015fi benzeri g\u00f6r\u00fclmemi\u015f miktarlarda veri ile kutsanm\u0131\u015flard\u0131r. Bu cesur yeni d\u00fcnyad\u0131r1<\/a><\/sup>. \u00d6\u011frencilerin dikkatlerinin yo\u011funla\u015ft\u0131rd\u0131klar\u0131 yere saniye saniye bakabilir veya KA\u00c7D'lerdeki binlerce \u00f6\u011frenciyi inceleyerek hangi t\u00fcr \u00e7al\u0131\u015fma becerilerinin etkili oldu\u011funu inceleyebiliriz. Wise ve Shaffer (2016)'\u0131n, \u00d6\u011frenme Analiti\u011fi Dergisi<\/i><\/span>nin \u00f6zel bir b\u00f6l\u00fcm\u00fcnde belirtti\u011fi gibi, yeterli bilgi varsa verinin kendi ad\u0131na konu\u015fabilece\u011fini yani, \u00f6\u011frenme teorileri olmadan \u00f6\u011frenme analizleri yapabilece\u011fimizi d\u00fc\u015f\u00fcnmek tehlikelidir. Esasen, bunun tam tersi do\u011frudur. Daha b\u00fcy\u00fck miktarda veri ile teori, analizde daha da hassas bir rol oynar. Basit bir ifadeyle belirtmek gerekirse, belirli boyut ve t\u00fcrdeki veri k\u00fcmeleri i\u00e7in en g\u00fcncel istatistiksel ara\u00e7lar geli\u015ftirilmi\u015ftir: rastgele etkilerin normal da\u011f\u0131l\u0131m\u0131 i\u00e7in yeterince b\u00fcy\u00fck ancak geleneksel veri toplama teknikleri kullan\u0131larak elde edilecek kadar k\u00fc\u00e7\u00fck. Bu teknikleri, g\u00fc\u00e7l\u00fc bir teorik temele sahip olmayan b\u00fcy\u00fckl\u00fc\/boyut s\u0131ras\u0131 daha uzun olan ve de\u011fi\u015fken say\u0131s\u0131 bak\u0131m\u0131ndan daha b\u00fcy\u00fck olan veri k\u00fcmelerine uygulamak en iyi ihtimalle tehlikelidir.<\/span><\/p>\n

Sonras\u0131nda, bu soruya istatisti\u011fin uygulama problemlerini teorik bir \u00e7er\u00e7eve olmadan analiz ederek bakm\u0131yoruz. Wise ve Shaffer\u2019\u0131n \u00f6nerdi\u011fi -ve \u00d6\u011frenme Analiti\u011fi Dergisi<\/i><\/span>'nin \u00f6zel b\u00f6l\u00fcm\u00fcndeki makale ve yorumlar\u0131n bize g\u00f6sterdi\u011fi \u015fey- teoriye dayal\u0131 \u00f6\u011frenme analiti\u011fi y\u00fcr\u00fctmenin zor oldu\u011fudur. Sonu\u00e7 olarak, neyin takip edece\u011fi ile ilgili yakla\u015f\u0131m\u0131m\u0131z, \u00e7al\u0131\u015fan bir \u00f6rnek kullanarak \u00f6\u011frenme analiti\u011fi teorisinin rol\u00fcn\u00fc incelemektir; \u00f6rnek olarak bir problemin sunumu ve \u00e7\u00f6z\u00fcm\u00fcn\u00fcn ad\u0131m ad\u0131m a\u00e7\u0131klamas\u0131 (Atkinson, Derry, Renkl ve Wortham, 2000) verilebilir.<\/span><\/p>\n

Bunu yaparken amac\u0131m\u0131z, ba\u015fkalar\u0131na taklit edecek ideal bir \u00e7\u00f6z\u00fcm sunmak veya bizim teoriyi \u00f6\u011frenme analiti\u011finde belli bir \u015fekilde kullanmamam\u0131z\u0131n di\u011ferlerinden daha iyi oldu\u011funu ortaya koymak de\u011fildir. Daha \u00e7ok, hedefimiz, b\u00fcy\u00fck e\u011fitsel veri k\u00fcmelerinin analizine teorik temelli -veri odakl\u0131 ya da teori temelli olmayan bir yakla\u015f\u0131m\u0131n aksine- bir yakla\u015f\u0131m\u0131n \u00f6nemini yans\u0131tmakt\u0131r. Bunu yeni bir \u00f6\u011frenme analiti\u011fi tekni\u011fi olan epistemik a\u011f analizini sunarak (EAA; Andrist, Collier, Gleicher, Mutlu ve Shaffer, 2015; Arastoopour, Shaffer, Swiecki, Ruis ve Chesler, 2016; Chesler vd., 2015; Nash ve Shaffer, 2013; Rupp, Gustha, Mislevy ve Shaffer, 2010; Rupp, Sweet ve Choi, 2010; Shaffer vd., 2009; Shaffer, Collier ve Ruis, 2016; Svarovsky, 2011) yap\u0131yoruz. Fakat daha da \u00f6nemlisi, EAA'n\u0131n dayand\u0131\u011f\u0131 \u00f6\u011frenme yakla\u015f\u0131m\u0131 olan epistemik \u00e7er\u00e7eve teorisi<\/i><\/span> ba\u011flam\u0131nda sunuyoruz ve onu epistemik \u00e7er\u00e7eve teorisine dayanan e\u011fitsel oyun tasar\u0131m\u0131na bir yakla\u015f\u0131m olarak bir epistemik oyuna uyguluyoruz. Bu nedenle, EAA'y\u0131 sonucun teori, veri ve analizin uyumlanmas\u0131n\u0131 nas\u0131l alandaki \u201cen iyi uygulama\u201d olarak \u00f6rneklendirdi\u011fini incelemek amac\u0131yla belirli bir analitik sonu\u00e7 yoluyla tan\u0131ml\u0131yoruz.<\/span><\/p>\n\n

VER\u0130<\/h2>\n

Bu \u00e7al\u0131\u015fan belirli \u00f6rne\u011fi incelemek i\u00e7in kullanaca\u011f\u0131m\u0131z veriler, \u00f6\u011frencilerin uzmanlar gibi d\u00fc\u015f\u00fcnmelerini \u00f6\u011frenmelerine yard\u0131mc\u0131 olan otantik bir profesyonel uygulama sim\u00fclasyonu olan epistemik bir oyundan gelmektedir (Shaffer, 2006, 2007). \u00d6zel olarak, veriler, \u00f6\u011frencilerin stajyer rol\u00fcn\u00fc \u00fcstlendikleri Lowell, Massachusetts kentindeki hayali bir firmada bir yeniden geli\u015ftirme s\u00f6zle\u015fmesi i\u00e7in rekabet ettikleri \u00e7evrimi\u00e7i bir kentsel planlama sim\u00fclasyonu olan bir epistemik oyun Land Science'dan geliyor. \u015eehri farkl\u0131 payda\u015f gruplar\u0131n\u0131n taleplerini kar\u015f\u0131layan farkl\u0131 bir kullan\u0131m i\u00e7in tahsis eden yeni bir plan geli\u015ftirmek i\u00e7in sohbet ve e-posta yoluyla ileti\u015fim kuran k\u00fc\u00e7\u00fck ekiplerde \u00e7al\u0131\u015f\u0131yorlar. Bunu yapmak i\u00e7in, \u00f6\u011frenciler ara\u015ft\u0131rma \u00f6zetlerini ve di\u011fer kaynaklar\u0131 g\u00f6zden ge\u00e7irir, payda\u015f tercihleri hakk\u0131nda bir anket yaparlar ve arazi kullan\u0131m\u0131 de\u011fi\u015fikliklerinin kirlilik, gelir, bar\u0131nma ve GIS haritalama arac\u0131 kullanarak di\u011fer g\u00f6stergeler \u00fczerindeki etkilerini modelleyebilirler. Hi\u00e7bir farkl\u0131 kullan\u0131m tahsis plan\u0131 t\u00fcm payda\u015f tercihlerini yerine getiremeyece\u011finden, \u00f6\u011frenciler nihai tekliflerinde verdikleri kararlar\u0131 gerek\u00e7elendirmelidir.<\/span><\/p>\n

Land Science, lise \u00f6\u011frencileri ve \u00fcniversite birinci s\u0131n\u0131f \u00f6\u011frencileri ile 30'dan fazla kez kullan\u0131lm\u0131\u015ft\u0131r. \u00d6nceki ara\u015ft\u0131rmam\u0131z (Bagley ve Shaffer, 2009, 2015b; Nash, Bagley ve Shaffer, 2012; Nash ve Shaffer, 2012; Shaffer, 2007), Land Science'\u0131n \u00f6\u011frencilerin kentsel ekoloji, kentsel planlama ve ilgili alanlarda i\u00e7erik ve uygulamalar\u0131 \u00f6\u011frenmelerine yard\u0131mc\u0131 oldu\u011funu ve ayr\u0131ca okuldaki performans\u0131 iyile\u015ftirmek i\u00e7in beceriler, ilgi alanlar\u0131 ve motivasyon geli\u015ftirmelerine yard\u0131mc\u0131 oldu\u011funu g\u00f6stermi\u015ftir.<\/span><\/p>\n

Pek \u00e7ok e\u011fitim teknolojisinde oldu\u011fu gibi, Land Science, sohbet s\u0131ras\u0131nda, e-postalar\u0131nda, not defterlerinde, di\u011fer i\u015f \u00fcr\u00fcnlerinde, her tu\u015f bas\u0131\u015f\u0131nda ve fare t\u0131klatmas\u0131 d\u00e2hil olmak \u00fczere, sim\u00fclasyon s\u0131ras\u0131nda \u00f6\u011frencilerin yapt\u0131klar\u0131 her \u015feyi kaydeder. Bu sadece \u00f6\u011frencilerin nihai \u00fcr\u00fcnlerini de\u011fil ayn\u0131 zamanda kulland\u0131klar\u0131 problem \u00e7\u00f6zme s\u00fcre\u00e7lerini de analiz etmeyi m\u00fcmk\u00fcn k\u0131lar.<\/span><\/p>\n

A\u015fa\u011f\u0131da verilen \u00e7al\u0131\u015f\u0131lm\u0131\u015f \u00f6rnekte, Land Science'\u0131n ayn\u0131 s\u00fcr\u00fcm\u00fcn\u00fc kullanan yedi \u00fcniversite \u00f6\u011frencisi grubu (n = 155), sekiz lise \u00f6\u011frencisi grubunu (n = 110) ve \u00fc\u00e7 grup \u00fcst\u00fcn yetenekli ve yetenekli lise \u00f6\u011frencisi (n = 46) d\u00e2hil olmak \u00fczere 311 \u00f6\u011frencini sohbetlerini inceliyoruz. Bu veri k\u00fcmesi b\u00fct\u00fcn\u00fcyle 44.964 sohbet sat\u0131r\u0131n\u0131 i\u00e7eriyor.<\/span><\/p>\n\n

KURAM<\/h2>\n

Land Sciencedan gelen sohbet verisi analizimiz epistemik \u00e7er\u00e7eve teorisi taraf\u0131ndan bilgilendirilmektedir (Shaffer, 2004, 2006, 2007, 2012). Epistemik \u00e7er\u00e7eve teorisi, bir uygulama toplulu\u011funun d\u00fcnyadaki d\u00fc\u015f\u00fcnme, hareket etme ve olma yollar\u0131n\u0131 modellemektedir (Lave ve Wenger, 1991; Rohde ve Shaffer, 2004). Sorunlar\u0131 \u00e7er\u00e7evelemek, ara\u015ft\u0131rmak ve \u00e7\u00f6zmek i\u00e7in ortak bir yakla\u015f\u0131ma sahip bir uygulama toplulu\u011fu veya bir grup insan, bir bilgi ve beceri repertuar\u0131na, beceri ve bilginin nas\u0131l kullan\u0131lmas\u0131 gerekti\u011fini y\u00f6nlendiren bir de\u011ferler dizisine ve kararlar almak ve do\u011frulamak i\u00e7in bir dizi s\u00fcrece sahiptir. Bir toplulu\u011fun hem a\u00e7\u0131k belirte\u00e7lerle hem de toplulu\u011fun karakteristik becerilerinin, de\u011ferlerinin ve karar alma s\u00fcre\u00e7lerinin \u00e7\u0131kar\u0131lmas\u0131 yoluyla sergilenen ortak bir kimli\u011fi de vard\u0131r.<\/span><\/p>\n

Bir uygulama toplulu\u011funun par\u00e7as\u0131 olmak, ba\u015fka bir deyi\u015fle, belirli bir S\u00f6ylem edinmek demektir : bir \u201ckonu\u015fma, dinleme, yazma, okuma, hareket etme, etkile\u015fim kurma, inanma, de\u011fer verme ve hissetme\" yolu (ve \u00e7e\u015fitli nesneler, semboller, g\u00f6r\u00fcnt\u00fcler ara\u00e7lar ve teknolojiler kullanma) \u201d(Gee, 1999, s. 719). Bir S\u00f6ylem, bir k\u00fclt\u00fcr\u00fcn tezah\u00fcr\u00fcd\u00fcr ve Goodwin\u2019in (1994) profesyonel g\u00f6r\u00fc\u015f\u00fcne dayanarak, epistemik bir \u00e7er\u00e7eve bir S\u00f6ylemin dil bilgisidir: belirli bir uygulama toplulu\u011funun \u00fcyeleri taraf\u0131ndan sergilenen S\u00f6ylem \u00f6gelerinin yap\u0131land\u0131rmas\u0131n\u0131n resm\u00ee a\u00e7\u0131klamas\u0131d\u0131r.<\/span><\/p>\n

Ancak \u00f6nemli olarak, bir toplulu\u011fun epistemik \u00e7er\u00e7evesini niteleyen ilgili bilgi, beceri, de\u011ferler, uygulamalar ve di\u011fer nitelikler de\u011fil; onlar\u0131n belirli bir \u015fekilde ayarlan\u0131p yap\u0131land\u0131r\u0131lmas\u0131d\u0131r. Bir \u00e7er\u00e7eve kavram\u0131 Goffman'dan (1974) gelmektedir (ayr\u0131ca bk. Tannen, 1993). Etkinlik, \u00e7er\u00e7eve olarak yorumlan\u0131r: alg\u0131lar\u0131 ve eylemleri \u015fekillendiren kurallar ve g\u00f6r\u00fc\u015fler ya da deneyimlerin yorumland\u0131\u011f\u0131 normlar ve uygulamalar dizisi. B\u00f6ylece, epistemik bir \u00e7er\u00e7eve, otantik g\u00f6revlerle (veya otantik g\u00f6revlerin sim\u00fclasyonlar\u0131na) ilgilenen bir bireyin eylemleri ve etkile\u015fimleri ile ortaya \u00e7\u0131kar.<\/span><\/p>\n

Epistemik bir \u00e7er\u00e7eveyi olu\u015fturan unsurlar aras\u0131ndaki ba\u011flant\u0131lar\u0131 analitik olarak tan\u0131mlamak i\u00e7in, \u00f6\u011frencilerin s\u00f6ylemindeki e\u015f olu\u015fumlar\u0131<\/i><\/span> -bu durumda \u00e7evrimi\u00e7i bir sohbet program\u0131nda yap\u0131lan konu\u015fmalarda tespit ederiz. Ara\u015ft\u0131rmac\u0131lar (Chesler vd., 2015; Dorogovtsev ve Mendes, 2013; i Cancho ve Sole, 2001; Landauer, McNamara, Dennis ve Kintsch, 2007; Lund ve Burgess, 1996) \u00f6zellikle de e\u015f olu\u015fumlar s\u0131k oldu\u011funda belirli bir s\u00f6ylem verisi dilimindeki kavramlar\u0131n e\u015f olu\u015fumlar\u0131n\u0131n bili\u015fsel ba\u011flant\u0131lar\u0131n iyi bir g\u00f6stergesi oldu\u011funu tespit etmi\u015flerdir (Newman, 2004). Bu kavramlar, teorik ya da g\u00f6rg\u00fcl\/ deneysel bir analizden ya da eylem halindeki toplulu\u011fun etnografik bir \u00e7al\u0131\u015fmas\u0131ndan olay \u00f6ncesi2<\/a><\/sup> duruma dayal\u0131 olarak tan\u0131mlanabilir.<\/span><\/p>\n

EAA, s\u00f6ylem verilerinin b\u00f6l\u00fcmlerindeki e\u015f olu\u015fumlar\u0131 tespit ederek ve e\u015f olu\u015fumlar\u0131n a\u011f\u0131rl\u0131kl\u0131 yap\u0131s\u0131n\u0131 modelleyerek epistemik \u00e7er\u00e7eve teorisini i\u015fler hale getirir. EAA zaman i\u00e7inde epistemik bir \u00e7er\u00e7evenin g\u00fcc\u00fcndeki ve kompozisyonundaki de\u011fi\u015fiklikleri \u00f6l\u00e7en dinamik bir a\u011f modelinde bu ortak olu\u015fum \u00f6r\u00fcnt\u00fclerini temsil eder- bir sonraki b\u00f6l\u00fcmde a\u00e7\u0131klayaca\u011f\u0131m\u0131z bir s\u00fcre\u00e7 olarak tan\u0131mlar\u0131z.<\/span><\/p>\n\n

EAA<\/h2>\n

EAA, ba\u011flant\u0131 verilerinin a\u011f\u0131rl\u0131kl\u0131 yap\u0131s\u0131n\u0131 s\u00f6ylem verilerinde veya herhangi bir d\u00f6rtl\u00fck3<\/a><\/sup> temelli etkile\u015fim verilerinde modeller. Daha sonra, EAA y\u00f6nteminin genel prensiplerini ve EAA yaz\u0131l\u0131m\u0131n\u0131n g\u00fcncel versiyonunun www.epistemicnetwork.org<\/span>'un EAA algoritmalar\u0131n\u0131 uygulad\u0131\u011f\u0131<\/i><\/span> spesifik s\u00fcreci a\u00e7\u0131kl\u0131yoruz.<\/span><\/p>\n\n

Fikir Birimleri Tabanl\u0131 Etkile\u015fim Verileri<\/h3>\n

EAA'n\u0131n epistemik \u00e7er\u00e7eve teorisini nas\u0131l i\u015fletti\u011fini a\u00e7\u0131klamadan \u00f6nce, verilerin EAA kullan\u0131larak analiz i\u00e7in nas\u0131l yap\u0131land\u0131r\u0131ld\u0131\u011f\u0131n\u0131 anlamak \u00f6nemlidir. Land Science'de bir grup \u00f6\u011frenci taraf\u0131ndan yap\u0131lan iki konu\u015fmadan al\u0131nt\u0131lar\u0131 g\u00f6steren Tablo 15.1'deki basitle\u015ftirilmi\u015f verilere dikkat edin. Sa\u011fdaki be\u015f s\u00fctunda, birliktelik \u00f6r\u00fcnt\u00fcs\u00fcn\u00fc modellemek istedi\u011fimiz kavramlar ya da kodlar vard\u0131r. Bu durumda, kodlar, bir kentsel planlama epistemik \u00e7er\u00e7evesinin \u00e7e\u015fitli unsurlar\u0131 olan profesyonel \u015fehir planlama prati\u011finin \u00e7e\u015fitli y\u00f6nlerini temsil eder.<\/span><\/p>\n

Bazen, Jorge'nin hem sosyal hem de \u00e7evresel konular hakk\u0131ndaki bilgileri referans ald\u0131\u011f\u0131 Sat\u0131r 3 'te oldu\u011fu gibi, kodlar aras\u0131ndaki ili\u015fkileri tek bir ifadede g\u00f6rebilece\u011fimizi unutmay\u0131n. Di\u011fer durumlarda, ifadeler aras\u0131nda ili\u015fkiler ortaya \u00e7\u0131kar: Sat\u0131r 10'da Depesh, Natalie'nin Sat\u0131r 8'deki feragat hakk\u0131ndaki daha genel bir yorumuna cevap veren ve a\u00e7\u0131k alan\u0131n artmas\u0131yla ilgili olarak bunun \u00fczerine dayand\u0131rd\u0131\u011f\u0131 feragatten bahseder. Ancak her konu\u015fma s\u0131ras\u0131 aras\u0131nda kodlar aras\u0131ndaki ili\u015fkilere bakmak istemeyebiliriz. \u00d6rne\u011fin, iki ayr\u0131 konu\u015fma Tablo 15.1'de g\u00f6sterilmektedir. Her ikisi de ayn\u0131 \u00f6\u011frenci grubunu (Grup 3) i\u00e7erir ancak \u00f6\u011frenciler iki farkl\u0131 etkinlik \u00fczerinde \u00e7al\u0131\u015f\u0131rken konu\u015fmalar iki farkl\u0131 g\u00fcnde ger\u00e7ekle\u015fmi\u015ftir.<\/span><\/p>\n

Bu verilerin bir a\u011f modelini olu\u015fturmak i\u00e7in, sat\u0131rlar\u0131 fikir birimlerine g\u00f6re gruplamam\u0131z gerekir. Bu fikir biriminin arkas\u0131ndaki ana fikir, (a) ayn\u0131 fikir birimi i\u00e7indeki herhangi bir sat\u0131rdaki kodlar\u0131n modelde birbirleriyle ili\u015fkili oldu\u011fu ve (b) ayn\u0131 fikir biriminde olmayan sat\u0131rlardaki kodlar\u0131n, modelde birbirleriyle ili\u015fkili olmad\u0131\u011f\u0131d\u0131r. Bu durumda, fikir birimleri hangi kavram birlikteliklerinin kent planlamas\u0131n\u0131n epistemik \u00e7er\u00e7eve unsurlar\u0131 aras\u0131nda anlaml\u0131 bili\u015fsel ba\u011flant\u0131lar\u0131 temsil etti\u011fini g\u00f6stermektedir.<\/span><\/p>\n

<\/a><\/a><\/a><\/a><\/a><\/p>\n

Tablo 15.1. EAA Format\u0131nda Kodlanan S\u00f6ylem Verilerinin D\u00fczenlenmi\u015f Al\u0131nt\u0131lar\u0131<\/i><\/span><\/span><\/p>\n\n<\/colgroup>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\n

Sat\u0131r<\/b><\/span><\/p>\n<\/td>\n

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Etkinlik<\/b><\/span><\/p>\n<\/td>\n

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Grup<\/b><\/span><\/p>\n<\/td>\n

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Kullan\u0131c\u0131 ad\u0131<\/b><\/span><\/p>\n<\/td>\n

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Olu\u015fturma<\/b><\/span><\/p>\n<\/td>\n

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\u0130fade<\/b><\/span><\/p>\n<\/td>\n

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E.Sosyal.Kullan\u0131m<\/b><\/span><\/p>\n<\/td>\n

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S.imar.kodlar\u0131<\/b><\/span><\/p>\n<\/td>\n

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K.sosyal.konular<\/b><\/span><\/p>\n<\/td>\n

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K.imar.kodlar\u0131<\/b><\/span><\/p>\n<\/td>\n

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K.ortam<\/b><\/span><\/p>\n<\/td>\n<\/tr>\n<\/thead>\n

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1<\/span><\/p>\n<\/td>\n

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VSV Toplant\u0131s\u0131<\/span><\/p>\n<\/td>\n

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3<\/span><\/p>\n<\/td>\n

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Natalie<\/span><\/p>\n<\/td>\n

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02\/11\/14 10:03<\/span><\/p>\n<\/td>\n

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Tamam, payda\u015flar ne istiyor?<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n<\/tr>\n

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2<\/span><\/p>\n<\/td>\n

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VSV Toplant\u0131s\u0131<\/span><\/p>\n<\/td>\n

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3<\/span><\/p>\n<\/td>\n

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Depesh<\/span><\/p>\n<\/td>\n

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02\/11\/14 10:03<\/span><\/p>\n<\/td>\n

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w \/ payda\u015flarla konu\u015furken, \u015fehir i\u00e7inde bir\u00e7ok sorun oldu\u011funu \u00f6\u011frendik, ancak bu sorunlar\u0131n kolayca \u00e7\u00f6z\u00fclmesini engelleyen baz\u0131 engeller var<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n<\/tr>\n

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3<\/span><\/p>\n<\/td>\n

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VSV Toplant\u0131s\u0131<\/span><\/p>\n<\/td>\n

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3<\/span><\/p>\n<\/td>\n

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Jorge<\/span><\/p>\n<\/td>\n

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02\/11\/14 10:04<\/span><\/p>\n<\/td>\n

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Evet, payda\u015flar b\u00f6lgedeki \u00e7evresel etkilerin yan\u0131 s\u0131ra d\u00fc\u015f\u00fck gelirli konut ihtiyac\u0131na da \u00f6nem veriyor<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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1<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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1<\/span><\/p>\n<\/td>\n<\/tr>\n

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4<\/span><\/p>\n<\/td>\n

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VSV Toplant\u0131s\u0131<\/span><\/p>\n<\/td>\n

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3<\/span><\/p>\n<\/td>\n

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Depesh<\/span><\/p>\n<\/td>\n

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02\/11\/14 10:04<\/span><\/p>\n<\/td>\n

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farkl\u0131 konular\u0131 \u00f6nemsiyorlard\u0131 ama hepsi sa\u011fl\u0131kl\u0131 ve ya\u015fanabilir bir topluluk yaratmak istiyorlard\u0131<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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1<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n<\/tr>\n

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5<\/span><\/p>\n<\/td>\n

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VSV Toplant\u0131s\u0131<\/span><\/p>\n<\/td>\n

\n

3<\/span><\/p>\n<\/td>\n

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Natalie<\/span><\/p>\n<\/td>\n

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02\/11\/14 10:05<\/span><\/p>\n<\/td>\n

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Kat\u0131l\u0131yorum. Ayr\u0131ca suyun kalitesi i\u00e7in endi\u015feleniyorlar.<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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1<\/span><\/p>\n<\/td>\n<\/tr>\n

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6<\/span><\/p>\n<\/td>\n

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VSV Toplant\u0131s\u0131<\/span><\/p>\n<\/td>\n

\n

3<\/span><\/p>\n<\/td>\n

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Jessie<\/span><\/p>\n<\/td>\n

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02\/11\/14 10:06<\/span><\/p>\n<\/td>\n

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ve d\u00fc\u015f\u00fck gelirli sakinler i\u00e7in daha fazla konut f\u0131rsat\u0131 istiyorlar<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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1<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n<\/tr>\n

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7<\/span><\/p>\n<\/td>\n

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iPlan Toplant\u0131s\u0131<\/span><\/p>\n<\/td>\n

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3<\/span><\/p>\n<\/td>\n

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Jorge<\/span><\/p>\n<\/td>\n

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02\/13\/14 10:21<\/span><\/p>\n<\/td>\n

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H\u0131zl\u0131 soru, P g\u00f6stergesinin anlam\u0131 nedir?<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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1<\/span><\/p>\n<\/td>\n<\/tr>\n

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8<\/span><\/p>\n<\/td>\n

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iPlan Toplant\u0131s\u0131<\/span><\/p>\n<\/td>\n

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3<\/span><\/p>\n<\/td>\n

\n

Natalie<\/span><\/p>\n<\/td>\n

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02\/13\/14 10:21<\/span><\/p>\n<\/td>\n

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Belirli sitelerin imar tan\u0131mlar\u0131n\u0131 de\u011fi\u015ftirirken belirli g\u00f6stergelerin de\u011fi\u015fti\u011fini buldum. \u0130mar kategorisindeki her de\u011fi\u015fiklik, faydalar\u0131 ve sak\u0131ncalar\u0131 ile geldi. Genelde bir feragat durumu vard\u0131.<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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1<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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1<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n<\/tr>\n

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9<\/span><\/p>\n<\/td>\n

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iPlan Toplant\u0131s\u0131<\/span><\/p>\n<\/td>\n

\n

3<\/span><\/p>\n<\/td>\n

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Jessie<\/span><\/p>\n<\/td>\n

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02\/13\/14 10:21<\/span><\/p>\n<\/td>\n

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@Jorge: P = fosforlu<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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1<\/span><\/p>\n<\/td>\n<\/tr>\n

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10<\/span><\/p>\n<\/td>\n

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iPlan Toplant\u0131s\u0131<\/span><\/p>\n<\/td>\n

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3<\/span><\/p>\n<\/td>\n

\n

Depesh<\/span><\/p>\n<\/td>\n

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02\/13\/14 10:22<\/span><\/p>\n<\/td>\n

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evet, a\u00e7\u0131k alan eklerseniz, ka\u00e7maya ve i\u00e7 i\u00e7e ge\u00e7meye yard\u0131mc\u0131 olabilirsiniz ancak i\u015f tutar\u0131n\u0131 da olumsuz etkileyebilirsiniz<\/span><\/p>\n<\/td>\n

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1<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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1<\/span><\/p>\n<\/td>\n

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1<\/span><\/p>\n<\/td>\n<\/tr>\n

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11<\/span><\/p>\n<\/td>\n

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iPlan Toplant\u0131s\u0131<\/span><\/p>\n<\/td>\n

\n

3<\/span><\/p>\n<\/td>\n

\n

Jorge<\/span><\/p>\n<\/td>\n

\n

02\/13\/14 10:25<\/span><\/p>\n<\/td>\n

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Evet, her \u015fey bir \u015feyi etkiler.<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

EAA Modelleri<\/h3>\n

Fikir birimlerine dayal\u0131 etkile\u015fim verilerinden bir a\u011f modeli olu\u015fturmak i\u00e7in EAA, fikir birimlerini daralt\u0131r. Genellikle bu ikili bir birikim olarak yap\u0131l\u0131r: e\u011fer fikir birimindeki herhangi bir veri sat\u0131r\u0131 A kodunu i\u00e7eriyorsa, o zaman fikir birimi A kodunu i\u00e7erir. \u00d6rne\u011fin, fikir birimlerini tan\u0131mlamak i\u00e7in \u201cEtkinlik\u201d se\u00e7ene\u011fini se\u00e7ersek, Tablo 15.1'de g\u00f6sterilen veriler Tablo 15.2'de g\u00f6sterildi\u011fi gibi daralt\u0131l\u0131r.<\/span><\/p>\n

<\/a><\/a><\/a><\/a><\/a> Tablo 15.2. Grup 3 i\u00e7in etkinliklerine g\u00f6re Fikir Birimleri<\/i><\/span><\/span><\/p>\n\n<\/colgroup>\n\n\n\n\n
\n

Etkinlik<\/b><\/p>\n<\/td>\n

\n

Grup<\/b><\/p>\n<\/td>\n

\n

E.sosyal:Say\u0131<\/b><\/p>\n<\/td>\n

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S.imar kodlar\u0131<\/b><\/p>\n<\/td>\n

\n

K.imar.kodlar\u0131<\/b><\/p>\n<\/td>\n

\n

K.ortam<\/b><\/p>\n<\/td>\n<\/tr>\n

VSV Toplant\u0131s\u0131<\/span><\/span><\/td>\n3<\/span><\/span><\/td>\n\n

0<\/p>\n<\/td>\n

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0<\/p>\n<\/td>\n

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0<\/p>\n<\/td>\n

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0<\/p>\n<\/td>\n<\/tr>\n

VSV Toplant\u0131s\u0131<\/span><\/span><\/td>\n3<\/span><\/span><\/td>\n\n

0<\/p>\n<\/td>\n

\n

0<\/p>\n<\/td>\n

\n

1<\/p>\n<\/td>\n

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0<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

EAA daha sonra her bir fikir birimi i\u00e7in kodlar\u0131n bir arada oldu\u011funu \u00f6zetleyen bir kom\u015fuluk matrisi yarat\u0131r (bk. Tablo 15.3). Matrisin k\u00f6\u015fegen k\u0131sm\u0131 t\u00fcm s\u0131f\u0131rlar\u0131 i\u00e7erir, \u00e7\u00fcnk\u00fc bu modeldeki ve genel olarak EAA'daki kodlar kendileri ile birlikte bulunmaz. Her bir biti\u015fiklik matrisi, bu durumda, Grup 3'\u00fcn belirli bir faaliyet s\u0131ras\u0131nda \u015fehir planlama epistemik \u00e7er\u00e7eve elemanlar\u0131 aras\u0131nda yapt\u0131\u011f\u0131 ba\u011flant\u0131lar\u0131 temsil eder. \u00d6rne\u011fin, VSV Toplant\u0131s\u0131 etkinli\u011finde, K.sosyal.sorunlar ve K.ortam\u0131n ikisi de Grup 3\u2019\u00fcn s\u00f6yleminde ger\u00e7ekle\u015fti. Tablo 15.3'teki (yukar\u0131da) bu etkinli\u011fi temsil eden biti\u015fiklik matris, bu nedenle, bu iki kodun e\u015fzamanl\u0131l\u0131\u011f\u0131n\u0131 temsil eden h\u00fccrelerde 1 i\u00e7erir.<\/span><\/p>\n

Her fikir birimini temsil eden biti\u015fiklik matrisleri daha sonra veri k\u00fcmesindeki her bir analiz birimi i\u00e7in k\u00fcm\u00fclatif bir biti\u015fiklik matrisi halinde toplan\u0131r. Tablo 15.3'te g\u00f6sterilen basit \u00f6rnek b\u00f6ylece Tablo 15.4'te g\u00f6sterilen k\u00fcm\u00fclatif biti\u015fiklik matrisi ile temsil edilir. Bu birikim i\u015fleminin sonunda, veri k\u00fcmesindeki her birim (bu durumda, her bir grup) bu birim i\u00e7in, kodlar aras\u0131nda (epistemik \u00e7er\u00e7eve elemanlar\u0131) a\u011f\u0131rl\u0131kl\u0131 birlikte ya\u015fama modelini (bili\u015fsel ba\u011flant\u0131lar) temsil eden k\u00fcm\u00fclatif bir biti\u015fiklik matrisi ile ili\u015fkilidir.<\/span><\/p>\n

Farkl\u0131 birimler aras\u0131ndaki ba\u011flant\u0131lar\u0131n yap\u0131s\u0131n\u0131 anlamak, kendi ba\u011flant\u0131 a\u011flar\u0131 aras\u0131ndaki ili\u015fkileri veya birikimli biti\u015fik matrisleri aras\u0131ndaki farkl\u0131l\u0131klar\u0131 anlamak i\u00e7in EAA, her bir vekt\u00f6r\u00fcn matrisin \u00fcst \u00e7apraz yar\u0131s\u0131ndaki bir de\u011ferle tan\u0131mland\u0131\u011f\u0131 her bir birikimli biti\u015fiklik matrisini y\u00fcksek boyutlu bir uzayda bir vekt\u00f6r olarak temsil eder. Bu bo\u015flu\u011fun boyutlar\u0131n\u0131n, her bir kod \u00e7ifti aras\u0131ndaki ili\u015fkinin g\u00fcc\u00fcne kar\u015f\u0131l\u0131k geldi\u011fine dikkat edin.<\/span><\/p>\n

<\/a><\/a><\/a><\/a><\/a> Tablo 15.3. Grup 3 i\u00e7in etkinliklerine g\u00f6re Fikir Birimleri<\/i><\/span><\/span><\/p>\n\n<\/colgroup>\n\n\n\n\n\n\n\n
\n

3. Grup VS Toplant\u0131s\u0131<\/b><\/span><\/p>\n<\/td>\n

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E.sosyal.konular<\/b><\/span><\/p>\n<\/td>\n

\n

S.imar.kodlar\u0131<\/b><\/span><\/p>\n<\/td>\n

\n

K.sosyal.konular<\/b><\/span><\/p>\n<\/td>\n

\n

K.imar.kodlar\u0131<\/b><\/span><\/p>\n<\/td>\n

\n

K.ortam<\/b><\/span><\/p>\n<\/td>\n<\/tr>\n

E.sosyal.konular<\/span><\/span><\/td>\n\n

0<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n<\/tr>\n

S.imar.kodlar\u0131<\/span><\/span><\/td>\n\n

0<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n<\/tr>\n

K.sosyal.konular<\/span><\/span><\/td>\n\n

0<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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1<\/span><\/p>\n<\/td>\n<\/tr>\n

K.imar.kodlar\u0131<\/span><\/span><\/td>\n\n

0<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n<\/tr>\n

K.ortam<\/span><\/span><\/td>\n\n

0<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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1<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/colgroup>\n\n\n\n\n\n\n\n
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3. Grup iPlan Toplant\u0131s\u0131<\/b><\/span><\/p>\n<\/td>\n

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E.sosyal.konular<\/b><\/span><\/p>\n<\/td>\n

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<\/a><\/a><\/a><\/a><\/a> Tablo 15.4. Grup 3 i\u00e7in K\u00fcm\u00fclatif Biti\u015fiklik Matrisi, Tablo 3'te g\u00f6sterilen \u0130ki Biti\u015fiklik Matrisinin Toplanmas\u0131<\/i><\/span><\/span><\/p>\n\n<\/colgroup>\n\n\n\n\n\n\n\n
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EAA alan\u0131ndaki verileri analiz etmeden \u00f6nce, EAA, verileri normalle\u015ftirmek i\u00e7in her bir vekt\u00f6r\u00fc uzunlu\u011funa b\u00f6ler. Bu bir vekt\u00f6r\u00fcn uzunlu\u011fu potansiyel olarak analiz \u00fcnitesinde bulunan fikir birimi say\u0131s\u0131ndan etkilendi\u011fi i\u00e7in yap\u0131l\u0131r. Daha fazla birimin daha fazla vekt\u00f6r ortaya \u00e7\u0131karmas\u0131 olas\u0131d\u0131r, bu da daha uzun vekt\u00f6rlerle sonu\u00e7lan\u0131r. Bu problemlidir, \u00e7\u00fcnk\u00fc iki vekt\u00f6r ayn\u0131 birliktelik \u00f6r\u00fcnt\u00fcs\u00fcn\u00fc temsil edebilir ve bu nedenle ayn\u0131 y\u00f6ne i\u015faret eder ancak farkl\u0131 say\u0131da fikir birimini temsil eder ve dolay\u0131s\u0131yla farkl\u0131 uzunluklara sahiptir.<\/span><\/p>\n

Veriler normalle\u015ftirildikten sonra EAA, verileri merkezleyen ancak yeniden \u00f6l\u00e7eklendirmeyen bir projeksiyon olarak, bir tekil de\u011fer ayr\u0131\u015ft\u0131rmas\u0131 (TDA) ger\u00e7ekle\u015ftirir. Bu verilerde hesaba kat\u0131lan varyans\u0131 maksimuma \u00e7\u0131kar\u0131r (temel bile\u015fenler analizine benzer). Bununla birlikte, geleneksel bir TBA veya fakt\u00f6r analizinden farkl\u0131 olarak, (a) EAA, kodlar\u0131n say\u0131lar\u0131 veya g\u00fc\u00e7l\u00fcl\u00fc\u011f\u00fcnden ziyade, k\u00fcm\u00fclatif biti\u015fiklik matrislerin e\u015f olu\u015fumlar\u0131 \u00fczerinde ger\u00e7ekle\u015ftirilir ve (b) EAA, orijinal veriler \u00fczerinde bir k\u00fcre veya kosin\u00fcs normu uygular ve onlar\u0131 ortalar ancak boyutlar\u0131 tek tek \u00f6l\u00e7eklendirmez.<\/span><\/p>\n\n

EAA Modellerinin Yorumlanmas\u0131<\/h4>\n

Bir ENA modeli olu\u015fturulduktan sonra, anlaml\u0131 bir yorumu anlamak ve olu\u015fturmak i\u00e7in bir tak\u0131m ara\u00e7lar kullan\u0131labilir. \u00d6rne\u011fin, yukar\u0131da a\u00e7\u0131klanan Land Science veri k\u00fcmesinde, t\u00fcm \u00f6\u011frencilerin sohbet ifadeleri, daha \u00f6nce geli\u015ftirilmi\u015f ve onaylanm\u0131\u015f bir otomatik kodlama i\u015flemi kullan\u0131larak (24) kentsel planlama epistemik \u00e7er\u00e7eve elemanlar\u0131 i\u00e7in kodlanm\u0131\u015ft\u0131r (Ek I'e bak\u0131n\u0131z). Nash ve Shaffer (Bagley ve Shaffer, 2015b; Nash ve Shaffer)., 2011). Kentsel planlamac\u0131lar\u0131n nas\u0131l e\u011fitildi\u011fine dair etnografik bir \u00e7al\u0131\u015fmaya dayanarak otantik kentsel planlama uygulamas\u0131yla ilgili kodlar geli\u015ftirilmi\u015ftir (Bagley ve Shaffer, 2015a).<\/span><\/p>\n

\"\"<\/p>\n<\/a> \u015eekil 15.1. Sim\u00fcle edilmi\u015f bir kentsel geli\u015fim problemini \u00e7\u00f6zerken \u00f6\u011frencini yapt\u0131\u011f\u0131 bili\u015fsel ba\u011flant\u0131lar\u0131n yap\u0131s\u0131n\u0131 temsil eden bir lise \u00f6\u011frencisinin epistemik a\u011f\u0131 (\u00d6\u011frenci A). Parantez i\u00e7indeki y\u00fczdeler, her bir boyut taraf\u0131ndan hesaplanan modeldeki toplam varyans\u0131 g\u00f6stermektedir. Birden fazla veri kayna\u011f\u0131n\u0131n birle\u015ftirilmesi.<\/i><\/span><\/span>\n

EAA modelleri tipik olarak, bir seferde iki boyutu kullanarak g\u00f6rselle\u015ftirilir ki bu yorumlamay\u0131 kolayla\u015ft\u0131r\u0131r. \u00d6rne\u011fin, \u015eekil 15.1, Land Science'a kat\u0131lan bir lise \u00f6\u011frencisinin (\u00d6\u011frenci A) k\u00fcm\u00fclatif epistemik a\u011f\u0131n\u0131 g\u00f6stermektedir. A\u011f, \u00f6\u011frenenin kentsel planlama epistemik \u00e7er\u00e7evesinin unsurlar\u0131 aras\u0131ndaki ba\u011flant\u0131lar\u0131n yap\u0131s\u0131n\u0131 modellemektedir. Bu durumda, \u00d6\u011frenci A'n\u0131n a\u011f\u0131, sosyal konular ve karma\u015f\u0131k sistemlerin bilgisi gibi bilgi unsurlar\u0131,uzla\u015fma ve kentsel planlama ara\u00e7lar\u0131n\u0131 kullanma becerisi (tercih anketi gibi) gibi epistemolojik unsurlar aras\u0131nda bir dizi ba\u011flant\u0131 g\u00f6sterir. Bu a\u011f ayr\u0131ca a\u011f\u0131rl\u0131kl\u0131d\u0131r: daha kal\u0131n, daha doymu\u015f \u00e7izgiler daha g\u00fc\u00e7l\u00fc ba\u011flant\u0131lar\u0131 temsil ederken, daha ince, daha az doymu\u015f \u00e7izgiler daha zay\u0131f ba\u011flant\u0131lar\u0131 temsil eder. Bir \u00e7izginin kal\u0131nl\u0131\u011f\u0131 \/ doygunlu\u011fu, iki epistemik \u00e7er\u00e7eve eleman\u0131 aras\u0131ndaki ba\u011flant\u0131n\u0131n meydana geldi\u011fi fikir birimi say\u0131s\u0131 ile orant\u0131l\u0131d\u0131r.<\/span><\/p>\n

\u00c7o\u011fu durumda bu \u00f6\u011frencinin a\u011f\u0131 -\u00f6rne\u011fin genellikle temel bilgi ve beceriler aras\u0131nda bili\u015fsel ba\u011flant\u0131lar kurmu\u015f olan A \u00f6\u011frencisi -hakk\u0131nda baz\u0131 \u00e7\u0131kar\u0131mlara ula\u015f\u0131rken, bir a\u011f\u0131n g\u00f6ze \u00e7arpan \u00f6zelliklerinin di\u011fer a\u011flarla kar\u015f\u0131la\u015ft\u0131r\u0131ld\u0131\u011f\u0131nda tan\u0131mlanmas\u0131 daha kolayd\u0131r. \u015eekil 15.2, ikinci lise \u00f6\u011frencisinin (\u00d6\u011frenci B) kentsel planlama epistemik a\u011f\u0131n\u0131 g\u00f6stermektedir. \u00d6\u011frenci A gibi, \u00d6\u011frenci B de temel bilgi unsurlar\u0131 aras\u0131nda bir tak\u0131m ba\u011flant\u0131lar kursa da \u00d6\u011frenci B'nin a\u011f\u0131, daha \u00e7ok ve daha g\u00fc\u00e7l\u00fc ba\u011flant\u0131lar ve ek unsurlara, \u00f6zellikle bilimsel d\u00fc\u015f\u00fcnce gibi daha ileri becerilere ve epistemolojik \u00f6zelliklere sahiptir.<\/span><\/p>\n

\"\"<\/p>\n<\/a> \u015eekil 15.2. Sim\u00fcle edilmi\u015f bir kentsel geli\u015fim problemini \u00e7\u00f6zerken lise \u00f6\u011frencisinin bili\u015fsel ba\u011flant\u0131lar\u0131n\u0131 temsil eden bir epistemik a\u011f\u0131 (\u00d6\u011frenci B).<\/i><\/span><\/span>\n

Yukar\u0131da tart\u0131\u015f\u0131ld\u0131\u011f\u0131 gibi, epistemik \u00e7er\u00e7eve teorisi, kentsel planlama (veya herhangi bir uygulama toplulu\u011funun) epistemik \u00e7er\u00e7evesinin, kentsel planlama bilgisi, becerileri, de\u011ferleri ve di\u011fer niteliklerin birbiriyle ne kadar ba\u011flant\u0131l\u0131 oldu\u011fu ile tan\u0131mland\u0131\u011f\u0131n\u0131 ortaya koymaktad\u0131r. Bu \u00f6rnekte, EAA \u00d6\u011frenci B\u2019nin a\u011f\u0131n\u0131n daha a\u00e7\u0131k bir \u015fekilde epistemik oldu\u011funu ortaya koymaktad\u0131r: d\u00fc\u015f\u00fcncesini \u015fehir planlamac\u0131lar\u0131n\u0131n yapt\u0131\u011f\u0131 gibi a\u00e7\u0131klam\u0131\u015f ve gerek\u00e7elendirmi\u015f ve b\u00f6ylece bir \u015fehir planc\u0131s\u0131 gibi d\u00fc\u015f\u00fcnmeyi \u00f6\u011frenmi\u015ftir.<\/span><\/p>\n

A ve B \u00f6\u011frencileri aras\u0131ndaki bu kar\u015f\u0131la\u015ft\u0131rmay\u0131 m\u00fcmk\u00fcn k\u0131lan \u015fey, her iki epistemik a\u011fdaki d\u00fc\u011f\u00fcmlerin, bu iki \u00f6\u011frenci i\u00e7in ve veri k\u00fcmesindeki t\u00fcm \u00f6\u011frenciler i\u00e7in a\u011f projeksiyon alan\u0131nda ayn\u0131 yerlerde g\u00f6r\u00fcnmesidir. D\u00fc\u011f\u00fcm yerle\u015fimindeki bu de\u011fi\u015fmezlik, farkl\u0131 birimlerin a\u011f projeksiyonlar\u0131n\u0131 do\u011frudan kar\u015f\u0131la\u015ft\u0131rmam\u0131za olanak tan\u0131r ancak bu do\u011frudan kar\u015f\u0131la\u015ft\u0131rma y\u00f6ntemi sadece \u00e7ok az say\u0131da a\u011f- i\u00e7in \u00e7al\u0131\u015f\u0131r, ya d\u00fczinelerce veya y\u00fczlerce a\u011f\u0131 kar\u015f\u0131la\u015ft\u0131rmak istiyorsak? \u00d6rne\u011fin, bu veri k\u00fcmesindeki 110 lise \u00f6\u011frencisini kar\u015f\u0131la\u015ft\u0131rmak veya lise \u00f6\u011frencilerini \u00fcniversite \u00f6\u011frencileriyle kar\u015f\u0131la\u015ft\u0131rmak istiyorsak ne olur? EAA bunu, her bir a\u011f\u0131 projeksiyon alan\u0131ndaki tek bir nokta olarak temsil ederek m\u00fcmk\u00fcn k\u0131lar, b\u00f6ylece her bir nokta kar\u015f\u0131l\u0131k gelen a\u011f\u0131n sentroidi olur.<\/span><\/p>\n

Bir a\u011f\u0131n sentroidi, bir nesnenin k\u00fctle merkezine benzer. Spesifik olarak, bir a\u011f grafi\u011finin sentroidi, uzayda a\u011f projeksiyonuna g\u00f6re da\u011f\u0131t\u0131lm\u0131\u015f a\u011f modelinin kenar a\u011f\u0131rl\u0131klar\u0131n\u0131n aritmetik ortalamas\u0131d\u0131r. Buradaki \u00f6nemli nokta, bir EAA a\u011f\u0131n\u0131n sentroidinin a\u011f\u0131, a\u011f modelinin belirli bir d\u00fczenlemesindeki ba\u011flant\u0131lar\u0131n a\u011f\u0131rl\u0131kl\u0131 yap\u0131s\u0131n\u0131 a\u00e7\u0131klayan projeksiyon alan\u0131ndaki tek bir nokta olarak \u00f6zetlemesidir.<\/span><\/p>\n

A\u011f projeksiyonundaki d\u00fc\u011f\u00fcmlerin yerleri, herhangi bir a\u011f i\u00e7in, (a) a\u011f grafi\u011finin k\u00fctle merkezi ve (b) a\u011f\u0131 TDA d\u00f6n\u00fc\u015f\u00fcm\u00fc alt\u0131nda temsil eden noktay\u0131 en aza indirmek i\u00e7in bir optimizasyon rutini ile belirlenir. Bir a\u011f\u0131n sentroidinin, \u00f6ng\u00f6r\u00fclen bir uzayda a\u011f\u0131n konumuna kar\u015f\u0131l\u0131k gelmesi i\u00e7in sabit d\u00fc\u011f\u00fcm konumlar\u0131n\u0131n se\u00e7ilmesi, projeksiyon alan\u0131n\u0131n ve dolay\u0131s\u0131yla EAA modelinde farkl\u0131 a\u011flar aras\u0131ndaki belirgin farkl\u0131l\u0131klar\u0131n karakterizasyonuna izin verir. Bu durumda, projeksiyon alan\u0131n\u0131 \u015fu \u015fekilde yorumlayabiliriz: sola do\u011fru, profesyonel ileti\u015fim ve \u015fehir planlama ara\u00e7lar\u0131n\u0131n kullan\u0131m\u0131 gibi temel mesleki beceriler; sa\u011fa do\u011fru, belirli geli\u015fim problemiyle ilgili bilgi unsurlar\u0131, veri ve bilimsel d\u00fc\u015f\u00fcnme gibi daha genel konular\u0131n bilgisi ve sol \u00fcste do\u011fru daha geli\u015fmi\u015f kentsel planlama d\u00fc\u015f\u00fcncesinin unsurlar\u0131, \u00f6zellikle kentsel planlama s\u00f6zle\u015fmelerine ve imar kodlar\u0131n\u0131n kullan\u0131m\u0131na g\u00f6re kararlar alan ve hakl\u0131 \u00e7\u0131karan epistemolojik unsurlar.<\/span><\/p>\n

B\u00f6ylece, \u00e7ok say\u0131da farkl\u0131 a\u011f\u0131 e\u015fzamanl\u0131 olarak kar\u015f\u0131la\u015ft\u0131rabiliriz, \u00e7\u00fcnk\u00fc projeksiyon alan\u0131n\u0131n ayn\u0131 b\u00f6l\u00fcm\u00fcnde bulunan sentroidler benzer ba\u011flant\u0131 \u00f6r\u00fcnt\u00fclerine sahip a\u011flar\u0131 temsil ederken, projeksiyon alan\u0131n\u0131n farkl\u0131 b\u00f6l\u00fcmlerinde bulunan k\u00fctle merkezleri farkl\u0131 ba\u011flant\u0131 \u00f6r\u00fcnt\u00fclerine sahip a\u011flar\u0131 temsil eder4<\/a><\/sup>. Bu \u00f6\u011frencilerin kentsel planlama epistemik \u00e7er\u00e7eveleri hakk\u0131nda herhangi bir say\u0131da ara\u015ft\u0131rma sorusunu ke\u015ffetmemize olanak sa\u011flar. Land Science veri k\u00fcmesine sorabilece\u011fimiz bir soru, farkl\u0131 \u00f6\u011frenci topluluklar\u0131n\u0131n (kolej, lise ve \u00fcst\u00fcn yetenekli lise) epistemik a\u011flar\u0131n\u0131n nas\u0131l farkl\u0131 oldu\u011fudur? \u00d6rne\u011fin, \u00fcniversite \u00f6\u011frencilerini ve lise \u00f6\u011frencilerinin sentroidlerini \u00e7izdi\u011fimizde (\u015eekil 15.3), iki grup farkl\u0131 \u015fekilde da\u011f\u0131lm\u0131\u015ft\u0131r. Fark\u0131n istatistiksel olarak anlaml\u0131 olup olmad\u0131\u011f\u0131n\u0131 belirlemek i\u00e7in, iki pop\u00fclasyonun projeksiyon alan\u0131ndaki ortalama pozisyonlar\u0131 \u00fczerinde ba\u011f\u0131ms\u0131z \u00f6rneklemler t testi yapabiliriz. \u00dcniversite \u00f6\u011frencileri (koyu ve lise \u00f6\u011frencilerine (a\u00e7\u0131k) her iki boyutta da \u00f6nemli \u00f6l\u00e7\u00fcde farkl\u0131d\u0131r:<\/span><\/p>\nx \u0305 <\/i>\u0305<\/span>\u00dcniversite<\/i><\/sub>= <\/i>-0.083, x <\/i>\u0305<\/span>HS<\/i><\/sub>= <\/i>0.115, t = <\/i>-7.025, p < <\/i>0.001, Cohen's d = <\/i>-0.428 <\/span><\/span>\n\ny <\/i>\u0305<\/span>\u00dcniversite<\/i><\/sub>= <\/i>0.040, y <\/i>\u0305<\/span>HS<\/i><\/sub>= -<\/i>0.045, t = <\/i>3.199, p = <\/i>0.002, Cohen's d = <\/i>0.186 <\/span><\/span>\n

\"\"<\/p>\n<\/a> \u015eekil 15.3. \u00dcniversite \u00f6\u011frencileri (koyu) ve lise \u00f6\u011frencilerinin (a\u00e7\u0131k) sentroidlerive onlara kar\u015f\u0131l\u0131k gelen ara\u00e7larla (kareler) ve g\u00fcven aral\u0131klar\u0131 (kutular).<\/i><\/span><\/span>\n

\u00dcst\u00fcn zek\u00e2l\u0131 ve yetenekli lise \u00f6\u011frencileri analize d\u00e2hil edildi\u011finde, baz\u0131 a\u00e7\u0131lardan, \u00fcniversite \u00f6\u011frencilerine daha \u00e7ok benzerken di\u011ferleri ise lise \u00f6\u011frencilerine daha \u00e7ok benzerler. \u00dcst\u00fcn yetenekli lise \u00f6\u011frencilerinin projeksiyon alan\u0131ndaki ortalama konumu (\u015eekil 15.4) hem \u00fcniversite \u00f6\u011frencilerinden hem de lise \u00f6\u011frencilerinden yaln\u0131zca ilk (x) boyutta istatistiksel olarak anlaml\u0131 derecede farkl\u0131d\u0131r:<\/span><\/p>\n

\"\"<\/p>\n

\u015eekil 15.4. \u00dcniversite \u00f6\u011frencileri (solda), lise \u00f6\u011frencileri (sa\u011fda) ve \u00fcst\u00fcn yetenekli lise \u00f6\u011frencilerinde (ortada) ortalama a\u011f konumlar\u0131 (kareler) ve g<\/i><\/span>\u00fcven aral\u0131klar\u0131 (kutular).<\/i><\/span><\/p>\n

<\/a><\/p>\n

x \u0305<\/span>GiftedHS<\/sub>= <\/i>0.007, x <\/i>\u0305<\/span>\u00dcniversite<\/sub>= -<\/i>0.083, t = <\/i>2.538, p = <\/i>0.013, Cohen's d=<\/i>0.202<\/span><\/p>\n

x \u0305<\/span>GiftedHS<\/sub>= <\/i>0.007, x <\/i>\u0305<\/span>\u00dcniversite<\/sub>= <\/i>0.115, t = -<\/i>2.736, p = <\/i>0.007, Cohen's d=-<\/i>0.223<\/span><\/p>\n \n

\"\"<\/p>\n<\/a> \u015eekil 15.5. \u00dcniversite \u00f6\u011frencileri (sol), \u00fcst\u00fcn yetenekli lise \u00f6\u011frencileri (merkez) ve lise \u00f6\u011frencileri (sa\u011f) ortalama epistemik a\u011flar\u0131.<\/i><\/span><\/span>\n

\u00dc\u00e7 grup aras\u0131ndaki farkl\u0131l\u0131klar\u0131 belirlemede hangi fakt\u00f6rlerin hesaba kat\u0131laca\u011f\u0131n\u0131 belirlemek i\u00e7in onlar\u0131n ortalama epistemik a\u011flar\u0131n\u0131 kar\u015f\u0131la\u015ft\u0131rabiliriz. \u015eekil 15.5'te g\u00f6r\u00fcld\u00fc\u011f\u00fc gibi, \u00fcst\u00fcn yetenekli lise \u00f6\u011frencileri ortalama olarak lise \u00f6\u011frencilerinden daha geli\u015fmi\u015f ve \u015fehir planlama d\u00fc\u015f\u00fcncesinin unsurlar\u0131yla daha g\u00fc\u00e7l\u00fc ba\u011flar kurmu\u015flard\u0131r. Yani, lise ve \u00fcniversite \u00f6\u011frencilerinden aras\u0131nda, alandaki karma\u015f\u0131k d\u00fc\u015f\u00fcnceye ili\u015fkin bir yerdeydiler. Buna kar\u015f\u0131l\u0131k, \u00fcst\u00fcn yetenekli lise \u00f6\u011frencileri, her iki pop\u00fclasyonun da temel mesleki beceriler ve ileri kent planlama d\u00fc\u015f\u00fcncesi aras\u0131ndaki \u00fcniversite \u00f6\u011frencilerinden daha az ba\u011flant\u0131 kurmas\u0131 nedeniyle lise \u00f6\u011frencilerine daha benzer g\u00f6r\u00fcn\u00fcyor. Ba\u015fka bir deyi\u015fle, \u00fcst\u00fcn zek\u00e2l\u0131 lise \u00f6\u011frencileri, lise ve \u00fcniversite \u00f6\u011frencileri aras\u0131nda entelekt\u00fcel bir yerdedir ancak temel mesleki ve ki\u015filer aras\u0131 beceriler seviyesinde lise \u00f6\u011frencilerine daha benzerdir.<\/span><\/p>\n\n

EAA A\u011f Modellerinin Nicel \u00dc\u00e7genlemesi(Triangulation)<\/h3>\n

EAA'n\u0131n en \u00f6nemli \u00f6zelli\u011fi, modeldeki ba\u011flant\u0131lar\u0131, sohbetlerin dayand\u0131\u011f\u0131 orijinal verilere kadar izleyebilmesidir. \u201cSosyal konular\u0131n epistemolojisi\u201d ile \u201cveri bilgisi\u201d aras\u0131ndaki ba\u011flant\u0131y\u0131 t\u0131klayarak, bu ba\u011flant\u0131ya katk\u0131da bulunan t\u00fcm ifadelere a\u011f grafi\u011finden eri\u015febiliriz. \u015eekil 15.6, bir \u00fcniversite \u00f6\u011frencisinin epistemik a\u011f\u0131nda bu ba\u011flant\u0131ya katk\u0131da bulunan ifadelerin bir k\u0131sm\u0131n\u0131 g\u00f6stermektedir.<\/span><\/p>\n

\"\"<\/p>\n<\/a> \u015eekil 15.6. Bir \u00fcniversite \u00f6\u011frencisinin epistemik a\u011f\u0131ndaki sosyal sorunlar\u0131n epistemolojisi ile veri bilgisi aras\u0131ndaki ba\u011flant\u0131ya katk\u0131da bulunan sohbet ifadeleri. EAA ara\u00e7 setinde, her bir ifadenin metni, A kodunu mu (k\u0131rm\u0131z\u0131), B kodunu mu (mavi), her ikisini de mi (mor) i\u00e7erir veya hi\u00e7birini (siyah) i\u00e7ermedi\u011fini belirtmek i\u00e7in renklidir.<\/i><\/span><\/span>\n

Metin, sadece birinci kodu i\u00e7eren bo\u015fluklar veya ifadeler k\u0131rm\u0131z\u0131, sadece ikinci kodu i\u00e7erenler mavi, her iki kodu i\u00e7erenler de mor renk ve hi\u00e7bir kodu i\u00e7ermeyenler siyah renkte g\u00f6sterilecek \u015fekilde renklidir. \u201cNihai Teklif Yans\u0131mas\u0131\u201d fikir birimi (etkinlik, gibi), \u00f6rne\u011fin mor renktedir, \u00e7\u00fcnk\u00fc hem E.sosyal.konular hem de K.veri i\u00e7in kodlanan ifadeler i\u00e7erir: birinci (k\u0131rm\u0131z\u0131) ifade, arazi kullan\u0131m de\u011fi\u015fikli\u011fine dayanarak kenti iyile\u015ftirme iste\u011fini gerek\u00e7elendirirken (sosyal sorunlar\u0131n epistemolojisi), ikinci ifade ise imar de\u011fi\u015fikliklerinin atmosferik karbondioksit seviyeleri \u00fczerindeki etkileriyle ilgili bilgileri (veri bilgisi) g\u00f6sterir.<\/span><\/p>\n

\"\"<\/p>\n<\/a> \u015eekil 15.7. \u0130yi teoriye dayal\u0131 \u00f6\u011frenme analiti\u011fi, bir modelin orijinal verilere kar\u015f\u0131 yorumlanmas\u0131n\u0131 do\u011frulamay\u0131 m\u00fcmk\u00fcn k\u0131larak \u201cyorumlay\u0131c\u0131 d\u00f6ng\u00fcy\u00fc kapat\u0131r\u201d.<\/i><\/span><\/span>\n

EAA'n\u0131n bu \u00f6zelli\u011fi yorumlay\u0131c\u0131 d\u00f6ng\u00fcy\u00fc kapatmam\u0131z\u0131 sa\u011flar (bk. \u015eekil 15.7). Kentsel planlama epistemik \u00e7er\u00e7eve \u00f6geleri i\u00e7in kodlanm\u0131\u015f bir veri k\u00fcmesi ile ba\u015flad\u0131k; kodlanm\u0131\u015f verileri, \u00e7er\u00e7eve \u00f6gelerinin birlikte olu\u015fmas\u0131na dayanarak \u00f6\u011frencilerin kentsel planlama d\u00fc\u015f\u00fcncesinin a\u011f modellerini olu\u015fturmak ve g\u00f6rselle\u015ftirmek i\u00e7in kulland\u0131k; o zaman, a\u011f modellerinde ba\u011flant\u0131lar\u0131n herhangi birinin temelini anlamak istiyorsak, orijinal ifadelere geri d\u00f6nebiliriz. B\u00f6ylece EAA, nicel verilerin nitel olarak do\u011frulanabilmesi i\u00e7in nicel verilerin nitel analizini m\u00fcmk\u00fcn k\u0131lar.<\/span><\/p>\n\n

TARTI\u015eMA<\/h2>\n

Bu analizi \u00e7al\u0131\u015f\u0131rken, amac\u0131m\u0131z takip edilesi ideal bir \u00f6rnek sunmak, epistemik \u00e7er\u00e7eve teorisinin di\u011fer \u00f6\u011frenme teorilerine g\u00f6re herhangi bir \u00f6zel analitik avantaj\u0131 oldu\u011funu \u00f6ne s\u00fcrmek de\u011fil, e\u011fitsel veri madencili\u011fi ve \u00f6\u011frenme analiti\u011fi metodolojisinin daha genel bir tart\u0131\u015fmas\u0131 i\u00e7in ba\u011flam sa\u011flamakt\u0131. B\u00fcy\u00fck e\u011fitsel veri k\u00fcmelerinin analizleri daha yayg\u0131n hale geldik\u00e7e, \u201c\u00f6\u011frenmeyi etkileyen kilit fakt\u00f6rleri daha iyi anlamalar\u0131n\u0131 sa\u011flamak i\u00e7in e\u011fitim teorilerini ve iyi bilinen e\u011fitim olaylar\u0131n\u0131 geli\u015ftirmek ve geni\u015fletmek amac\u0131yla\" g\u00f6rg\u00fcl kan\u0131tlar elde etmek \u00f6nemli bir uygulamad\u0131r. (Baker ve Yacef, 2009, s. 7). Ba\u015fka bir deyi\u015fle, teorik bir \u00e7er\u00e7eve de\u011fi\u015fkenlerin se\u00e7ilmesine ve hipotezlerin geli\u015fimine rehberlik eder; bu durum, g\u00f6zlenen olaylar\u0131n neden meydana geldi\u011finin a\u00e7\u0131klanmas\u0131na yol a\u00e7abilir.<\/span><\/p>\n

Yukar\u0131da sunulan \u00e7al\u0131\u015f\u0131lm\u0131\u015f \u00f6rnekte, bir kentsel planlama sim\u00fclasyonunda \u00f6\u011frenen sohbet verisi analizimizi y\u00f6nlendirmek i\u00e7in epistemik \u00e7er\u00e7eve teorisini kulland\u0131k. Epistemik \u00e7er\u00e7eve teorisi, \u00f6\u011frenmenin, \u00f6\u011frencilerin ger\u00e7ek uygulama pratikleri aras\u0131nda yapt\u0131klar\u0131 ba\u011flant\u0131lar\u0131n yap\u0131s\u0131 ile karakterize edilebilece\u011fini \u00f6ne s\u00fcrer. Analitik yakla\u015f\u0131m\u0131m\u0131z olan ENA, a\u011f grafi\u011fi olarak g\u00f6rselle\u015ftirilen \u00f6\u011frenen \u00f6\u011frenme modellerini, ba\u011flant\u0131 \u00f6r\u00fcnt\u00fclerinin matematiksel g\u00f6sterimlerini olu\u015fturmak i\u00e7in s\u00f6ylem verilerini kullan\u0131r. Bu sebeple analiz, \u00f6\u011frenmeyi anlamak i\u00e7in belirli bir teorik yakla\u015f\u0131m\u0131n i\u015flevselle\u015ftirilmesidir.<\/span><\/p>\n

\"\"<\/p>\n<\/a> \u015eekil 15.8. Bir KDDT De\u011ferlendirmesinde Modeller (Mislevy, 2006'dan uyarlanm\u0131\u015ft\u0131r).<\/i><\/span><\/span>\n

Teori, veri ve analiz aras\u0131ndaki ba\u011flant\u0131y\u0131 kavramsalla\u015ft\u0131rman\u0131n bir yolu kan\u0131ta dayal\u0131 tasar\u0131md\u0131r (Mislevy ve Riconscente, 2006; Rupp, Gustha vd., 2010; Shaffer vd., 2009). Kan\u0131t merkezli tasar\u0131mda, analitik bir \u00e7er\u00e7eve birbirine ba\u011fl\u0131 \u00fc\u00e7 modelden olu\u015fur: bir \u00f6\u011frenen modeli, bir kan\u0131t modeli ve bir g\u00f6rev modeli (bk. \u015eekil 15.8; Mislevy, Steinberg ve Almond, 1999; Mislevy, 2006). \u00d6\u011frenci modeli, de\u011ferlendirmek istedi\u011fimiz \u00f6\u011frencinin \u00f6zelliklerini veya daha genel olarak modellemeye veya \u00f6l\u00e7meye \u00e7al\u0131\u015ft\u0131\u011f\u0131m\u0131z sonucu temsil eder. G\u00f6rev modeli, \u00f6\u011frenen modelindeki sonu\u00e7lar\u0131 \u00f6l\u00e7mek i\u00e7in kullan\u0131lacak faaliyetleri ve verileri temsil eder. \u00d6\u011frenci (sonu\u00e7) modeli ve g\u00f6rev (veri) modeli, verilere dayanan \u00e7\u0131kar\u0131mlarla ilgili sonu\u00e7lar\u0131 garanti alt\u0131na almak i\u00e7in kullan\u0131lacak analitik ara\u00e7 ve teknikleri ayr\u0131nt\u0131land\u0131ran bir kan\u0131t modeliyle ba\u011flant\u0131l\u0131d\u0131r.<\/span><\/p>\n

\u00c7al\u0131\u015f\u0131lan \u00f6rnek, \u00f6\u011frenme analiti\u011fine modellerin her birinin (\u00f6\u011frenci, kan\u0131t ve g\u00f6rev) bu durumda, ayn\u0131 kuramsal \u00e7er\u00e7eveden, epistemik \u00e7er\u00e7eve kuram\u0131ndan t\u00fcretildi\u011fi bir yakla\u015f\u0131m\u0131 g\u00f6stermektedir (bk. \u015eekil 15.9).<\/span><\/p>\n

\"\"<\/p>\n<\/a> \u015eekil 15.9. \u00dcniversite \u00f6\u011frencileri (solda), lise \u00f6\u011frencileri (sa\u011fda) ve \u00fcst\u00fcn yetenekli lise \u00f6\u011frencilerinde (ortada) ortalama a\u011f konumlar\u0131 (kareler) ve g\u00fcven aral\u0131klar\u0131 (kutular).<\/i><\/span><\/span>\n

Sonu\u00e7, belirli bir uzmanl\u0131k teorisi taraf\u0131ndan y\u00f6nlendirilen ve g\u00f6rg\u00fcl\/deneysel olarak do\u011frulanan (sim\u00fcle edilmi\u015f) karma\u015f\u0131k problem \u00e7\u00f6zme ba\u011flam\u0131nda uzmanl\u0131\u011f\u0131 analiz etmeye y\u00f6nelik bir yakla\u015f\u0131md\u0131r. Ancak sonu\u00e7lar\u0131n g\u00f6rg\u00fcl\/deneysel esaslar\u0131 ciddi bir \u015fekilde yaln\u0131zca istatistiksel manidarl\u0131\u011fa dayanmamaktad\u0131r: kan\u0131tsal arg\u00fcman\u0131n\u0131n farkl\u0131 modelleri veya katmanlar\u0131 aras\u0131ndaki ba\u011flant\u0131lar nedeniyle, -modelin anlam\u0131n\u0131n- yorumlanmas\u0131ndaki istatistikler orijinal verilerde do\u011frulanabilir.<\/span><\/p>\n

Teoriye dayal\u0131 bir yakla\u015f\u0131m\u0131n veri analizine getirdi\u011fi bu avantajlara ra\u011fmen, bulgular i\u00e7in radikal bir \u015fekilde teorik olmayan bir yakla\u015f\u0131m izleyen \u00e7al\u0131\u015fmalarda \u00f6nemli bir art\u0131\u015f olmu\u015ftur. Wired dergisi ba\u015f edit\u00f6r\u00fc Chris Anderson (2008) b\u00fcy\u00fck veri \u00e7a\u011f\u0131nda teoriye dayal\u0131 soru\u015fturman\u0131n gereksiz oldu\u011funu bile iddia etti. Anderson, \u201cPetabayt [veri] \u015funu s\u00f6ylememize izin veriyor: 'Korelasyon yeterli,'\u201d telkininde bulunuyor. \u201cNeyi g\u00f6sterebilecekleri konusunda hipotezler olmadan verileri analiz edebiliriz. Rakamlar\u0131 d\u00fcnyan\u0131n g\u00f6rd\u00fc\u011f\u00fc en b\u00fcy\u00fck hesaplama k\u00fcmelerine koyabiliriz ve istatistiksel algoritmalar\u0131n bilimin bulamayaca\u011f\u0131 \u00f6r\u00fcnt\u00fcleri bulmas\u0131na izin verebiliriz. \u201d\u00c7o\u011fu bilim insan\u0131n\u0131n nedenselli\u011fin \u00f6nemsiz oldu\u011fu fikrinden derinden rahats\u0131zl\u0131k duyaca\u011f\u0131 ger\u00e7e\u011fine ra\u011fmen, Anderson'un b\u00fcy\u00fck verinin analizine -\u201cilk \u00f6nce matematiksel verileri g\u00f6r\u00fcnt\u00fcleme ve daha sonra bunun i\u00e7in bir ba\u011flam olu\u015fturma\"- yakla\u015f\u0131m\u0131 veri madencili\u011finde yayg\u0131n olarak kullan\u0131lmaktad\u0131r.<\/span><\/p>\n

Tabii ki, yeterince b\u00fcy\u00fck bir veri k\u00fcmesi ve y\u00fczlerce olmasa bile onlarca matematiksel model ile bu verilerin alt\u0131ndan girip \u00fcst\u00fcnden \u00e7\u0131kma becerisi ile istatistiksel olarak anlaml\u0131 \u00f6r\u00fcnt\u00fcler bulunacakt\u0131r. Ancak istatistiksel anlaml\u0131l\u0131k kavramsal ve hatta kullan\u0131labilir bir anlam ifade etmez. Bu geni\u015f veri toplama y\u00f6ntemlerini analiz etmeye y\u00f6nelik t\u00fcm teori temelli yakla\u015f\u0131mlar\u0131n ideal veya hatta de\u011ferli oldu\u011fu anlam\u0131na gelmez. K\u00f6t\u00fc g\u00f6rg\u00fcll\u00fck ve hatta k\u00f6t\u00fc bir \u015fekilde i\u015flevselle\u015ftirilmi\u015f veya uygulanm\u0131\u015f iyi teori oldu\u011fu gibi k\u00f6t\u00fc teori de vard\u0131r. Yukar\u0131daki \u00e7al\u0131\u015f\u0131lan \u00f6rne\u011fin veya daha genel olarak se\u00e7ti\u011fimiz teori ve y\u00f6ntemlerin her ko\u015fulda ideal oldu\u011funu da iddia etmiyoruz.<\/span><\/p>\n

Bizim arg\u00fcman\u0131m\u0131z daha \u00e7ok, b\u00fcy\u00fck e\u011fitsel veri k\u00fcmelerinin analizinde teoriye dayal\u0131 bir yakla\u015f\u0131m benimsemenin belirgin avantajlar\u0131 oldu\u011fu \u015feklindedir. Yukar\u0131daki \u00e7al\u0131\u015fan \u00f6rnek, teori g\u00fcd\u00fcml\u00fc \u00f6\u011frenme analitiklerinde, a\u00e7\u0131k bir teorik \u00e7er\u00e7evenin, bir veri derlemini anlama aray\u0131\u015f\u0131nda ve uygun analitik y\u00f6ntemlerin se\u00e7iminde nas\u0131l yol g\u00f6sterdi\u011fini g\u00f6stermektedir. Veri, teori ve analiz aras\u0131ndaki bu ba\u011flant\u0131lar b\u00f6ylece sonu\u00e7lar\u0131 hassas ve anlaml\u0131 bir \u015fekilde yorumlama becerisi sa\u011flar.<\/span><\/p>\n\n

TE\u015eEKK\u00dcR B\u00d6L\u00dcM\u00dc<\/h2>\n

Bu \u00e7al\u0131\u015fma, k\u0131smen Ulusal Bilim Vakf\u0131 (DRL-0918409, DRL-0946372, DRL-1247262, DRL-1418288, DUE-0919347, DUE-1225885, EEC-1232656, EEC-1340402, REC-0347000) MacArthur Vakf\u0131, Spencer Vakf\u0131, Wisconsin Mezunlar\u0131 Ara\u015ft\u0131rma Vakf\u0131 ve Wisconsin-Madison \u00dcniversitesi Ara\u015ft\u0131rma ve Lisans\u00fcst\u00fc E\u011fitimden Sorumlu Ba\u015fkan Yard\u0131mc\u0131l\u0131\u011f\u0131 Ofisi taraf\u0131ndan finanse edildi. G\u00f6r\u00fc\u015fler, bulgular ve \u00e7\u0131kar\u0131mlar, fon veren kurulu\u015flar\u0131n, i\u015f birli\u011fi yapan kurumlar\u0131n veya di\u011fer ki\u015filerin g\u00f6r\u00fc\u015flerini yans\u0131tmamaktad\u0131r.<\/span><\/p>\n\n

KAYNAK\u00c7A<\/h2>\nAnderson, C. (2008). The end of theory: The data deluge makes the scientific method obsolete. Wired, 16<\/i>(7). https:\/\/www.wired.com\/2008\/06\/pb-theory\/ <\/span><\/span>\n\nAndrist, S., Collier, W., Gleicher, M., Mutlu, B., & Shaffer, D. (2015). Look together: Analyzing gaze coordination with epistemic network analysis. Frontiers in Psychology, 6<\/i>(1016). journal.frontiersin.org\/article\/10.3389\/ fpsyg.2015.01016 \/ pdf <\/span><\/span>\n\nArastoopour, G., Shaffer, D. W., Swiecki, Z., Ruis, A. R., & Chesler, N. C. (2016). Teaching and assessing engineering design thinking with virtual internships and epistemic network analysis. International Journal of Engineering Education, 32<\/i>(2), in press. <\/span><\/span>\n\nAtkinson, R., Derry, S., Renkl, A., & Wortham, D. (2000). Learning from examples: Instructional principles from the worked examples research. Review of Educational Research, 70<\/i>(2), 181\u2013214. <\/span><\/span>\n\nBagley, E. A., & Shaffer, D. W. (2009). When people get in the way: Promoting civic thinking through epistemic game play. International Journal of Gaming and Computer-Mediated Simulations, 1<\/i>(1), 36\u201352. <\/span><\/span>\n\nBagley, E. A., & Shaffer, D. W. (2015a). Learning in an urban and regional planning practicum: The view from educational ethnography. Journal of Interactive Learning Research, 26<\/i>(4), 369\u2013393. <\/span><\/span>\n\nBagley, E. A., & Shaffer, D. W. (2015b). Stop talking and type: Comparing virtual and face-to-face mentoring in an epistemic game. Journal of Computer Assisted Learning, 31<\/i>(6), 606\u2013622. <\/span><\/span>\n\nBaker, R. S. J. d., & Yacef, K. (2009). The state of educational data mining in 2009: A review and future visions. Journal of Educational Data Mining, 1<\/i>(1), 3\u201317. <\/span><\/span>\n\nChesler, N. C., Ruis, A. R., Collier, W., Swiecki, Z., Arastoopour, G., & Shaffer, D. W. (2015). A novel paradigm for engineering education: Virtual internships with individualized mentoring and assessment of engineering thinking. Journal of Biomechanical Engineering, 137<\/i>(2), 024701:1\u20138. <\/span><\/span>\n\nDorogovtsev, S. N., & Mendes, J. F. F. (2013). Evolution of networks: From biological nets to the Internet and WWW<\/i>. Oxford, UK: Oxford University Press. <\/span><\/span>\n\nGee, J. P. (1999). An introduction to discourse analysis: Theory and method<\/i>. London: Routledge. <\/span><\/span>\n\nGoffman, E. (1974). Frame analysis: An essay on the organization of experience<\/i>. Cambridge, MA: Harvard University Press. <\/span><\/span>\n\nGoodwin, C. (1994). Professional vision. American Anthropologist, 96<\/i>(3), 606\u2013633. <\/span><\/span>\n\ni Cancho, R. F., & Sol\u00e9, R. V. (2001). The small world of human language. Proceedings of the Royal Society of London B: Biological Sciences, 268<\/i>(1482), 2261\u20132265. <\/span><\/span>\n\nLandauer, T. K., McNamara, D. S., Dennis, S., & Kintsch, W. (2007). Handbook of latent semantic <\/i>analysis. Mahwah, NJ: Erlbaum. <\/span><\/span>\n\nLave, J., & Wenger, E. (1991). Situated learning: Legitimate peripheral participation<\/i>. Cambridge, MA: Cambridge University Press. <\/span><\/span>\n\nLund, K., & Burgess, C. (1996). Producing high-dimensional semantic spaces from lexical co-occurrence. Behavior Research Methods, Instruments, & Computers, 28<\/i>(2), 203\u2013208. <\/span><\/span>\n\nMislevy, R. J. (2006). Issues of structure and issues of scale in assessment from a situative\/sociocultural perspective<\/i>. CSE Technical Report 668. Los Angeles, CA. <\/span><\/span>\n\nMislevy, R. J., Steinberg, L. S., & Almond, R. G. (1999). Evidence-centered assessment design<\/i>. Educational Testing Service. http:\/\/www.education.umd.edu\/EVMS\/mislevy\/papers\/ECD_overview.html <\/span><\/span>\n\nMislevy, R., & Riconscente, M. M. (2006). Evidence-centered assessment design: Layers, concepts, and terminology. In S. Downing & T. Haladyna (Eds.), Handbook of Test Development <\/i>(pp. 61\u201390). Mahwah, NJ: Erlbaum.<\/span><\/span>\n\nNash, P., Bagley, E. A., & Shaffer, D. W. (2012). Playing for public interest: Epistemic games as civic engagement activities. American Educational Research Association Annual Conference <\/i>(AERA). Vancouver, BC, Canada. <\/span><\/span>\n\nNash, P., & Shaffer, D. W. (2011). Mentor modeling: The internalization of modeled professional thinking in an epistemic game. Journal of Computer Assisted Learning, 27<\/i>(2), 173\u2013189. <\/span><\/span>\n\nNash, P., & Shaffer, D. W. (2012). Epistemic youth development: Educational games as youth development activities. American Educational Research Association Annual Conference <\/i>(AERA). Vancouver, BC, Canada. <\/span><\/span>\n\nNash, P., & Shaffer, D. W. (2013). Epistemic trajectories: Mentoring in a game design practicum. Instructional Science<\/i>, 41(4), 745\u2013771. <\/span><\/span>\n\nNewman, M. E. J. (2004). Analysis of weighted networks. Physical Review E, 70<\/i>(5), 56131. <\/span><\/span>\n\nRohde, M., & Shaffer, D. W. (2004). Us, ourselves and we: Thoughts about social (self-) categorization. Association for Computing Machinery (ACM) SigGROUP Bulletin, 24<\/i>(3), 19\u201324. <\/span><\/span>\n\nRupp, A. A., Sweet, S., & Choi, Y. (2010). Modeling learning trajectories with epistemic network analysis: A simulation-based investigation of a novel analytic method for epistemic games. In R. S. J. d. Baker, A. Merceron, P. I. Pavlik Jr. (Eds.), Proceedings of the 3rd International Conference on Educational Data Mining <\/i>(EDM2010), 11\u201313 June 2010, Pittsburgh, PA, USA (pp. 319\u2013320). International Educational Data Mining Society. <\/span><\/span>\n\nShaffer, D.W. (2004). Epistemic frames and islands of expertise: Learning from infusion experiences. Proceedings of the 6th International Conference of the Learning Sciences <\/i>(ICLS 2004): Embracing Diversity in the Learning Sciences<\/i>, 22\u201326 June 2004, Santa Monica, CA, USA (pp. 473\u2013480). Mahwah, NJ: Lawrence Erlbaum. <\/span><\/span>\n\nShaffer, D. W. (2006). Epistemic frames for epistemic games. Computers and Education<\/i>, 46(3), 223\u2013234. <\/span><\/span>\n\nShaffer, D. W. (2007). How computer games help children learn<\/i>. New York: Palgrave Macmillan. <\/span><\/span>\n\nShaffer, D. W. (2012). Models of situated action: Computer games and the problem of transfer. In C. Steinkuehler, K. D. Squire, & S. A. Barab (Eds.), Games, learning, and society: Learning and meaning in the digital age <\/i>(pp. 403\u2013431). Cambridge, UK: Cambridge University Press. <\/span><\/span>\n\nShaffer, D. W., Collier, W., & Ruis, A. R. (2016). A tutorial on epistemic network analysis: Analyzing the structure of connections in cognitive, social, and interaction data. Journal of Learning Analytics, 3<\/i>(3), 9\u201345. <\/span><\/span>\n\nShaffer, D. W., Hatfield, D. L., Svarovsky, G. N., Nash, P., Nulty, A., Bagley, E. A., \u2026 Frank, K. (2009). Epistemic Network Analysis: A prototype for 21st century assessment of learning. International Journal of Learning and Media, 1<\/i>(1), 1\u201321. <\/span><\/span>\n\nSvarovsky, G.N. (2011). Exploring complex engineering learning over time with epistemic network analysis. Journal of Pre-College Engineering Education Research, 1<\/i>(2), 19\u201330. <\/span><\/span>\n\nTannen, D. (1993). Framing in discourse<\/i>. Oxford, UK: Oxford University Press. <\/span><\/span>\n\nWise, A. F., & Shaffer, D. W. (2016). Why theory matters more than ever in the age of big data. Journal of Learning Analytics, 2(2), 5\u201313.<\/span><\/span>\n\n
\n\n1<\/a> \u00c7evirenin notu: Yazar Aldoux Huxley\u2019in Cesur Yeni D\u00fcnya isimli kitab\u0131na at\u0131fta bulunuyor.<\/span><\/span>\n
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2<\/a> orj. a priori<\/span><\/span><\/p>\n\n<\/div>\n

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3<\/a> orj. Stanza<\/span><\/span><\/p>\n\n<\/div>\n

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4<\/a> Elbette, \u00e7ok farkl\u0131 ba\u011flant\u0131 yap\u0131lar\u0131na sahip iki a\u011f\u0131n benzer k\u00fctle merkezini payla\u015fmas\u0131 m\u00fcmk\u00fcnd\u00fcr. \u00d6rne\u011fin, \u00e7ok say\u0131da ba\u011flant\u0131ya sahip bir a\u011f, men\u015fei\/ kaynak yak\u0131n\u0131nda bir k\u00fctle merkezini i\u00e7erebilir; ancak ayn\u0131 \u015fey, en sa\u011fda ve n solda yaln\u0131zca birka\u00e7 ba\u011flant\u0131 bulunan bir a\u011f i\u00e7in de ge\u00e7erlidir. Belli ba\u015fl\u0131 baz\u0131 nedenlerden \u00f6t\u00fcr\u00fc, boyutsal bir k\u00fc\u00e7\u00fcltmedeki hi\u00e7bir \u00f6zet istatistik orijinal a\u011f\u0131n t\u00fcm bilgilerini koruyamaz.<\/span><\/span><\/p>\n\n<\/div>\n","rendered":"

David Williamson Shaffer ve A. R. Ruis<\/span><\/span><\/p>\n

Wisconsin E\u011fitim Ara\u015ft\u0131rmalar\u0131 Merkezi, Wisconsin \u00dcniversitesi, Madison, ABD<\/span><\/span><\/p>\n

DOI: 10.18608\/hla17.015<\/span><\/span><\/p>\n

\u00d6Z<\/h2>\n

Bu makalede, bir e\u011fitsel oyun ba\u011flam\u0131nda \u00f6\u011frenme analiti\u011finin teori temelli bir yakla\u015f\u0131m\u0131n \u00e7al\u0131\u015f\u0131lm\u0131\u015f bir \u00f6rne\u011fini sunuyoruz. Bunu, di\u011ferlerinin taklit etti\u011fi ideal bir \u00e7\u00f6z\u00fcm sunmak i\u00e7in de\u011fil; veri odakl\u0131 bir yakla\u015f\u0131mdan ziyade teori temelli yakla\u015f\u0131m\u0131n sa\u011flay\u0131c\u0131l\u0131\u011f\u0131n\u0131 ara\u015ft\u0131rmak i\u00e7in yap\u0131yoruz. Bunu, 1) \u00f6\u011frenmenin kavramsalla\u015ft\u0131r\u0131lmas\u0131na bir yakla\u015f\u0131m olarak epistemik \u00e7er\u00e7eve teorisini sunarak; 2) epistemik \u00e7er\u00e7eve teorisine dayanan e\u011fitsel oyun tasar\u0131m\u0131na bir yakla\u015f\u0131m olan epistemik bir oyundan elde edilen veriler ve 3) epistemik a\u011f analizi (EAA), ayn\u0131 teoriye dayanan karma\u015f\u0131k d\u00fc\u015f\u00fcnmenin kan\u0131t\u0131 i\u00e7in s\u00f6ylem ve di\u011fer verileri analiz etme tekni\u011fi olarak sunuyoruz. EAA’y\u0131 belirli bir analitik sonu\u00e7 ile tan\u0131ml\u0131yoruz ancak amac\u0131m\u0131z bu sonucun \u00f6\u011frenme analiti\u011fi alan\u0131nda bizim kilit “en iyi uygulama” olarak d\u00fc\u015f\u00fcnd\u00fc\u011f\u00fcm\u00fcz \u015feyi nas\u0131l \u00f6rnekledi\u011fini ara\u015ft\u0131rmakt\u0131r.<\/span><\/span><\/p>\n

Anahtar Kelimeler<\/span>: Epistemik \u00e7er\u00e7eve teorisi, epistemik oyun, epistemik a\u011f analizi (EAA), kan\u0131t merkezli tasar\u0131m<\/span><\/span><\/p>\n

Bu b\u00f6l\u00fcmde, kuram\u0131n \u00f6\u011frenme analiti\u011findeki rol\u00fcne bak\u0131yoruz. \u00d6\u011frenmeyi inceleyen ara\u015ft\u0131rmac\u0131lar, ister son derece \u00e7ok say\u0131daki ki\u015fi hakk\u0131ndaki bilgi veya ister \u00f6\u011frenme s\u00fcrecinde mikroskobik, anl\u0131k eylemleri g\u00f6steren veriler olsun, e\u015fi benzeri g\u00f6r\u00fclmemi\u015f miktarlarda veri ile kutsanm\u0131\u015flard\u0131r. Bu cesur yeni d\u00fcnyad\u0131r1<\/a><\/sup>. \u00d6\u011frencilerin dikkatlerinin yo\u011funla\u015ft\u0131rd\u0131klar\u0131 yere saniye saniye bakabilir veya KA\u00c7D’lerdeki binlerce \u00f6\u011frenciyi inceleyerek hangi t\u00fcr \u00e7al\u0131\u015fma becerilerinin etkili oldu\u011funu inceleyebiliriz. Wise ve Shaffer (2016)’\u0131n, \u00d6\u011frenme Analiti\u011fi Dergisi<\/i><\/span>nin \u00f6zel bir b\u00f6l\u00fcm\u00fcnde belirtti\u011fi gibi, yeterli bilgi varsa verinin kendi ad\u0131na konu\u015fabilece\u011fini yani, \u00f6\u011frenme teorileri olmadan \u00f6\u011frenme analizleri yapabilece\u011fimizi d\u00fc\u015f\u00fcnmek tehlikelidir. Esasen, bunun tam tersi do\u011frudur. Daha b\u00fcy\u00fck miktarda veri ile teori, analizde daha da hassas bir rol oynar. Basit bir ifadeyle belirtmek gerekirse, belirli boyut ve t\u00fcrdeki veri k\u00fcmeleri i\u00e7in en g\u00fcncel istatistiksel ara\u00e7lar geli\u015ftirilmi\u015ftir: rastgele etkilerin normal da\u011f\u0131l\u0131m\u0131 i\u00e7in yeterince b\u00fcy\u00fck ancak geleneksel veri toplama teknikleri kullan\u0131larak elde edilecek kadar k\u00fc\u00e7\u00fck. Bu teknikleri, g\u00fc\u00e7l\u00fc bir teorik temele sahip olmayan b\u00fcy\u00fckl\u00fc\/boyut s\u0131ras\u0131 daha uzun olan ve de\u011fi\u015fken say\u0131s\u0131 bak\u0131m\u0131ndan daha b\u00fcy\u00fck olan veri k\u00fcmelerine uygulamak en iyi ihtimalle tehlikelidir.<\/span><\/p>\n

Sonras\u0131nda, bu soruya istatisti\u011fin uygulama problemlerini teorik bir \u00e7er\u00e7eve olmadan analiz ederek bakm\u0131yoruz. Wise ve Shaffer\u2019\u0131n \u00f6nerdi\u011fi -ve \u00d6\u011frenme Analiti\u011fi Dergisi<\/i><\/span>‘nin \u00f6zel b\u00f6l\u00fcm\u00fcndeki makale ve yorumlar\u0131n bize g\u00f6sterdi\u011fi \u015fey- teoriye dayal\u0131 \u00f6\u011frenme analiti\u011fi y\u00fcr\u00fctmenin zor oldu\u011fudur. Sonu\u00e7 olarak, neyin takip edece\u011fi ile ilgili yakla\u015f\u0131m\u0131m\u0131z, \u00e7al\u0131\u015fan bir \u00f6rnek kullanarak \u00f6\u011frenme analiti\u011fi teorisinin rol\u00fcn\u00fc incelemektir; \u00f6rnek olarak bir problemin sunumu ve \u00e7\u00f6z\u00fcm\u00fcn\u00fcn ad\u0131m ad\u0131m a\u00e7\u0131klamas\u0131 (Atkinson, Derry, Renkl ve Wortham, 2000) verilebilir.<\/span><\/p>\n

Bunu yaparken amac\u0131m\u0131z, ba\u015fkalar\u0131na taklit edecek ideal bir \u00e7\u00f6z\u00fcm sunmak veya bizim teoriyi \u00f6\u011frenme analiti\u011finde belli bir \u015fekilde kullanmamam\u0131z\u0131n di\u011ferlerinden daha iyi oldu\u011funu ortaya koymak de\u011fildir. Daha \u00e7ok, hedefimiz, b\u00fcy\u00fck e\u011fitsel veri k\u00fcmelerinin analizine teorik temelli -veri odakl\u0131 ya da teori temelli olmayan bir yakla\u015f\u0131m\u0131n aksine- bir yakla\u015f\u0131m\u0131n \u00f6nemini yans\u0131tmakt\u0131r. Bunu yeni bir \u00f6\u011frenme analiti\u011fi tekni\u011fi olan epistemik a\u011f analizini sunarak (EAA; Andrist, Collier, Gleicher, Mutlu ve Shaffer, 2015; Arastoopour, Shaffer, Swiecki, Ruis ve Chesler, 2016; Chesler vd., 2015; Nash ve Shaffer, 2013; Rupp, Gustha, Mislevy ve Shaffer, 2010; Rupp, Sweet ve Choi, 2010; Shaffer vd., 2009; Shaffer, Collier ve Ruis, 2016; Svarovsky, 2011) yap\u0131yoruz. Fakat daha da \u00f6nemlisi, EAA’n\u0131n dayand\u0131\u011f\u0131 \u00f6\u011frenme yakla\u015f\u0131m\u0131 olan epistemik \u00e7er\u00e7eve teorisi<\/i><\/span> ba\u011flam\u0131nda sunuyoruz ve onu epistemik \u00e7er\u00e7eve teorisine dayanan e\u011fitsel oyun tasar\u0131m\u0131na bir yakla\u015f\u0131m olarak bir epistemik oyuna uyguluyoruz. Bu nedenle, EAA’y\u0131 sonucun teori, veri ve analizin uyumlanmas\u0131n\u0131 nas\u0131l alandaki \u201cen iyi uygulama\u201d olarak \u00f6rneklendirdi\u011fini incelemek amac\u0131yla belirli bir analitik sonu\u00e7 yoluyla tan\u0131ml\u0131yoruz.<\/span><\/p>\n

VER\u0130<\/h2>\n

Bu \u00e7al\u0131\u015fan belirli \u00f6rne\u011fi incelemek i\u00e7in kullanaca\u011f\u0131m\u0131z veriler, \u00f6\u011frencilerin uzmanlar gibi d\u00fc\u015f\u00fcnmelerini \u00f6\u011frenmelerine yard\u0131mc\u0131 olan otantik bir profesyonel uygulama sim\u00fclasyonu olan epistemik bir oyundan gelmektedir (Shaffer, 2006, 2007). \u00d6zel olarak, veriler, \u00f6\u011frencilerin stajyer rol\u00fcn\u00fc \u00fcstlendikleri Lowell, Massachusetts kentindeki hayali bir firmada bir yeniden geli\u015ftirme s\u00f6zle\u015fmesi i\u00e7in rekabet ettikleri \u00e7evrimi\u00e7i bir kentsel planlama sim\u00fclasyonu olan bir epistemik oyun Land Science’dan geliyor. \u015eehri farkl\u0131 payda\u015f gruplar\u0131n\u0131n taleplerini kar\u015f\u0131layan farkl\u0131 bir kullan\u0131m i\u00e7in tahsis eden yeni bir plan geli\u015ftirmek i\u00e7in sohbet ve e-posta yoluyla ileti\u015fim kuran k\u00fc\u00e7\u00fck ekiplerde \u00e7al\u0131\u015f\u0131yorlar. Bunu yapmak i\u00e7in, \u00f6\u011frenciler ara\u015ft\u0131rma \u00f6zetlerini ve di\u011fer kaynaklar\u0131 g\u00f6zden ge\u00e7irir, payda\u015f tercihleri hakk\u0131nda bir anket yaparlar ve arazi kullan\u0131m\u0131 de\u011fi\u015fikliklerinin kirlilik, gelir, bar\u0131nma ve GIS haritalama arac\u0131 kullanarak di\u011fer g\u00f6stergeler \u00fczerindeki etkilerini modelleyebilirler. Hi\u00e7bir farkl\u0131 kullan\u0131m tahsis plan\u0131 t\u00fcm payda\u015f tercihlerini yerine getiremeyece\u011finden, \u00f6\u011frenciler nihai tekliflerinde verdikleri kararlar\u0131 gerek\u00e7elendirmelidir.<\/span><\/p>\n

Land Science, lise \u00f6\u011frencileri ve \u00fcniversite birinci s\u0131n\u0131f \u00f6\u011frencileri ile 30’dan fazla kez kullan\u0131lm\u0131\u015ft\u0131r. \u00d6nceki ara\u015ft\u0131rmam\u0131z (Bagley ve Shaffer, 2009, 2015b; Nash, Bagley ve Shaffer, 2012; Nash ve Shaffer, 2012; Shaffer, 2007), Land Science’\u0131n \u00f6\u011frencilerin kentsel ekoloji, kentsel planlama ve ilgili alanlarda i\u00e7erik ve uygulamalar\u0131 \u00f6\u011frenmelerine yard\u0131mc\u0131 oldu\u011funu ve ayr\u0131ca okuldaki performans\u0131 iyile\u015ftirmek i\u00e7in beceriler, ilgi alanlar\u0131 ve motivasyon geli\u015ftirmelerine yard\u0131mc\u0131 oldu\u011funu g\u00f6stermi\u015ftir.<\/span><\/p>\n

Pek \u00e7ok e\u011fitim teknolojisinde oldu\u011fu gibi, Land Science, sohbet s\u0131ras\u0131nda, e-postalar\u0131nda, not defterlerinde, di\u011fer i\u015f \u00fcr\u00fcnlerinde, her tu\u015f bas\u0131\u015f\u0131nda ve fare t\u0131klatmas\u0131 d\u00e2hil olmak \u00fczere, sim\u00fclasyon s\u0131ras\u0131nda \u00f6\u011frencilerin yapt\u0131klar\u0131 her \u015feyi kaydeder. Bu sadece \u00f6\u011frencilerin nihai \u00fcr\u00fcnlerini de\u011fil ayn\u0131 zamanda kulland\u0131klar\u0131 problem \u00e7\u00f6zme s\u00fcre\u00e7lerini de analiz etmeyi m\u00fcmk\u00fcn k\u0131lar.<\/span><\/p>\n

A\u015fa\u011f\u0131da verilen \u00e7al\u0131\u015f\u0131lm\u0131\u015f \u00f6rnekte, Land Science’\u0131n ayn\u0131 s\u00fcr\u00fcm\u00fcn\u00fc kullanan yedi \u00fcniversite \u00f6\u011frencisi grubu (n = 155), sekiz lise \u00f6\u011frencisi grubunu (n = 110) ve \u00fc\u00e7 grup \u00fcst\u00fcn yetenekli ve yetenekli lise \u00f6\u011frencisi (n = 46) d\u00e2hil olmak \u00fczere 311 \u00f6\u011frencini sohbetlerini inceliyoruz. Bu veri k\u00fcmesi b\u00fct\u00fcn\u00fcyle 44.964 sohbet sat\u0131r\u0131n\u0131 i\u00e7eriyor.<\/span><\/p>\n

KURAM<\/h2>\n

Land Sciencedan gelen sohbet verisi analizimiz epistemik \u00e7er\u00e7eve teorisi taraf\u0131ndan bilgilendirilmektedir (Shaffer, 2004, 2006, 2007, 2012). Epistemik \u00e7er\u00e7eve teorisi, bir uygulama toplulu\u011funun d\u00fcnyadaki d\u00fc\u015f\u00fcnme, hareket etme ve olma yollar\u0131n\u0131 modellemektedir (Lave ve Wenger, 1991; Rohde ve Shaffer, 2004). Sorunlar\u0131 \u00e7er\u00e7evelemek, ara\u015ft\u0131rmak ve \u00e7\u00f6zmek i\u00e7in ortak bir yakla\u015f\u0131ma sahip bir uygulama toplulu\u011fu veya bir grup insan, bir bilgi ve beceri repertuar\u0131na, beceri ve bilginin nas\u0131l kullan\u0131lmas\u0131 gerekti\u011fini y\u00f6nlendiren bir de\u011ferler dizisine ve kararlar almak ve do\u011frulamak i\u00e7in bir dizi s\u00fcrece sahiptir. Bir toplulu\u011fun hem a\u00e7\u0131k belirte\u00e7lerle hem de toplulu\u011fun karakteristik becerilerinin, de\u011ferlerinin ve karar alma s\u00fcre\u00e7lerinin \u00e7\u0131kar\u0131lmas\u0131 yoluyla sergilenen ortak bir kimli\u011fi de vard\u0131r.<\/span><\/p>\n

Bir uygulama toplulu\u011funun par\u00e7as\u0131 olmak, ba\u015fka bir deyi\u015fle, belirli bir S\u00f6ylem edinmek demektir : bir \u201ckonu\u015fma, dinleme, yazma, okuma, hareket etme, etkile\u015fim kurma, inanma, de\u011fer verme ve hissetme” yolu (ve \u00e7e\u015fitli nesneler, semboller, g\u00f6r\u00fcnt\u00fcler ara\u00e7lar ve teknolojiler kullanma) \u201d(Gee, 1999, s. 719). Bir S\u00f6ylem, bir k\u00fclt\u00fcr\u00fcn tezah\u00fcr\u00fcd\u00fcr ve Goodwin\u2019in (1994) profesyonel g\u00f6r\u00fc\u015f\u00fcne dayanarak, epistemik bir \u00e7er\u00e7eve bir S\u00f6ylemin dil bilgisidir: belirli bir uygulama toplulu\u011funun \u00fcyeleri taraf\u0131ndan sergilenen S\u00f6ylem \u00f6gelerinin yap\u0131land\u0131rmas\u0131n\u0131n resm\u00ee a\u00e7\u0131klamas\u0131d\u0131r.<\/span><\/p>\n

Ancak \u00f6nemli olarak, bir toplulu\u011fun epistemik \u00e7er\u00e7evesini niteleyen ilgili bilgi, beceri, de\u011ferler, uygulamalar ve di\u011fer nitelikler de\u011fil; onlar\u0131n belirli bir \u015fekilde ayarlan\u0131p yap\u0131land\u0131r\u0131lmas\u0131d\u0131r. Bir \u00e7er\u00e7eve kavram\u0131 Goffman’dan (1974) gelmektedir (ayr\u0131ca bk. Tannen, 1993). Etkinlik, \u00e7er\u00e7eve olarak yorumlan\u0131r: alg\u0131lar\u0131 ve eylemleri \u015fekillendiren kurallar ve g\u00f6r\u00fc\u015fler ya da deneyimlerin yorumland\u0131\u011f\u0131 normlar ve uygulamalar dizisi. B\u00f6ylece, epistemik bir \u00e7er\u00e7eve, otantik g\u00f6revlerle (veya otantik g\u00f6revlerin sim\u00fclasyonlar\u0131na) ilgilenen bir bireyin eylemleri ve etkile\u015fimleri ile ortaya \u00e7\u0131kar.<\/span><\/p>\n

Epistemik bir \u00e7er\u00e7eveyi olu\u015fturan unsurlar aras\u0131ndaki ba\u011flant\u0131lar\u0131 analitik olarak tan\u0131mlamak i\u00e7in, \u00f6\u011frencilerin s\u00f6ylemindeki e\u015f olu\u015fumlar\u0131<\/i><\/span> -bu durumda \u00e7evrimi\u00e7i bir sohbet program\u0131nda yap\u0131lan konu\u015fmalarda tespit ederiz. Ara\u015ft\u0131rmac\u0131lar (Chesler vd., 2015; Dorogovtsev ve Mendes, 2013; i Cancho ve Sole, 2001; Landauer, McNamara, Dennis ve Kintsch, 2007; Lund ve Burgess, 1996) \u00f6zellikle de e\u015f olu\u015fumlar s\u0131k oldu\u011funda belirli bir s\u00f6ylem verisi dilimindeki kavramlar\u0131n e\u015f olu\u015fumlar\u0131n\u0131n bili\u015fsel ba\u011flant\u0131lar\u0131n iyi bir g\u00f6stergesi oldu\u011funu tespit etmi\u015flerdir (Newman, 2004). Bu kavramlar, teorik ya da g\u00f6rg\u00fcl\/ deneysel bir analizden ya da eylem halindeki toplulu\u011fun etnografik bir \u00e7al\u0131\u015fmas\u0131ndan olay \u00f6ncesi2<\/a><\/sup> duruma dayal\u0131 olarak tan\u0131mlanabilir.<\/span><\/p>\n

EAA, s\u00f6ylem verilerinin b\u00f6l\u00fcmlerindeki e\u015f olu\u015fumlar\u0131 tespit ederek ve e\u015f olu\u015fumlar\u0131n a\u011f\u0131rl\u0131kl\u0131 yap\u0131s\u0131n\u0131 modelleyerek epistemik \u00e7er\u00e7eve teorisini i\u015fler hale getirir. EAA zaman i\u00e7inde epistemik bir \u00e7er\u00e7evenin g\u00fcc\u00fcndeki ve kompozisyonundaki de\u011fi\u015fiklikleri \u00f6l\u00e7en dinamik bir a\u011f modelinde bu ortak olu\u015fum \u00f6r\u00fcnt\u00fclerini temsil eder- bir sonraki b\u00f6l\u00fcmde a\u00e7\u0131klayaca\u011f\u0131m\u0131z bir s\u00fcre\u00e7 olarak tan\u0131mlar\u0131z.<\/span><\/p>\n

EAA<\/h2>\n

EAA, ba\u011flant\u0131 verilerinin a\u011f\u0131rl\u0131kl\u0131 yap\u0131s\u0131n\u0131 s\u00f6ylem verilerinde veya herhangi bir d\u00f6rtl\u00fck3<\/a><\/sup> temelli etkile\u015fim verilerinde modeller. Daha sonra, EAA y\u00f6nteminin genel prensiplerini ve EAA yaz\u0131l\u0131m\u0131n\u0131n g\u00fcncel versiyonunun www.epistemicnetwork.org<\/span>‘un EAA algoritmalar\u0131n\u0131 uygulad\u0131\u011f\u0131<\/i><\/span> spesifik s\u00fcreci a\u00e7\u0131kl\u0131yoruz.<\/span><\/p>\n

Fikir Birimleri Tabanl\u0131 Etkile\u015fim Verileri<\/h3>\n

EAA’n\u0131n epistemik \u00e7er\u00e7eve teorisini nas\u0131l i\u015fletti\u011fini a\u00e7\u0131klamadan \u00f6nce, verilerin EAA kullan\u0131larak analiz i\u00e7in nas\u0131l yap\u0131land\u0131r\u0131ld\u0131\u011f\u0131n\u0131 anlamak \u00f6nemlidir. Land Science’de bir grup \u00f6\u011frenci taraf\u0131ndan yap\u0131lan iki konu\u015fmadan al\u0131nt\u0131lar\u0131 g\u00f6steren Tablo 15.1’deki basitle\u015ftirilmi\u015f verilere dikkat edin. Sa\u011fdaki be\u015f s\u00fctunda, birliktelik \u00f6r\u00fcnt\u00fcs\u00fcn\u00fc modellemek istedi\u011fimiz kavramlar ya da kodlar vard\u0131r. Bu durumda, kodlar, bir kentsel planlama epistemik \u00e7er\u00e7evesinin \u00e7e\u015fitli unsurlar\u0131 olan profesyonel \u015fehir planlama prati\u011finin \u00e7e\u015fitli y\u00f6nlerini temsil eder.<\/span><\/p>\n

Bazen, Jorge’nin hem sosyal hem de \u00e7evresel konular hakk\u0131ndaki bilgileri referans ald\u0131\u011f\u0131 Sat\u0131r 3 ‘te oldu\u011fu gibi, kodlar aras\u0131ndaki ili\u015fkileri tek bir ifadede g\u00f6rebilece\u011fimizi unutmay\u0131n. Di\u011fer durumlarda, ifadeler aras\u0131nda ili\u015fkiler ortaya \u00e7\u0131kar: Sat\u0131r 10’da Depesh, Natalie’nin Sat\u0131r 8’deki feragat hakk\u0131ndaki daha genel bir yorumuna cevap veren ve a\u00e7\u0131k alan\u0131n artmas\u0131yla ilgili olarak bunun \u00fczerine dayand\u0131rd\u0131\u011f\u0131 feragatten bahseder. Ancak her konu\u015fma s\u0131ras\u0131 aras\u0131nda kodlar aras\u0131ndaki ili\u015fkilere bakmak istemeyebiliriz. \u00d6rne\u011fin, iki ayr\u0131 konu\u015fma Tablo 15.1’de g\u00f6sterilmektedir. Her ikisi de ayn\u0131 \u00f6\u011frenci grubunu (Grup 3) i\u00e7erir ancak \u00f6\u011frenciler iki farkl\u0131 etkinlik \u00fczerinde \u00e7al\u0131\u015f\u0131rken konu\u015fmalar iki farkl\u0131 g\u00fcnde ger\u00e7ekle\u015fmi\u015ftir.<\/span><\/p>\n

Bu verilerin bir a\u011f modelini olu\u015fturmak i\u00e7in, sat\u0131rlar\u0131 fikir birimlerine g\u00f6re gruplamam\u0131z gerekir. Bu fikir biriminin arkas\u0131ndaki ana fikir, (a) ayn\u0131 fikir birimi i\u00e7indeki herhangi bir sat\u0131rdaki kodlar\u0131n modelde birbirleriyle ili\u015fkili oldu\u011fu ve (b) ayn\u0131 fikir biriminde olmayan sat\u0131rlardaki kodlar\u0131n, modelde birbirleriyle ili\u015fkili olmad\u0131\u011f\u0131d\u0131r. Bu durumda, fikir birimleri hangi kavram birlikteliklerinin kent planlamas\u0131n\u0131n epistemik \u00e7er\u00e7eve unsurlar\u0131 aras\u0131nda anlaml\u0131 bili\u015fsel ba\u011flant\u0131lar\u0131 temsil etti\u011fini g\u00f6stermektedir.<\/span><\/p>\n

<\/a><\/a><\/a><\/a><\/a><\/p>\n

Tablo 15.1. EAA Format\u0131nda Kodlanan S\u00f6ylem Verilerinin D\u00fczenlenmi\u015f Al\u0131nt\u0131lar\u0131<\/i><\/span><\/span><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n<\/colgroup>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
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Sat\u0131r<\/b><\/span><\/p>\n<\/td>\n

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Etkinlik<\/b><\/span><\/p>\n<\/td>\n

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Grup<\/b><\/span><\/p>\n<\/td>\n

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Kullan\u0131c\u0131 ad\u0131<\/b><\/span><\/p>\n<\/td>\n

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Olu\u015fturma<\/b><\/span><\/p>\n<\/td>\n

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\u0130fade<\/b><\/span><\/p>\n<\/td>\n

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E.Sosyal.Kullan\u0131m<\/b><\/span><\/p>\n<\/td>\n

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S.imar.kodlar\u0131<\/b><\/span><\/p>\n<\/td>\n

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K.sosyal.konular<\/b><\/span><\/p>\n<\/td>\n

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K.imar.kodlar\u0131<\/b><\/span><\/p>\n<\/td>\n

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K.ortam<\/b><\/span><\/p>\n<\/td>\n<\/tr>\n<\/thead>\n

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1<\/span><\/p>\n<\/td>\n

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VSV Toplant\u0131s\u0131<\/span><\/p>\n<\/td>\n

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3<\/span><\/p>\n<\/td>\n

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Natalie<\/span><\/p>\n<\/td>\n

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02\/11\/14 10:03<\/span><\/p>\n<\/td>\n

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Tamam, payda\u015flar ne istiyor?<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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2<\/span><\/p>\n<\/td>\n

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VSV Toplant\u0131s\u0131<\/span><\/p>\n<\/td>\n

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3<\/span><\/p>\n<\/td>\n

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Depesh<\/span><\/p>\n<\/td>\n

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02\/11\/14 10:03<\/span><\/p>\n<\/td>\n

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w \/ payda\u015flarla konu\u015furken, \u015fehir i\u00e7inde bir\u00e7ok sorun oldu\u011funu \u00f6\u011frendik, ancak bu sorunlar\u0131n kolayca \u00e7\u00f6z\u00fclmesini engelleyen baz\u0131 engeller var<\/span><\/p>\n<\/td>\n

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VSV Toplant\u0131s\u0131<\/span><\/p>\n<\/td>\n

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3<\/span><\/p>\n<\/td>\n

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Jorge<\/span><\/p>\n<\/td>\n

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02\/11\/14 10:04<\/span><\/p>\n<\/td>\n

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Evet, payda\u015flar b\u00f6lgedeki \u00e7evresel etkilerin yan\u0131 s\u0131ra d\u00fc\u015f\u00fck gelirli konut ihtiyac\u0131na da \u00f6nem veriyor<\/span><\/p>\n<\/td>\n

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1<\/span><\/p>\n<\/td>\n<\/tr>\n

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4<\/span><\/p>\n<\/td>\n

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VSV Toplant\u0131s\u0131<\/span><\/p>\n<\/td>\n

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3<\/span><\/p>\n<\/td>\n

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Depesh<\/span><\/p>\n<\/td>\n

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02\/11\/14 10:04<\/span><\/p>\n<\/td>\n

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farkl\u0131 konular\u0131 \u00f6nemsiyorlard\u0131 ama hepsi sa\u011fl\u0131kl\u0131 ve ya\u015fanabilir bir topluluk yaratmak istiyorlard\u0131<\/span><\/p>\n<\/td>\n

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5<\/span><\/p>\n<\/td>\n

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VSV Toplant\u0131s\u0131<\/span><\/p>\n<\/td>\n

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3<\/span><\/p>\n<\/td>\n

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Natalie<\/span><\/p>\n<\/td>\n

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02\/11\/14 10:05<\/span><\/p>\n<\/td>\n

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Kat\u0131l\u0131yorum. Ayr\u0131ca suyun kalitesi i\u00e7in endi\u015feleniyorlar.<\/span><\/p>\n<\/td>\n

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6<\/span><\/p>\n<\/td>\n

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VSV Toplant\u0131s\u0131<\/span><\/p>\n<\/td>\n

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3<\/span><\/p>\n<\/td>\n

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Jessie<\/span><\/p>\n<\/td>\n

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02\/11\/14 10:06<\/span><\/p>\n<\/td>\n

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ve d\u00fc\u015f\u00fck gelirli sakinler i\u00e7in daha fazla konut f\u0131rsat\u0131 istiyorlar<\/span><\/p>\n<\/td>\n

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7<\/span><\/p>\n<\/td>\n

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iPlan Toplant\u0131s\u0131<\/span><\/p>\n<\/td>\n

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3<\/span><\/p>\n<\/td>\n

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Jorge<\/span><\/p>\n<\/td>\n

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02\/13\/14 10:21<\/span><\/p>\n<\/td>\n

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H\u0131zl\u0131 soru, P g\u00f6stergesinin anlam\u0131 nedir?<\/span><\/p>\n<\/td>\n

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iPlan Toplant\u0131s\u0131<\/span><\/p>\n<\/td>\n

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3<\/span><\/p>\n<\/td>\n

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Natalie<\/span><\/p>\n<\/td>\n

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02\/13\/14 10:21<\/span><\/p>\n<\/td>\n

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Belirli sitelerin imar tan\u0131mlar\u0131n\u0131 de\u011fi\u015ftirirken belirli g\u00f6stergelerin de\u011fi\u015fti\u011fini buldum. \u0130mar kategorisindeki her de\u011fi\u015fiklik, faydalar\u0131 ve sak\u0131ncalar\u0131 ile geldi. Genelde bir feragat durumu vard\u0131.<\/span><\/p>\n<\/td>\n

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9<\/span><\/p>\n<\/td>\n

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iPlan Toplant\u0131s\u0131<\/span><\/p>\n<\/td>\n

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3<\/span><\/p>\n<\/td>\n

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Jessie<\/span><\/p>\n<\/td>\n

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02\/13\/14 10:21<\/span><\/p>\n<\/td>\n

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@Jorge: P = fosforlu<\/span><\/p>\n<\/td>\n

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10<\/span><\/p>\n<\/td>\n

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iPlan Toplant\u0131s\u0131<\/span><\/p>\n<\/td>\n

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3<\/span><\/p>\n<\/td>\n

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Depesh<\/span><\/p>\n<\/td>\n

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02\/13\/14 10:22<\/span><\/p>\n<\/td>\n

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evet, a\u00e7\u0131k alan eklerseniz, ka\u00e7maya ve i\u00e7 i\u00e7e ge\u00e7meye yard\u0131mc\u0131 olabilirsiniz ancak i\u015f tutar\u0131n\u0131 da olumsuz etkileyebilirsiniz<\/span><\/p>\n<\/td>\n

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1<\/span><\/p>\n<\/td>\n

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1<\/span><\/p>\n<\/td>\n<\/tr>\n

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11<\/span><\/p>\n<\/td>\n

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iPlan Toplant\u0131s\u0131<\/span><\/p>\n<\/td>\n

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3<\/span><\/p>\n<\/td>\n

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Jorge<\/span><\/p>\n<\/td>\n

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02\/13\/14 10:25<\/span><\/p>\n<\/td>\n

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Evet, her \u015fey bir \u015feyi etkiler.<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

EAA Modelleri<\/h3>\n

Fikir birimlerine dayal\u0131 etkile\u015fim verilerinden bir a\u011f modeli olu\u015fturmak i\u00e7in EAA, fikir birimlerini daralt\u0131r. Genellikle bu ikili bir birikim olarak yap\u0131l\u0131r: e\u011fer fikir birimindeki herhangi bir veri sat\u0131r\u0131 A kodunu i\u00e7eriyorsa, o zaman fikir birimi A kodunu i\u00e7erir. \u00d6rne\u011fin, fikir birimlerini tan\u0131mlamak i\u00e7in \u201cEtkinlik\u201d se\u00e7ene\u011fini se\u00e7ersek, Tablo 15.1’de g\u00f6sterilen veriler Tablo 15.2’de g\u00f6sterildi\u011fi gibi daralt\u0131l\u0131r.<\/span><\/p>\n

<\/a><\/a><\/a><\/a><\/a> Tablo 15.2. Grup 3 i\u00e7in etkinliklerine g\u00f6re Fikir Birimleri<\/i><\/span><\/span><\/p>\n\n\n\n\n\n\n\n<\/colgroup>\n\n\n\n\n
\n

Etkinlik<\/b><\/p>\n<\/td>\n

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Grup<\/b><\/p>\n<\/td>\n

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E.sosyal:Say\u0131<\/b><\/p>\n<\/td>\n

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S.imar kodlar\u0131<\/b><\/p>\n<\/td>\n

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K.imar.kodlar\u0131<\/b><\/p>\n<\/td>\n

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K.ortam<\/b><\/p>\n<\/td>\n<\/tr>\n

VSV Toplant\u0131s\u0131<\/span><\/span><\/td>\n3<\/span><\/span><\/td>\n\n

0<\/p>\n<\/td>\n

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0<\/p>\n<\/td>\n

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VSV Toplant\u0131s\u0131<\/span><\/span><\/td>\n3<\/span><\/span><\/td>\n\n

0<\/p>\n<\/td>\n

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0<\/p>\n<\/td>\n

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1<\/p>\n<\/td>\n

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0<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

EAA daha sonra her bir fikir birimi i\u00e7in kodlar\u0131n bir arada oldu\u011funu \u00f6zetleyen bir kom\u015fuluk matrisi yarat\u0131r (bk. Tablo 15.3). Matrisin k\u00f6\u015fegen k\u0131sm\u0131 t\u00fcm s\u0131f\u0131rlar\u0131 i\u00e7erir, \u00e7\u00fcnk\u00fc bu modeldeki ve genel olarak EAA’daki kodlar kendileri ile birlikte bulunmaz. Her bir biti\u015fiklik matrisi, bu durumda, Grup 3’\u00fcn belirli bir faaliyet s\u0131ras\u0131nda \u015fehir planlama epistemik \u00e7er\u00e7eve elemanlar\u0131 aras\u0131nda yapt\u0131\u011f\u0131 ba\u011flant\u0131lar\u0131 temsil eder. \u00d6rne\u011fin, VSV Toplant\u0131s\u0131 etkinli\u011finde, K.sosyal.sorunlar ve K.ortam\u0131n ikisi de Grup 3\u2019\u00fcn s\u00f6yleminde ger\u00e7ekle\u015fti. Tablo 15.3’teki (yukar\u0131da) bu etkinli\u011fi temsil eden biti\u015fiklik matris, bu nedenle, bu iki kodun e\u015fzamanl\u0131l\u0131\u011f\u0131n\u0131 temsil eden h\u00fccrelerde 1 i\u00e7erir.<\/span><\/p>\n

Her fikir birimini temsil eden biti\u015fiklik matrisleri daha sonra veri k\u00fcmesindeki her bir analiz birimi i\u00e7in k\u00fcm\u00fclatif bir biti\u015fiklik matrisi halinde toplan\u0131r. Tablo 15.3’te g\u00f6sterilen basit \u00f6rnek b\u00f6ylece Tablo 15.4’te g\u00f6sterilen k\u00fcm\u00fclatif biti\u015fiklik matrisi ile temsil edilir. Bu birikim i\u015fleminin sonunda, veri k\u00fcmesindeki her birim (bu durumda, her bir grup) bu birim i\u00e7in, kodlar aras\u0131nda (epistemik \u00e7er\u00e7eve elemanlar\u0131) a\u011f\u0131rl\u0131kl\u0131 birlikte ya\u015fama modelini (bili\u015fsel ba\u011flant\u0131lar) temsil eden k\u00fcm\u00fclatif bir biti\u015fiklik matrisi ile ili\u015fkilidir.<\/span><\/p>\n

Farkl\u0131 birimler aras\u0131ndaki ba\u011flant\u0131lar\u0131n yap\u0131s\u0131n\u0131 anlamak, kendi ba\u011flant\u0131 a\u011flar\u0131 aras\u0131ndaki ili\u015fkileri veya birikimli biti\u015fik matrisleri aras\u0131ndaki farkl\u0131l\u0131klar\u0131 anlamak i\u00e7in EAA, her bir vekt\u00f6r\u00fcn matrisin \u00fcst \u00e7apraz yar\u0131s\u0131ndaki bir de\u011ferle tan\u0131mland\u0131\u011f\u0131 her bir birikimli biti\u015fiklik matrisini y\u00fcksek boyutlu bir uzayda bir vekt\u00f6r olarak temsil eder. Bu bo\u015flu\u011fun boyutlar\u0131n\u0131n, her bir kod \u00e7ifti aras\u0131ndaki ili\u015fkinin g\u00fcc\u00fcne kar\u015f\u0131l\u0131k geldi\u011fine dikkat edin.<\/span><\/p>\n

<\/a><\/a><\/a><\/a><\/a> Tablo 15.3. Grup 3 i\u00e7in etkinliklerine g\u00f6re Fikir Birimleri<\/i><\/span><\/span><\/p>\n\n\n\n\n\n\n\n<\/colgroup>\n\n\n\n\n\n\n\n
\n

3. Grup VS Toplant\u0131s\u0131<\/b><\/span><\/p>\n<\/td>\n

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E.sosyal.konular<\/b><\/span><\/p>\n<\/td>\n

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S.imar.kodlar\u0131<\/b><\/span><\/p>\n<\/td>\n

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K.sosyal.konular<\/b><\/span><\/p>\n<\/td>\n

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K.imar.kodlar\u0131<\/b><\/span><\/p>\n<\/td>\n

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K.ortam<\/b><\/span><\/p>\n<\/td>\n<\/tr>\n

E.sosyal.konular<\/span><\/span><\/td>\n\n

0<\/span><\/p>\n<\/td>\n

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S.imar.kodlar\u0131<\/span><\/span><\/td>\n\n

0<\/span><\/p>\n<\/td>\n

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K.sosyal.konular<\/span><\/span><\/td>\n\n

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K.imar.kodlar\u0131<\/span><\/span><\/td>\n\n

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0<\/span><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n\n\n\n\n\n<\/colgroup>\n\n\n\n\n\n\n\n
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3. Grup iPlan Toplant\u0131s\u0131<\/b><\/span><\/p>\n<\/td>\n

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E.sosyal.konular<\/b><\/span><\/p>\n<\/td>\n

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S.imar.kodlar\u0131<\/b><\/span><\/p>\n<\/td>\n

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K.sosyal.konular<\/b><\/span><\/p>\n<\/td>\n

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K.imar.kodlar\u0131<\/b><\/span><\/p>\n<\/td>\n

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K.ortam<\/b><\/span><\/p>\n<\/td>\n<\/tr>\n

E.sosyal.konular<\/span><\/span><\/td>\n\n

0<\/span><\/p>\n<\/td>\n

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1<\/span><\/p>\n<\/td>\n

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S.imar.kodlar\u0131<\/span><\/span><\/td>\n\n

1<\/span><\/p>\n<\/td>\n

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K.sosyal.konular<\/span><\/span><\/td>\n\n

1<\/span><\/p>\n<\/td>\n

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1<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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K.imar.kodlar\u0131<\/span><\/span><\/td>\n\n

1<\/span><\/p>\n<\/td>\n

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1<\/span><\/p>\n<\/td>\n

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1<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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1<\/span><\/p>\n<\/td>\n<\/tr>\n

K.ortam<\/span><\/span><\/td>\n\n

1<\/span><\/p>\n<\/td>\n

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1<\/span><\/p>\n<\/td>\n

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1<\/span><\/p>\n<\/td>\n

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1<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

<\/a><\/a><\/a><\/a><\/a> Tablo 15.4. Grup 3 i\u00e7in K\u00fcm\u00fclatif Biti\u015fiklik Matrisi, Tablo 3’te g\u00f6sterilen \u0130ki Biti\u015fiklik Matrisinin Toplanmas\u0131<\/i><\/span><\/span><\/p>\n\n\n\n\n\n\n\n<\/colgroup>\n\n\n\n\n\n\n\n
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Grup 3<\/b><\/span><\/p>\n<\/td>\n

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E.sosyal.konular<\/b><\/span><\/p>\n<\/td>\n

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S.imar.kodlar\u0131<\/b><\/span><\/p>\n<\/td>\n

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K.sosyal.Say\u0131<\/b><\/span><\/p>\n<\/td>\n

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K.imar.kodlar\u0131<\/b><\/span><\/p>\n<\/td>\n

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K.ortam<\/b><\/span><\/p>\n<\/td>\n<\/tr>\n

E.sosyal.konular<\/span><\/span><\/td>\n\n

0<\/span><\/p>\n<\/td>\n

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1<\/span><\/p>\n<\/td>\n

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1<\/span><\/p>\n<\/td>\n

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1<\/span><\/p>\n<\/td>\n

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1<\/span><\/p>\n<\/td>\n<\/tr>\n

S.imar.kodlar\u0131<\/span><\/span><\/td>\n\n

1<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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1<\/span><\/p>\n<\/td>\n

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1<\/span><\/p>\n<\/td>\n

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1<\/span><\/p>\n<\/td>\n<\/tr>\n

K.sosyal.konular<\/span><\/span><\/td>\n\n

1<\/span><\/p>\n<\/td>\n

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1<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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1<\/span><\/p>\n<\/td>\n

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2<\/span><\/p>\n<\/td>\n<\/tr>\n

K.imar.kodlar\u0131<\/span><\/span><\/td>\n\n

1<\/span><\/p>\n<\/td>\n

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1<\/span><\/p>\n<\/td>\n

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1<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n

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1<\/span><\/p>\n<\/td>\n<\/tr>\n

K.ortam<\/span><\/span><\/td>\n\n

1<\/span><\/p>\n<\/td>\n

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1<\/span><\/p>\n<\/td>\n

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2<\/span><\/p>\n<\/td>\n

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1<\/span><\/p>\n<\/td>\n

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0<\/span><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

EAA alan\u0131ndaki verileri analiz etmeden \u00f6nce, EAA, verileri normalle\u015ftirmek i\u00e7in her bir vekt\u00f6r\u00fc uzunlu\u011funa b\u00f6ler. Bu bir vekt\u00f6r\u00fcn uzunlu\u011fu potansiyel olarak analiz \u00fcnitesinde bulunan fikir birimi say\u0131s\u0131ndan etkilendi\u011fi i\u00e7in yap\u0131l\u0131r. Daha fazla birimin daha fazla vekt\u00f6r ortaya \u00e7\u0131karmas\u0131 olas\u0131d\u0131r, bu da daha uzun vekt\u00f6rlerle sonu\u00e7lan\u0131r. Bu problemlidir, \u00e7\u00fcnk\u00fc iki vekt\u00f6r ayn\u0131 birliktelik \u00f6r\u00fcnt\u00fcs\u00fcn\u00fc temsil edebilir ve bu nedenle ayn\u0131 y\u00f6ne i\u015faret eder ancak farkl\u0131 say\u0131da fikir birimini temsil eder ve dolay\u0131s\u0131yla farkl\u0131 uzunluklara sahiptir.<\/span><\/p>\n

Veriler normalle\u015ftirildikten sonra EAA, verileri merkezleyen ancak yeniden \u00f6l\u00e7eklendirmeyen bir projeksiyon olarak, bir tekil de\u011fer ayr\u0131\u015ft\u0131rmas\u0131 (TDA) ger\u00e7ekle\u015ftirir. Bu verilerde hesaba kat\u0131lan varyans\u0131 maksimuma \u00e7\u0131kar\u0131r (temel bile\u015fenler analizine benzer). Bununla birlikte, geleneksel bir TBA veya fakt\u00f6r analizinden farkl\u0131 olarak, (a) EAA, kodlar\u0131n say\u0131lar\u0131 veya g\u00fc\u00e7l\u00fcl\u00fc\u011f\u00fcnden ziyade, k\u00fcm\u00fclatif biti\u015fiklik matrislerin e\u015f olu\u015fumlar\u0131 \u00fczerinde ger\u00e7ekle\u015ftirilir ve (b) EAA, orijinal veriler \u00fczerinde bir k\u00fcre veya kosin\u00fcs normu uygular ve onlar\u0131 ortalar ancak boyutlar\u0131 tek tek \u00f6l\u00e7eklendirmez.<\/span><\/p>\n

EAA Modellerinin Yorumlanmas\u0131<\/h4>\n

Bir ENA modeli olu\u015fturulduktan sonra, anlaml\u0131 bir yorumu anlamak ve olu\u015fturmak i\u00e7in bir tak\u0131m ara\u00e7lar kullan\u0131labilir. \u00d6rne\u011fin, yukar\u0131da a\u00e7\u0131klanan Land Science veri k\u00fcmesinde, t\u00fcm \u00f6\u011frencilerin sohbet ifadeleri, daha \u00f6nce geli\u015ftirilmi\u015f ve onaylanm\u0131\u015f bir otomatik kodlama i\u015flemi kullan\u0131larak (24) kentsel planlama epistemik \u00e7er\u00e7eve elemanlar\u0131 i\u00e7in kodlanm\u0131\u015ft\u0131r (Ek I’e bak\u0131n\u0131z). Nash ve Shaffer (Bagley ve Shaffer, 2015b; Nash ve Shaffer)., 2011). Kentsel planlamac\u0131lar\u0131n nas\u0131l e\u011fitildi\u011fine dair etnografik bir \u00e7al\u0131\u015fmaya dayanarak otantik kentsel planlama uygulamas\u0131yla ilgili kodlar geli\u015ftirilmi\u015ftir (Bagley ve Shaffer, 2015a).<\/span><\/p>\n

\"\"<\/p>\n

<\/a> \u015eekil 15.1. Sim\u00fcle edilmi\u015f bir kentsel geli\u015fim problemini \u00e7\u00f6zerken \u00f6\u011frencini yapt\u0131\u011f\u0131 bili\u015fsel ba\u011flant\u0131lar\u0131n yap\u0131s\u0131n\u0131 temsil eden bir lise \u00f6\u011frencisinin epistemik a\u011f\u0131 (\u00d6\u011frenci A). Parantez i\u00e7indeki y\u00fczdeler, her bir boyut taraf\u0131ndan hesaplanan modeldeki toplam varyans\u0131 g\u00f6stermektedir. Birden fazla veri kayna\u011f\u0131n\u0131n birle\u015ftirilmesi.<\/i><\/span><\/span><\/p>\n

EAA modelleri tipik olarak, bir seferde iki boyutu kullanarak g\u00f6rselle\u015ftirilir ki bu yorumlamay\u0131 kolayla\u015ft\u0131r\u0131r. \u00d6rne\u011fin, \u015eekil 15.1, Land Science’a kat\u0131lan bir lise \u00f6\u011frencisinin (\u00d6\u011frenci A) k\u00fcm\u00fclatif epistemik a\u011f\u0131n\u0131 g\u00f6stermektedir. A\u011f, \u00f6\u011frenenin kentsel planlama epistemik \u00e7er\u00e7evesinin unsurlar\u0131 aras\u0131ndaki ba\u011flant\u0131lar\u0131n yap\u0131s\u0131n\u0131 modellemektedir. Bu durumda, \u00d6\u011frenci A’n\u0131n a\u011f\u0131, sosyal konular ve karma\u015f\u0131k sistemlerin bilgisi gibi bilgi unsurlar\u0131,uzla\u015fma ve kentsel planlama ara\u00e7lar\u0131n\u0131 kullanma becerisi (tercih anketi gibi) gibi epistemolojik unsurlar aras\u0131nda bir dizi ba\u011flant\u0131 g\u00f6sterir. Bu a\u011f ayr\u0131ca a\u011f\u0131rl\u0131kl\u0131d\u0131r: daha kal\u0131n, daha doymu\u015f \u00e7izgiler daha g\u00fc\u00e7l\u00fc ba\u011flant\u0131lar\u0131 temsil ederken, daha ince, daha az doymu\u015f \u00e7izgiler daha zay\u0131f ba\u011flant\u0131lar\u0131 temsil eder. Bir \u00e7izginin kal\u0131nl\u0131\u011f\u0131 \/ doygunlu\u011fu, iki epistemik \u00e7er\u00e7eve eleman\u0131 aras\u0131ndaki ba\u011flant\u0131n\u0131n meydana geldi\u011fi fikir birimi say\u0131s\u0131 ile orant\u0131l\u0131d\u0131r.<\/span><\/p>\n

\u00c7o\u011fu durumda bu \u00f6\u011frencinin a\u011f\u0131 -\u00f6rne\u011fin genellikle temel bilgi ve beceriler aras\u0131nda bili\u015fsel ba\u011flant\u0131lar kurmu\u015f olan A \u00f6\u011frencisi -hakk\u0131nda baz\u0131 \u00e7\u0131kar\u0131mlara ula\u015f\u0131rken, bir a\u011f\u0131n g\u00f6ze \u00e7arpan \u00f6zelliklerinin di\u011fer a\u011flarla kar\u015f\u0131la\u015ft\u0131r\u0131ld\u0131\u011f\u0131nda tan\u0131mlanmas\u0131 daha kolayd\u0131r. \u015eekil 15.2, ikinci lise \u00f6\u011frencisinin (\u00d6\u011frenci B) kentsel planlama epistemik a\u011f\u0131n\u0131 g\u00f6stermektedir. \u00d6\u011frenci A gibi, \u00d6\u011frenci B de temel bilgi unsurlar\u0131 aras\u0131nda bir tak\u0131m ba\u011flant\u0131lar kursa da \u00d6\u011frenci B’nin a\u011f\u0131, daha \u00e7ok ve daha g\u00fc\u00e7l\u00fc ba\u011flant\u0131lar ve ek unsurlara, \u00f6zellikle bilimsel d\u00fc\u015f\u00fcnce gibi daha ileri becerilere ve epistemolojik \u00f6zelliklere sahiptir.<\/span><\/p>\n

\"\"<\/p>\n

<\/a> \u015eekil 15.2. Sim\u00fcle edilmi\u015f bir kentsel geli\u015fim problemini \u00e7\u00f6zerken lise \u00f6\u011frencisinin bili\u015fsel ba\u011flant\u0131lar\u0131n\u0131 temsil eden bir epistemik a\u011f\u0131 (\u00d6\u011frenci B).<\/i><\/span><\/span><\/p>\n

Yukar\u0131da tart\u0131\u015f\u0131ld\u0131\u011f\u0131 gibi, epistemik \u00e7er\u00e7eve teorisi, kentsel planlama (veya herhangi bir uygulama toplulu\u011funun) epistemik \u00e7er\u00e7evesinin, kentsel planlama bilgisi, becerileri, de\u011ferleri ve di\u011fer niteliklerin birbiriyle ne kadar ba\u011flant\u0131l\u0131 oldu\u011fu ile tan\u0131mland\u0131\u011f\u0131n\u0131 ortaya koymaktad\u0131r. Bu \u00f6rnekte, EAA \u00d6\u011frenci B\u2019nin a\u011f\u0131n\u0131n daha a\u00e7\u0131k bir \u015fekilde epistemik oldu\u011funu ortaya koymaktad\u0131r: d\u00fc\u015f\u00fcncesini \u015fehir planlamac\u0131lar\u0131n\u0131n yapt\u0131\u011f\u0131 gibi a\u00e7\u0131klam\u0131\u015f ve gerek\u00e7elendirmi\u015f ve b\u00f6ylece bir \u015fehir planc\u0131s\u0131 gibi d\u00fc\u015f\u00fcnmeyi \u00f6\u011frenmi\u015ftir.<\/span><\/p>\n

A ve B \u00f6\u011frencileri aras\u0131ndaki bu kar\u015f\u0131la\u015ft\u0131rmay\u0131 m\u00fcmk\u00fcn k\u0131lan \u015fey, her iki epistemik a\u011fdaki d\u00fc\u011f\u00fcmlerin, bu iki \u00f6\u011frenci i\u00e7in ve veri k\u00fcmesindeki t\u00fcm \u00f6\u011frenciler i\u00e7in a\u011f projeksiyon alan\u0131nda ayn\u0131 yerlerde g\u00f6r\u00fcnmesidir. D\u00fc\u011f\u00fcm yerle\u015fimindeki bu de\u011fi\u015fmezlik, farkl\u0131 birimlerin a\u011f projeksiyonlar\u0131n\u0131 do\u011frudan kar\u015f\u0131la\u015ft\u0131rmam\u0131za olanak tan\u0131r ancak bu do\u011frudan kar\u015f\u0131la\u015ft\u0131rma y\u00f6ntemi sadece \u00e7ok az say\u0131da a\u011f- i\u00e7in \u00e7al\u0131\u015f\u0131r, ya d\u00fczinelerce veya y\u00fczlerce a\u011f\u0131 kar\u015f\u0131la\u015ft\u0131rmak istiyorsak? \u00d6rne\u011fin, bu veri k\u00fcmesindeki 110 lise \u00f6\u011frencisini kar\u015f\u0131la\u015ft\u0131rmak veya lise \u00f6\u011frencilerini \u00fcniversite \u00f6\u011frencileriyle kar\u015f\u0131la\u015ft\u0131rmak istiyorsak ne olur? EAA bunu, her bir a\u011f\u0131 projeksiyon alan\u0131ndaki tek bir nokta olarak temsil ederek m\u00fcmk\u00fcn k\u0131lar, b\u00f6ylece her bir nokta kar\u015f\u0131l\u0131k gelen a\u011f\u0131n sentroidi olur.<\/span><\/p>\n

Bir a\u011f\u0131n sentroidi, bir nesnenin k\u00fctle merkezine benzer. Spesifik olarak, bir a\u011f grafi\u011finin sentroidi, uzayda a\u011f projeksiyonuna g\u00f6re da\u011f\u0131t\u0131lm\u0131\u015f a\u011f modelinin kenar a\u011f\u0131rl\u0131klar\u0131n\u0131n aritmetik ortalamas\u0131d\u0131r. Buradaki \u00f6nemli nokta, bir EAA a\u011f\u0131n\u0131n sentroidinin a\u011f\u0131, a\u011f modelinin belirli bir d\u00fczenlemesindeki ba\u011flant\u0131lar\u0131n a\u011f\u0131rl\u0131kl\u0131 yap\u0131s\u0131n\u0131 a\u00e7\u0131klayan projeksiyon alan\u0131ndaki tek bir nokta olarak \u00f6zetlemesidir.<\/span><\/p>\n

A\u011f projeksiyonundaki d\u00fc\u011f\u00fcmlerin yerleri, herhangi bir a\u011f i\u00e7in, (a) a\u011f grafi\u011finin k\u00fctle merkezi ve (b) a\u011f\u0131 TDA d\u00f6n\u00fc\u015f\u00fcm\u00fc alt\u0131nda temsil eden noktay\u0131 en aza indirmek i\u00e7in bir optimizasyon rutini ile belirlenir. Bir a\u011f\u0131n sentroidinin, \u00f6ng\u00f6r\u00fclen bir uzayda a\u011f\u0131n konumuna kar\u015f\u0131l\u0131k gelmesi i\u00e7in sabit d\u00fc\u011f\u00fcm konumlar\u0131n\u0131n se\u00e7ilmesi, projeksiyon alan\u0131n\u0131n ve dolay\u0131s\u0131yla EAA modelinde farkl\u0131 a\u011flar aras\u0131ndaki belirgin farkl\u0131l\u0131klar\u0131n karakterizasyonuna izin verir. Bu durumda, projeksiyon alan\u0131n\u0131 \u015fu \u015fekilde yorumlayabiliriz: sola do\u011fru, profesyonel ileti\u015fim ve \u015fehir planlama ara\u00e7lar\u0131n\u0131n kullan\u0131m\u0131 gibi temel mesleki beceriler; sa\u011fa do\u011fru, belirli geli\u015fim problemiyle ilgili bilgi unsurlar\u0131, veri ve bilimsel d\u00fc\u015f\u00fcnme gibi daha genel konular\u0131n bilgisi ve sol \u00fcste do\u011fru daha geli\u015fmi\u015f kentsel planlama d\u00fc\u015f\u00fcncesinin unsurlar\u0131, \u00f6zellikle kentsel planlama s\u00f6zle\u015fmelerine ve imar kodlar\u0131n\u0131n kullan\u0131m\u0131na g\u00f6re kararlar alan ve hakl\u0131 \u00e7\u0131karan epistemolojik unsurlar.<\/span><\/p>\n

B\u00f6ylece, \u00e7ok say\u0131da farkl\u0131 a\u011f\u0131 e\u015fzamanl\u0131 olarak kar\u015f\u0131la\u015ft\u0131rabiliriz, \u00e7\u00fcnk\u00fc projeksiyon alan\u0131n\u0131n ayn\u0131 b\u00f6l\u00fcm\u00fcnde bulunan sentroidler benzer ba\u011flant\u0131 \u00f6r\u00fcnt\u00fclerine sahip a\u011flar\u0131 temsil ederken, projeksiyon alan\u0131n\u0131n farkl\u0131 b\u00f6l\u00fcmlerinde bulunan k\u00fctle merkezleri farkl\u0131 ba\u011flant\u0131 \u00f6r\u00fcnt\u00fclerine sahip a\u011flar\u0131 temsil eder4<\/a><\/sup>. Bu \u00f6\u011frencilerin kentsel planlama epistemik \u00e7er\u00e7eveleri hakk\u0131nda herhangi bir say\u0131da ara\u015ft\u0131rma sorusunu ke\u015ffetmemize olanak sa\u011flar. Land Science veri k\u00fcmesine sorabilece\u011fimiz bir soru, farkl\u0131 \u00f6\u011frenci topluluklar\u0131n\u0131n (kolej, lise ve \u00fcst\u00fcn yetenekli lise) epistemik a\u011flar\u0131n\u0131n nas\u0131l farkl\u0131 oldu\u011fudur? \u00d6rne\u011fin, \u00fcniversite \u00f6\u011frencilerini ve lise \u00f6\u011frencilerinin sentroidlerini \u00e7izdi\u011fimizde (\u015eekil 15.3), iki grup farkl\u0131 \u015fekilde da\u011f\u0131lm\u0131\u015ft\u0131r. Fark\u0131n istatistiksel olarak anlaml\u0131 olup olmad\u0131\u011f\u0131n\u0131 belirlemek i\u00e7in, iki pop\u00fclasyonun projeksiyon alan\u0131ndaki ortalama pozisyonlar\u0131 \u00fczerinde ba\u011f\u0131ms\u0131z \u00f6rneklemler t testi yapabiliriz. \u00dcniversite \u00f6\u011frencileri (koyu ve lise \u00f6\u011frencilerine (a\u00e7\u0131k) her iki boyutta da \u00f6nemli \u00f6l\u00e7\u00fcde farkl\u0131d\u0131r:<\/span><\/p>\n

x \u0305 <\/i>\u0305<\/span>\u00dcniversite<\/i><\/sub>= <\/i>-0.083, x <\/i>\u0305<\/span>HS<\/i><\/sub>= <\/i>0.115, t = <\/i>-7.025, p < <\/i>0.001, Cohen’s d = <\/i>-0.428 <\/span><\/span><\/p>\n

y <\/i>\u0305<\/span>\u00dcniversite<\/i><\/sub>= <\/i>0.040, y <\/i>\u0305<\/span>HS<\/i><\/sub>= –<\/i>0.045, t = <\/i>3.199, p = <\/i>0.002, Cohen’s d = <\/i>0.186 <\/span><\/span><\/p>\n

\"\"<\/p>\n

<\/a> \u015eekil 15.3. \u00dcniversite \u00f6\u011frencileri (koyu) ve lise \u00f6\u011frencilerinin (a\u00e7\u0131k) sentroidlerive onlara kar\u015f\u0131l\u0131k gelen ara\u00e7larla (kareler) ve g\u00fcven aral\u0131klar\u0131 (kutular).<\/i><\/span><\/span><\/p>\n

\u00dcst\u00fcn zek\u00e2l\u0131 ve yetenekli lise \u00f6\u011frencileri analize d\u00e2hil edildi\u011finde, baz\u0131 a\u00e7\u0131lardan, \u00fcniversite \u00f6\u011frencilerine daha \u00e7ok benzerken di\u011ferleri ise lise \u00f6\u011frencilerine daha \u00e7ok benzerler. \u00dcst\u00fcn yetenekli lise \u00f6\u011frencilerinin projeksiyon alan\u0131ndaki ortalama konumu (\u015eekil 15.4) hem \u00fcniversite \u00f6\u011frencilerinden hem de lise \u00f6\u011frencilerinden yaln\u0131zca ilk (x) boyutta istatistiksel olarak anlaml\u0131 derecede farkl\u0131d\u0131r:<\/span><\/p>\n

\"\"<\/p>\n

\u015eekil 15.4. \u00dcniversite \u00f6\u011frencileri (solda), lise \u00f6\u011frencileri (sa\u011fda) ve \u00fcst\u00fcn yetenekli lise \u00f6\u011frencilerinde (ortada) ortalama a\u011f konumlar\u0131 (kareler) ve g<\/i><\/span>\u00fcven aral\u0131klar\u0131 (kutular).<\/i><\/span><\/p>\n

<\/a><\/p>\n

x \u0305<\/span>GiftedHS<\/sub>= <\/i>0.007, x <\/i>\u0305<\/span>\u00dcniversite<\/sub>= –<\/i>0.083, t = <\/i>2.538, p = <\/i>0.013, Cohen’s d=<\/i>0.202<\/span><\/p>\n

x \u0305<\/span>GiftedHS<\/sub>= <\/i>0.007, x <\/i>\u0305<\/span>\u00dcniversite<\/sub>= <\/i>0.115, t = –<\/i>2.736, p = <\/i>0.007, Cohen’s d=-<\/i>0.223<\/span><\/p>\n

 <\/p>\n

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<\/a> \u015eekil 15.5. \u00dcniversite \u00f6\u011frencileri (sol), \u00fcst\u00fcn yetenekli lise \u00f6\u011frencileri (merkez) ve lise \u00f6\u011frencileri (sa\u011f) ortalama epistemik a\u011flar\u0131.<\/i><\/span><\/span><\/p>\n

\u00dc\u00e7 grup aras\u0131ndaki farkl\u0131l\u0131klar\u0131 belirlemede hangi fakt\u00f6rlerin hesaba kat\u0131laca\u011f\u0131n\u0131 belirlemek i\u00e7in onlar\u0131n ortalama epistemik a\u011flar\u0131n\u0131 kar\u015f\u0131la\u015ft\u0131rabiliriz. \u015eekil 15.5’te g\u00f6r\u00fcld\u00fc\u011f\u00fc gibi, \u00fcst\u00fcn yetenekli lise \u00f6\u011frencileri ortalama olarak lise \u00f6\u011frencilerinden daha geli\u015fmi\u015f ve \u015fehir planlama d\u00fc\u015f\u00fcncesinin unsurlar\u0131yla daha g\u00fc\u00e7l\u00fc ba\u011flar kurmu\u015flard\u0131r. Yani, lise ve \u00fcniversite \u00f6\u011frencilerinden aras\u0131nda, alandaki karma\u015f\u0131k d\u00fc\u015f\u00fcnceye ili\u015fkin bir yerdeydiler. Buna kar\u015f\u0131l\u0131k, \u00fcst\u00fcn yetenekli lise \u00f6\u011frencileri, her iki pop\u00fclasyonun da temel mesleki beceriler ve ileri kent planlama d\u00fc\u015f\u00fcncesi aras\u0131ndaki \u00fcniversite \u00f6\u011frencilerinden daha az ba\u011flant\u0131 kurmas\u0131 nedeniyle lise \u00f6\u011frencilerine daha benzer g\u00f6r\u00fcn\u00fcyor. Ba\u015fka bir deyi\u015fle, \u00fcst\u00fcn zek\u00e2l\u0131 lise \u00f6\u011frencileri, lise ve \u00fcniversite \u00f6\u011frencileri aras\u0131nda entelekt\u00fcel bir yerdedir ancak temel mesleki ve ki\u015filer aras\u0131 beceriler seviyesinde lise \u00f6\u011frencilerine daha benzerdir.<\/span><\/p>\n

EAA A\u011f Modellerinin Nicel \u00dc\u00e7genlemesi(Triangulation)<\/h3>\n

EAA’n\u0131n en \u00f6nemli \u00f6zelli\u011fi, modeldeki ba\u011flant\u0131lar\u0131, sohbetlerin dayand\u0131\u011f\u0131 orijinal verilere kadar izleyebilmesidir. \u201cSosyal konular\u0131n epistemolojisi\u201d ile \u201cveri bilgisi\u201d aras\u0131ndaki ba\u011flant\u0131y\u0131 t\u0131klayarak, bu ba\u011flant\u0131ya katk\u0131da bulunan t\u00fcm ifadelere a\u011f grafi\u011finden eri\u015febiliriz. \u015eekil 15.6, bir \u00fcniversite \u00f6\u011frencisinin epistemik a\u011f\u0131nda bu ba\u011flant\u0131ya katk\u0131da bulunan ifadelerin bir k\u0131sm\u0131n\u0131 g\u00f6stermektedir.<\/span><\/p>\n

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<\/a> \u015eekil 15.6. Bir \u00fcniversite \u00f6\u011frencisinin epistemik a\u011f\u0131ndaki sosyal sorunlar\u0131n epistemolojisi ile veri bilgisi aras\u0131ndaki ba\u011flant\u0131ya katk\u0131da bulunan sohbet ifadeleri. EAA ara\u00e7 setinde, her bir ifadenin metni, A kodunu mu (k\u0131rm\u0131z\u0131), B kodunu mu (mavi), her ikisini de mi (mor) i\u00e7erir veya hi\u00e7birini (siyah) i\u00e7ermedi\u011fini belirtmek i\u00e7in renklidir.<\/i><\/span><\/span><\/p>\n

Metin, sadece birinci kodu i\u00e7eren bo\u015fluklar veya ifadeler k\u0131rm\u0131z\u0131, sadece ikinci kodu i\u00e7erenler mavi, her iki kodu i\u00e7erenler de mor renk ve hi\u00e7bir kodu i\u00e7ermeyenler siyah renkte g\u00f6sterilecek \u015fekilde renklidir. \u201cNihai Teklif Yans\u0131mas\u0131\u201d fikir birimi (etkinlik, gibi), \u00f6rne\u011fin mor renktedir, \u00e7\u00fcnk\u00fc hem E.sosyal.konular hem de K.veri i\u00e7in kodlanan ifadeler i\u00e7erir: birinci (k\u0131rm\u0131z\u0131) ifade, arazi kullan\u0131m de\u011fi\u015fikli\u011fine dayanarak kenti iyile\u015ftirme iste\u011fini gerek\u00e7elendirirken (sosyal sorunlar\u0131n epistemolojisi), ikinci ifade ise imar de\u011fi\u015fikliklerinin atmosferik karbondioksit seviyeleri \u00fczerindeki etkileriyle ilgili bilgileri (veri bilgisi) g\u00f6sterir.<\/span><\/p>\n

\"\"<\/p>\n

<\/a> \u015eekil 15.7. \u0130yi teoriye dayal\u0131 \u00f6\u011frenme analiti\u011fi, bir modelin orijinal verilere kar\u015f\u0131 yorumlanmas\u0131n\u0131 do\u011frulamay\u0131 m\u00fcmk\u00fcn k\u0131larak \u201cyorumlay\u0131c\u0131 d\u00f6ng\u00fcy\u00fc kapat\u0131r\u201d.<\/i><\/span><\/span><\/p>\n

EAA’n\u0131n bu \u00f6zelli\u011fi yorumlay\u0131c\u0131 d\u00f6ng\u00fcy\u00fc kapatmam\u0131z\u0131 sa\u011flar (bk. \u015eekil 15.7). Kentsel planlama epistemik \u00e7er\u00e7eve \u00f6geleri i\u00e7in kodlanm\u0131\u015f bir veri k\u00fcmesi ile ba\u015flad\u0131k; kodlanm\u0131\u015f verileri, \u00e7er\u00e7eve \u00f6gelerinin birlikte olu\u015fmas\u0131na dayanarak \u00f6\u011frencilerin kentsel planlama d\u00fc\u015f\u00fcncesinin a\u011f modellerini olu\u015fturmak ve g\u00f6rselle\u015ftirmek i\u00e7in kulland\u0131k; o zaman, a\u011f modellerinde ba\u011flant\u0131lar\u0131n herhangi birinin temelini anlamak istiyorsak, orijinal ifadelere geri d\u00f6nebiliriz. B\u00f6ylece EAA, nicel verilerin nitel olarak do\u011frulanabilmesi i\u00e7in nicel verilerin nitel analizini m\u00fcmk\u00fcn k\u0131lar.<\/span><\/p>\n

TARTI\u015eMA<\/h2>\n

Bu analizi \u00e7al\u0131\u015f\u0131rken, amac\u0131m\u0131z takip edilesi ideal bir \u00f6rnek sunmak, epistemik \u00e7er\u00e7eve teorisinin di\u011fer \u00f6\u011frenme teorilerine g\u00f6re herhangi bir \u00f6zel analitik avantaj\u0131 oldu\u011funu \u00f6ne s\u00fcrmek de\u011fil, e\u011fitsel veri madencili\u011fi ve \u00f6\u011frenme analiti\u011fi metodolojisinin daha genel bir tart\u0131\u015fmas\u0131 i\u00e7in ba\u011flam sa\u011flamakt\u0131. B\u00fcy\u00fck e\u011fitsel veri k\u00fcmelerinin analizleri daha yayg\u0131n hale geldik\u00e7e, \u201c\u00f6\u011frenmeyi etkileyen kilit fakt\u00f6rleri daha iyi anlamalar\u0131n\u0131 sa\u011flamak i\u00e7in e\u011fitim teorilerini ve iyi bilinen e\u011fitim olaylar\u0131n\u0131 geli\u015ftirmek ve geni\u015fletmek amac\u0131yla” g\u00f6rg\u00fcl kan\u0131tlar elde etmek \u00f6nemli bir uygulamad\u0131r. (Baker ve Yacef, 2009, s. 7). Ba\u015fka bir deyi\u015fle, teorik bir \u00e7er\u00e7eve de\u011fi\u015fkenlerin se\u00e7ilmesine ve hipotezlerin geli\u015fimine rehberlik eder; bu durum, g\u00f6zlenen olaylar\u0131n neden meydana geldi\u011finin a\u00e7\u0131klanmas\u0131na yol a\u00e7abilir.<\/span><\/p>\n

Yukar\u0131da sunulan \u00e7al\u0131\u015f\u0131lm\u0131\u015f \u00f6rnekte, bir kentsel planlama sim\u00fclasyonunda \u00f6\u011frenen sohbet verisi analizimizi y\u00f6nlendirmek i\u00e7in epistemik \u00e7er\u00e7eve teorisini kulland\u0131k. Epistemik \u00e7er\u00e7eve teorisi, \u00f6\u011frenmenin, \u00f6\u011frencilerin ger\u00e7ek uygulama pratikleri aras\u0131nda yapt\u0131klar\u0131 ba\u011flant\u0131lar\u0131n yap\u0131s\u0131 ile karakterize edilebilece\u011fini \u00f6ne s\u00fcrer. Analitik yakla\u015f\u0131m\u0131m\u0131z olan ENA, a\u011f grafi\u011fi olarak g\u00f6rselle\u015ftirilen \u00f6\u011frenen \u00f6\u011frenme modellerini, ba\u011flant\u0131 \u00f6r\u00fcnt\u00fclerinin matematiksel g\u00f6sterimlerini olu\u015fturmak i\u00e7in s\u00f6ylem verilerini kullan\u0131r. Bu sebeple analiz, \u00f6\u011frenmeyi anlamak i\u00e7in belirli bir teorik yakla\u015f\u0131m\u0131n i\u015flevselle\u015ftirilmesidir.<\/span><\/p>\n

\"\"<\/p>\n

<\/a> \u015eekil 15.8. Bir KDDT De\u011ferlendirmesinde Modeller (Mislevy, 2006’dan uyarlanm\u0131\u015ft\u0131r).<\/i><\/span><\/span><\/p>\n

Teori, veri ve analiz aras\u0131ndaki ba\u011flant\u0131y\u0131 kavramsalla\u015ft\u0131rman\u0131n bir yolu kan\u0131ta dayal\u0131 tasar\u0131md\u0131r (Mislevy ve Riconscente, 2006; Rupp, Gustha vd., 2010; Shaffer vd., 2009). Kan\u0131t merkezli tasar\u0131mda, analitik bir \u00e7er\u00e7eve birbirine ba\u011fl\u0131 \u00fc\u00e7 modelden olu\u015fur: bir \u00f6\u011frenen modeli, bir kan\u0131t modeli ve bir g\u00f6rev modeli (bk. \u015eekil 15.8; Mislevy, Steinberg ve Almond, 1999; Mislevy, 2006). \u00d6\u011frenci modeli, de\u011ferlendirmek istedi\u011fimiz \u00f6\u011frencinin \u00f6zelliklerini veya daha genel olarak modellemeye veya \u00f6l\u00e7meye \u00e7al\u0131\u015ft\u0131\u011f\u0131m\u0131z sonucu temsil eder. G\u00f6rev modeli, \u00f6\u011frenen modelindeki sonu\u00e7lar\u0131 \u00f6l\u00e7mek i\u00e7in kullan\u0131lacak faaliyetleri ve verileri temsil eder. \u00d6\u011frenci (sonu\u00e7) modeli ve g\u00f6rev (veri) modeli, verilere dayanan \u00e7\u0131kar\u0131mlarla ilgili sonu\u00e7lar\u0131 garanti alt\u0131na almak i\u00e7in kullan\u0131lacak analitik ara\u00e7 ve teknikleri ayr\u0131nt\u0131land\u0131ran bir kan\u0131t modeliyle ba\u011flant\u0131l\u0131d\u0131r.<\/span><\/p>\n

\u00c7al\u0131\u015f\u0131lan \u00f6rnek, \u00f6\u011frenme analiti\u011fine modellerin her birinin (\u00f6\u011frenci, kan\u0131t ve g\u00f6rev) bu durumda, ayn\u0131 kuramsal \u00e7er\u00e7eveden, epistemik \u00e7er\u00e7eve kuram\u0131ndan t\u00fcretildi\u011fi bir yakla\u015f\u0131m\u0131 g\u00f6stermektedir (bk. \u015eekil 15.9).<\/span><\/p>\n

\"\"<\/p>\n

<\/a> \u015eekil 15.9. \u00dcniversite \u00f6\u011frencileri (solda), lise \u00f6\u011frencileri (sa\u011fda) ve \u00fcst\u00fcn yetenekli lise \u00f6\u011frencilerinde (ortada) ortalama a\u011f konumlar\u0131 (kareler) ve g\u00fcven aral\u0131klar\u0131 (kutular).<\/i><\/span><\/span><\/p>\n

Sonu\u00e7, belirli bir uzmanl\u0131k teorisi taraf\u0131ndan y\u00f6nlendirilen ve g\u00f6rg\u00fcl\/deneysel olarak do\u011frulanan (sim\u00fcle edilmi\u015f) karma\u015f\u0131k problem \u00e7\u00f6zme ba\u011flam\u0131nda uzmanl\u0131\u011f\u0131 analiz etmeye y\u00f6nelik bir yakla\u015f\u0131md\u0131r. Ancak sonu\u00e7lar\u0131n g\u00f6rg\u00fcl\/deneysel esaslar\u0131 ciddi bir \u015fekilde yaln\u0131zca istatistiksel manidarl\u0131\u011fa dayanmamaktad\u0131r: kan\u0131tsal arg\u00fcman\u0131n\u0131n farkl\u0131 modelleri veya katmanlar\u0131 aras\u0131ndaki ba\u011flant\u0131lar nedeniyle, -modelin anlam\u0131n\u0131n- yorumlanmas\u0131ndaki istatistikler orijinal verilerde do\u011frulanabilir.<\/span><\/p>\n

Teoriye dayal\u0131 bir yakla\u015f\u0131m\u0131n veri analizine getirdi\u011fi bu avantajlara ra\u011fmen, bulgular i\u00e7in radikal bir \u015fekilde teorik olmayan bir yakla\u015f\u0131m izleyen \u00e7al\u0131\u015fmalarda \u00f6nemli bir art\u0131\u015f olmu\u015ftur. Wired dergisi ba\u015f edit\u00f6r\u00fc Chris Anderson (2008) b\u00fcy\u00fck veri \u00e7a\u011f\u0131nda teoriye dayal\u0131 soru\u015fturman\u0131n gereksiz oldu\u011funu bile iddia etti. Anderson, \u201cPetabayt [veri] \u015funu s\u00f6ylememize izin veriyor: ‘Korelasyon yeterli,’\u201d telkininde bulunuyor. \u201cNeyi g\u00f6sterebilecekleri konusunda hipotezler olmadan verileri analiz edebiliriz. Rakamlar\u0131 d\u00fcnyan\u0131n g\u00f6rd\u00fc\u011f\u00fc en b\u00fcy\u00fck hesaplama k\u00fcmelerine koyabiliriz ve istatistiksel algoritmalar\u0131n bilimin bulamayaca\u011f\u0131 \u00f6r\u00fcnt\u00fcleri bulmas\u0131na izin verebiliriz. \u201d\u00c7o\u011fu bilim insan\u0131n\u0131n nedenselli\u011fin \u00f6nemsiz oldu\u011fu fikrinden derinden rahats\u0131zl\u0131k duyaca\u011f\u0131 ger\u00e7e\u011fine ra\u011fmen, Anderson’un b\u00fcy\u00fck verinin analizine -\u201cilk \u00f6nce matematiksel verileri g\u00f6r\u00fcnt\u00fcleme ve daha sonra bunun i\u00e7in bir ba\u011flam olu\u015fturma”- yakla\u015f\u0131m\u0131 veri madencili\u011finde yayg\u0131n olarak kullan\u0131lmaktad\u0131r.<\/span><\/p>\n

Tabii ki, yeterince b\u00fcy\u00fck bir veri k\u00fcmesi ve y\u00fczlerce olmasa bile onlarca matematiksel model ile bu verilerin alt\u0131ndan girip \u00fcst\u00fcnden \u00e7\u0131kma becerisi ile istatistiksel olarak anlaml\u0131 \u00f6r\u00fcnt\u00fcler bulunacakt\u0131r. Ancak istatistiksel anlaml\u0131l\u0131k kavramsal ve hatta kullan\u0131labilir bir anlam ifade etmez. Bu geni\u015f veri toplama y\u00f6ntemlerini analiz etmeye y\u00f6nelik t\u00fcm teori temelli yakla\u015f\u0131mlar\u0131n ideal veya hatta de\u011ferli oldu\u011fu anlam\u0131na gelmez. K\u00f6t\u00fc g\u00f6rg\u00fcll\u00fck ve hatta k\u00f6t\u00fc bir \u015fekilde i\u015flevselle\u015ftirilmi\u015f veya uygulanm\u0131\u015f iyi teori oldu\u011fu gibi k\u00f6t\u00fc teori de vard\u0131r. Yukar\u0131daki \u00e7al\u0131\u015f\u0131lan \u00f6rne\u011fin veya daha genel olarak se\u00e7ti\u011fimiz teori ve y\u00f6ntemlerin her ko\u015fulda ideal oldu\u011funu da iddia etmiyoruz.<\/span><\/p>\n

Bizim arg\u00fcman\u0131m\u0131z daha \u00e7ok, b\u00fcy\u00fck e\u011fitsel veri k\u00fcmelerinin analizinde teoriye dayal\u0131 bir yakla\u015f\u0131m benimsemenin belirgin avantajlar\u0131 oldu\u011fu \u015feklindedir. Yukar\u0131daki \u00e7al\u0131\u015fan \u00f6rnek, teori g\u00fcd\u00fcml\u00fc \u00f6\u011frenme analitiklerinde, a\u00e7\u0131k bir teorik \u00e7er\u00e7evenin, bir veri derlemini anlama aray\u0131\u015f\u0131nda ve uygun analitik y\u00f6ntemlerin se\u00e7iminde nas\u0131l yol g\u00f6sterdi\u011fini g\u00f6stermektedir. Veri, teori ve analiz aras\u0131ndaki bu ba\u011flant\u0131lar b\u00f6ylece sonu\u00e7lar\u0131 hassas ve anlaml\u0131 bir \u015fekilde yorumlama becerisi sa\u011flar.<\/span><\/p>\n

TE\u015eEKK\u00dcR B\u00d6L\u00dcM\u00dc<\/h2>\n

Bu \u00e7al\u0131\u015fma, k\u0131smen Ulusal Bilim Vakf\u0131 (DRL-0918409, DRL-0946372, DRL-1247262, DRL-1418288, DUE-0919347, DUE-1225885, EEC-1232656, EEC-1340402, REC-0347000) MacArthur Vakf\u0131, Spencer Vakf\u0131, Wisconsin Mezunlar\u0131 Ara\u015ft\u0131rma Vakf\u0131 ve Wisconsin-Madison \u00dcniversitesi Ara\u015ft\u0131rma ve Lisans\u00fcst\u00fc E\u011fitimden Sorumlu Ba\u015fkan Yard\u0131mc\u0131l\u0131\u011f\u0131 Ofisi taraf\u0131ndan finanse edildi. G\u00f6r\u00fc\u015fler, bulgular ve \u00e7\u0131kar\u0131mlar, fon veren kurulu\u015flar\u0131n, i\u015f birli\u011fi yapan kurumlar\u0131n veya di\u011fer ki\u015filerin g\u00f6r\u00fc\u015flerini yans\u0131tmamaktad\u0131r.<\/span><\/p>\n

KAYNAK\u00c7A<\/h2>\n

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Andrist, S., Collier, W., Gleicher, M., Mutlu, B., & Shaffer, D. (2015). Look together: Analyzing gaze coordination with epistemic network analysis. Frontiers in Psychology, 6<\/i>(1016). journal.frontiersin.org\/article\/10.3389\/ fpsyg.2015.01016 \/ pdf <\/span><\/span><\/p>\n

Arastoopour, G., Shaffer, D. W., Swiecki, Z., Ruis, A. R., & Chesler, N. C. (2016). Teaching and assessing engineering design thinking with virtual internships and epistemic network analysis. International Journal of Engineering Education, 32<\/i>(2), in press. <\/span><\/span><\/p>\n

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Bagley, E. A., & Shaffer, D. W. (2009). When people get in the way: Promoting civic thinking through epistemic game play. International Journal of Gaming and Computer-Mediated Simulations, 1<\/i>(1), 36\u201352. <\/span><\/span><\/p>\n

Bagley, E. A., & Shaffer, D. W. (2015a). Learning in an urban and regional planning practicum: The view from educational ethnography. Journal of Interactive Learning Research, 26<\/i>(4), 369\u2013393. <\/span><\/span><\/p>\n

Bagley, E. A., & Shaffer, D. W. (2015b). Stop talking and type: Comparing virtual and face-to-face mentoring in an epistemic game. Journal of Computer Assisted Learning, 31<\/i>(6), 606\u2013622. <\/span><\/span><\/p>\n

Baker, R. S. J. d., & Yacef, K. (2009). The state of educational data mining in 2009: A review and future visions. Journal of Educational Data Mining, 1<\/i>(1), 3\u201317. <\/span><\/span><\/p>\n

Chesler, N. C., Ruis, A. R., Collier, W., Swiecki, Z., Arastoopour, G., & Shaffer, D. W. (2015). A novel paradigm for engineering education: Virtual internships with individualized mentoring and assessment of engineering thinking. Journal of Biomechanical Engineering, 137<\/i>(2), 024701:1\u20138. <\/span><\/span><\/p>\n

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Goffman, E. (1974). Frame analysis: An essay on the organization of experience<\/i>. Cambridge, MA: Harvard University Press. <\/span><\/span><\/p>\n

Goodwin, C. (1994). Professional vision. American Anthropologist, 96<\/i>(3), 606\u2013633. <\/span><\/span><\/p>\n

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Landauer, T. K., McNamara, D. S., Dennis, S., & Kintsch, W. (2007). Handbook of latent semantic <\/i>analysis. Mahwah, NJ: Erlbaum. <\/span><\/span><\/p>\n

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Mislevy, R. J., Steinberg, L. S., & Almond, R. G. (1999). Evidence-centered assessment design<\/i>. Educational Testing Service. http:\/\/www.education.umd.edu\/EVMS\/mislevy\/papers\/ECD_overview.html <\/span><\/span><\/p>\n

Mislevy, R., & Riconscente, M. M. (2006). Evidence-centered assessment design: Layers, concepts, and terminology. In S. Downing & T. Haladyna (Eds.), Handbook of Test Development <\/i>(pp. 61\u201390). Mahwah, NJ: Erlbaum.<\/span><\/span><\/p>\n

Nash, P., Bagley, E. A., & Shaffer, D. W. (2012). Playing for public interest: Epistemic games as civic engagement activities. American Educational Research Association Annual Conference <\/i>(AERA). Vancouver, BC, Canada. <\/span><\/span><\/p>\n

Nash, P., & Shaffer, D. W. (2011). Mentor modeling: The internalization of modeled professional thinking in an epistemic game. Journal of Computer Assisted Learning, 27<\/i>(2), 173\u2013189. <\/span><\/span><\/p>\n

Nash, P., & Shaffer, D. W. (2012). Epistemic youth development: Educational games as youth development activities. American Educational Research Association Annual Conference <\/i>(AERA). Vancouver, BC, Canada. <\/span><\/span><\/p>\n

Nash, P., & Shaffer, D. W. (2013). Epistemic trajectories: Mentoring in a game design practicum. Instructional Science<\/i>, 41(4), 745\u2013771. <\/span><\/span><\/p>\n

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Rupp, A. A., Sweet, S., & Choi, Y. (2010). Modeling learning trajectories with epistemic network analysis: A simulation-based investigation of a novel analytic method for epistemic games. In R. S. J. d. Baker, A. Merceron, P. I. Pavlik Jr. (Eds.), Proceedings of the 3rd International Conference on Educational Data Mining <\/i>(EDM2010), 11\u201313 June 2010, Pittsburgh, PA, USA (pp. 319\u2013320). International Educational Data Mining Society. <\/span><\/span><\/p>\n

Shaffer, D.W. (2004). Epistemic frames and islands of expertise: Learning from infusion experiences. Proceedings of the 6th International Conference of the Learning Sciences <\/i>(ICLS 2004): Embracing Diversity in the Learning Sciences<\/i>, 22\u201326 June 2004, Santa Monica, CA, USA (pp. 473\u2013480). Mahwah, NJ: Lawrence Erlbaum. <\/span><\/span><\/p>\n

Shaffer, D. W. (2006). Epistemic frames for epistemic games. Computers and Education<\/i>, 46(3), 223\u2013234. <\/span><\/span><\/p>\n

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Shaffer, D. W. (2012). Models of situated action: Computer games and the problem of transfer. In C. Steinkuehler, K. D. Squire, & S. A. Barab (Eds.), Games, learning, and society: Learning and meaning in the digital age <\/i>(pp. 403\u2013431). Cambridge, UK: Cambridge University Press. <\/span><\/span><\/p>\n

Shaffer, D. W., Collier, W., & Ruis, A. R. (2016). A tutorial on epistemic network analysis: Analyzing the structure of connections in cognitive, social, and interaction data. Journal of Learning Analytics, 3<\/i>(3), 9\u201345. <\/span><\/span><\/p>\n

Shaffer, D. W., Hatfield, D. L., Svarovsky, G. N., Nash, P., Nulty, A., Bagley, E. A., \u2026 Frank, K. (2009). Epistemic Network Analysis: A prototype for 21st century assessment of learning. International Journal of Learning and Media, 1<\/i>(1), 1\u201321. <\/span><\/span><\/p>\n

Svarovsky, G.N. (2011). Exploring complex engineering learning over time with epistemic network analysis. Journal of Pre-College Engineering Education Research, 1<\/i>(2), 19\u201330. <\/span><\/span><\/p>\n

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Wise, A. F., & Shaffer, D. W. (2016). Why theory matters more than ever in the age of big data. Journal of Learning Analytics, 2(2), 5\u201313.<\/span><\/span><\/p>\n

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1<\/a> \u00c7evirenin notu: Yazar Aldoux Huxley\u2019in Cesur Yeni D\u00fcnya isimli kitab\u0131na at\u0131fta bulunuyor.<\/span><\/span><\/p>\n

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2<\/a> orj. a priori<\/span><\/span><\/p>\n<\/div>\n

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3<\/a> orj. Stanza<\/span><\/span><\/p>\n<\/div>\n

\n

4<\/a> Elbette, \u00e7ok farkl\u0131 ba\u011flant\u0131 yap\u0131lar\u0131na sahip iki a\u011f\u0131n benzer k\u00fctle merkezini payla\u015fmas\u0131 m\u00fcmk\u00fcnd\u00fcr. \u00d6rne\u011fin, \u00e7ok say\u0131da ba\u011flant\u0131ya sahip bir a\u011f, men\u015fei\/ kaynak yak\u0131n\u0131nda bir k\u00fctle merkezini i\u00e7erebilir; ancak ayn\u0131 \u015fey, en sa\u011fda ve n solda yaln\u0131zca birka\u00e7 ba\u011flant\u0131 bulunan bir a\u011f i\u00e7in de ge\u00e7erlidir. Belli ba\u015fl\u0131 baz\u0131 nedenlerden \u00f6t\u00fcr\u00fc, boyutsal bir k\u00fc\u00e7\u00fcltmedeki hi\u00e7bir \u00f6zet istatistik orijinal a\u011f\u0131n t\u00fcm bilgilerini koruyamaz.<\/span><\/span><\/p>\n<\/div>\n","protected":false},"author":1,"menu_order":5,"template":"","meta":{"pb_show_title":"on","pb_short_title":"","pb_subtitle":"","pb_authors":[],"pb_section_license":""},"chapter-type":[48],"contributor":[],"license":[],"class_list":["post-99","chapter","type-chapter","status-publish","hentry","chapter-type-numberless"],"part":73,"_links":{"self":[{"href":"https:\/\/acikkitap.com.tr\/oaek\/wp-json\/pressbooks\/v2\/chapters\/99","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/acikkitap.com.tr\/oaek\/wp-json\/pressbooks\/v2\/chapters"}],"about":[{"href":"https:\/\/acikkitap.com.tr\/oaek\/wp-json\/wp\/v2\/types\/chapter"}],"author":[{"embeddable":true,"href":"https:\/\/acikkitap.com.tr\/oaek\/wp-json\/wp\/v2\/users\/1"}],"version-history":[{"count":0,"href":"https:\/\/acikkitap.com.tr\/oaek\/wp-json\/pressbooks\/v2\/chapters\/99\/revisions"}],"part":[{"href":"https:\/\/acikkitap.com.tr\/oaek\/wp-json\/pressbooks\/v2\/parts\/73"}],"metadata":[{"href":"https:\/\/acikkitap.com.tr\/oaek\/wp-json\/pressbooks\/v2\/chapters\/99\/metadata\/"}],"wp:attachment":[{"href":"https:\/\/acikkitap.com.tr\/oaek\/wp-json\/wp\/v2\/media?parent=99"}],"wp:term":[{"taxonomy":"chapter-type","embeddable":true,"href":"https:\/\/acikkitap.com.tr\/oaek\/wp-json\/pressbooks\/v2\/chapter-type?post=99"},{"taxonomy":"contributor","embeddable":true,"href":"https:\/\/acikkitap.com.tr\/oaek\/wp-json\/wp\/v2\/contributor?post=99"},{"taxonomy":"license","embeddable":true,"href":"https:\/\/acikkitap.com.tr\/oaek\/wp-json\/wp\/v2\/license?post=99"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}