{"id":101,"date":"2020-09-03T16:39:43","date_gmt":"2020-09-03T13:39:43","guid":{"rendered":"http:\/\/acikkitap.com.tr\/oaek\/chapter\/bolum-23-ogrenme-ve-calisma-mesleki-ogrenme-analitigi\/"},"modified":"2020-09-03T16:39:43","modified_gmt":"2020-09-03T13:39:43","slug":"bolum-23-ogrenme-ve-calisma-mesleki-ogrenme-analitigi","status":"publish","type":"chapter","link":"https:\/\/acikkitap.com.tr\/oaek\/chapter\/bolum-23-ogrenme-ve-calisma-mesleki-ogrenme-analitigi\/","title":{"raw":"B\u00f6l\u00fcm 23 \u00d6\u011frenme ve \u00c7al\u0131\u015fma: Mesleki \u00d6\u011frenme Analiti\u011fi","rendered":"B\u00f6l\u00fcm 23 \u00d6\u011frenme ve \u00c7al\u0131\u015fma: Mesleki \u00d6\u011frenme Analiti\u011fi"},"content":{"raw":"\n

Allison Littlejohn<\/span><\/span><\/p>\n

E\u011fitim Teknolojileri Enstit\u00fcs\u00fc, A\u00e7\u0131k \u00dcniversite, Birle\u015fik Krall\u0131k<\/span><\/span><\/p>\n

DOI: 10.18608\/hla17.023<\/span><\/span><\/p>\n\n

\u00d6Z<\/h2>\n

Mesleki \u00f6\u011frenme, mesleki faaliyetler, yayg\u0131n e\u011fitim ve \u00f6rg\u00fcn e\u011fitim gibi farkl\u0131 t\u00fcrlerde olabilir. \u00c7al\u0131\u015fanlar a\u011fa ba\u011fl\u0131 farkl\u0131 \u00e7al\u0131\u015fma ortamlar\u0131nda i\u015f birli\u011fi yaparken de\u011fi\u015fik \u015fekillerde dijital ayak izleri ve \"\u00f6zel ili\u015fkileri\"ne ili\u015fkin veriler b\u0131rak\u0131rlar. Bu veriler \u00e7al\u0131\u015fanlar\u0131n \u00f6\u011frenmelerini desteklemek amac\u0131yla hem \u00f6rg\u00fcn hem de yayg\u0131n \u00f6\u011frenme s\u00fcre\u00e7lerini izlenebilir ve g\u00f6r\u00fcn\u00fcr k\u0131lmak i\u00e7in \u00f6\u011frenme analiti\u011finde (\u00d6A) kullan\u0131labilir. Bu b\u00f6l\u00fcm, mesleki \u00f6\u011frenme analiti\u011fi (M\u00d6A) i\u00e7in bir vizyon ortaya koyarak ve \u00e7al\u0131\u015fma ortamlar\u0131nda fiilen uygulanan analitik \u00f6rneklerini \u00e7\u00f6z\u00fcmleyerek \u00e7al\u0131\u015fanlar\u0131n nas\u0131l \u00f6\u011frendiklerinin g\u00f6z \u00f6n\u00fcnde bulunduruldu\u011fu, mesleki \u00f6\u011frenme analitiklerinde gelinen son noktay\u0131 incelemektedir. \u00d6A, duygusal ve motivasyonel \u00f6\u011frenme konular\u0131n\u0131n yan\u0131 s\u0131ra teknik ve pratik uzmanl\u0131\u011f\u0131 da ele alabilir; bireysel \u00f6\u011frenme faaliyetlerini kurumsal \u00f6\u011frenme hedeflerine g\u00f6re ak\u0131ll\u0131ca d\u00fczenleyebilir. M\u00d6A gelecekteki \u00f6\u011frenme ve \u00e7al\u0131\u015fma i\u00e7in bir temel olu\u015fturmak \u00fczere ayarlanm\u0131\u015ft\u0131r.<\/span><\/span><\/p>\n

Anahtar Kelimeler<\/span>: Mesleki \u00f6\u011frenme, \u00f6rg\u00fcn e\u011fitim, yayg\u0131n e\u011fitim<\/span><\/span><\/p>\n

Mesleki \u00f6\u011frenme, s\u00fcrekli iyile\u015ftirme, yenilik\u00e7ilik ve i\u015f i\u00e7in yeni uygulamalar\u0131n benimsenmesinin kritik bir bile\u015fenidir (Boud ve Garrick, 1999; Fuller vd., 2003; Engestrom, 2008). Belirsiz bir i\u015f ortam\u0131nda, kurulu\u015flar\u0131n s\u00fcrekli de\u011fi\u015fim ile ba\u015fa \u00e7\u0131kmalar\u0131 i\u00e7in s\u00fcrekli \u00f6\u011frenebilmeleri gerekir (IBM, 2008). Mesleki \u00f6\u011frenme, \u00f6rg\u00fcn e\u011fitimden meslekta\u015flarla yap\u0131lan g\u00f6r\u00fc\u015fmelere, i\u015f etkinlikleri yoluyla ger\u00e7ekle\u015fen resm\u00ee olmayan e\u011fitime kadar de\u011fi\u015fen farkl\u0131 bi\u00e7imlerde (Eraut, 2004; Fuller vd., 2003) \u015fekillenir. Bu eylemler, profesyonel \u00f6\u011frenme ve geli\u015fimi iyile\u015ftirmek i\u00e7in kullan\u0131labilecek \u00e7e\u015fitli veriler \u00fcreten farkl\u0131 \u00f6\u011frenme ba\u011flamlar\u0131 olarak alg\u0131lanabilir (Billett, 2004; Littlejohn, Milligan ve Margaryan, 2012). G\u00fcn\u00fcm\u00fcz i\u015fyerlerinde, \u00e7al\u0131\u015fanlar, dijital kaynaklar\u0131 kullanarak, \u00e7e\u015fitli dijital izler ve \"t\u0131klama\" verileri b\u0131rakarak a\u011fa ba\u011fl\u0131 ortamlarda i\u015f birli\u011fi yapma e\u011filimindedir. Bu farkl\u0131 veri t\u00fcrlerinin analizi potansiyel olarak, \u00e7al\u0131\u015fanlar\u0131n \u00e7ok \u00e7e\u015fitli \u00f6\u011frenme ve uyarlama tarzlar\u0131n\u0131 geli\u015ftirerek ve destekleyerek i\u015flevsel verimlili\u011fi art\u0131rmak i\u00e7in g\u00fc\u00e7l\u00fc bir yol sa\u011flar.<\/span><\/p>\n

Son birka\u00e7 y\u0131ld\u0131r, i\u015fverenler, \u00e7al\u0131\u015fan e\u011fitiminin desteklenmesi ve geli\u015ftirilmesinde \u00f6\u011frenme analiti\u011fi potansiyelinin fark\u0131ndad\u0131rlar (Buckingham Shum ve Ferguson, 2012). \u00d6\u011frenme analiti\u011fi (\u00d6A), \u201c\u00f6\u011frenmeyi ve ger\u00e7ekle\u015fti\u011fi ortamlar\u0131 anlamak ve onlar\u0131n verimini art\u0131rmak amac\u0131yla, \u00f6\u011frenenler ve durumlar\u0131 hakk\u0131ndaki verilerin \u00f6l\u00e7\u00fcm\u00fc, toplanmas\u0131, analizi ve raporlanmas\u0131\u201dn\u0131 ama\u00e7layan, ortaya \u00e7\u0131kmakta olan metodolojik ve \u00e7ok disiplinli bir ara\u015ft\u0131rma alan\u0131d\u0131r (Siemens ve Long, 2011, s. 34).<\/span><\/p>\n

E\u011fitimde \u00d6A'n\u0131n vizyonu, \u00f6\u011frenmeyi desteklemek i\u00e7in veriyi ve uyarlanabilir pedagoji modellerini g\u00fc\u00e7lendirebilecek \u00e7ok y\u00f6nl\u00fc sistemlerdir (Baker, 2016; Berendt, Vuorikari, Littlejohn ve Margaryan, 2014). Bu sistemler, \u00f6\u011frenenlerin hedeflerine ula\u015fmalar\u0131n\u0131 desteklemek i\u00e7in dijital \u00f6\u011frenme etkinli\u011finin bir yan \u00fcr\u00fcn\u00fc olarak \u00fcretilen b\u00fcy\u00fck miktardaki verileri i\u015fler (Ferguson, 2012). Bununla birlikte, \u00fcniversite e\u011fitiminde kullan\u0131lmak \u00fczere geli\u015ftirilen sistemler, y\u00fcksek\u00f6\u011frenimin maliyeti ile ilgili kayg\u0131lara ve kazan\u0131mlar\u0131n etkilili\u011fine odaklanmas\u0131yla \u00e7ok daha basit hale gelmi\u015ftir (Nistor, Derntl ve Klamma, 2015; HEC Report, 2016). Bir\u00e7ok \u00d6A sistemi, \u00f6\u011frenenin \u201cokulu b\u0131rakma riski alt\u0131nda olup olmad\u0131\u011f\u0131n\u0131\u201d tahmin etmek i\u00e7in her bir \u00f6\u011frenenin profilini analiz eden kestirimci modellere dayanmaktad\u0131r (Siemens ve Long, 2011, s. 36; Wolff, Zdrahal, Nikolov ve Pantucek, 2013; Berendt vd.,2014; Nistor vd., 2015). Bu veriler daha sonra \u00e7e\u015fitli g\u00f6sterge panelleri arac\u0131l\u0131\u011f\u0131 ile \u00f6\u011frenenlere veya \u00f6\u011fretmenlere sunulur. Mevcut ara\u015ft\u0131rmalar, bu geri bildirimleri takip etmek i\u00e7in ger\u00e7ekle\u015ftirilen eylemlere odaklanmaktad\u0131r (Rienties vd., 2016).<\/span><\/p>\n

E\u011fitim ortamlar\u0131nda, ders hedefleri \u00f6\u011frenmenin oda\u011f\u0131d\u0131r. Ancak \u00f6rg\u00fctsel ortamlarda proje hedefleri ve \u00f6rg\u00fctsel hedeflere g\u00f6re \u00f6\u011frenme s\u00fcre\u00e7leri uyumlu hale getirilmelidir (Kimmerle, Cress ve Held, 2010). \u00d6\u011frenme, genellikle bir insan kaynaklar\u0131 b\u00f6l\u00fcm\u00fc taraf\u0131ndan denetlenen y\u0131ll\u0131k performans inceleme s\u00fcre\u00e7leri etraf\u0131nda planlanma e\u011filimindedir. Bu t\u00fcr sistemler, b\u00fcy\u00fck gruplar\u0131n standart i\u015f g\u00f6revlerinin oldu\u011fu ve benzer geli\u015ftirme etkinlikleri planlad\u0131klar\u0131 \u00f6rg\u00fctlerde iyi \u00e7al\u0131\u015f\u0131r.<\/span><\/p>\n

Bununla birlikte, bir\u00e7ok kurulu\u015fta, i\u015f rollerinde benzersiz ve ki\u015fiselle\u015ftirilmi\u015f geli\u015fim planlamas\u0131 gerektiren bir uzmanla\u015fmaya gidilmektedir. Bu durumlarda, hedeflerin ve \u00f6nceliklerin ba\u015flang\u0131\u00e7tan itibaren planland\u0131\u011f\u0131 ve s\u0131raland\u0131\u011f\u0131 \u201cyukar\u0131dan a\u015fa\u011f\u0131ya\u201d planlama modelleri etkili olmayabilir. Baz\u0131 kurulu\u015flar, kurumsal sistemleri kullanan yukar\u0131dan a\u015fa\u011f\u0131ya ve ki\u015fiselle\u015ftirilmi\u015f geli\u015fim planlamas\u0131ndan, teknolojilerin kullan\u0131m\u0131n\u0131 temel alan i\u015f birli\u011fine dayal\u0131 etkinlik planlamas\u0131na, proje ekiplerinin zaman i\u00e7inde projenin y\u00f6n\u00fcn\u00fc de\u011fi\u015ftirme takdirine sahip oldu\u011fu \"ak\u0131ll\u0131\" veya \"\u00e7evik bir \u015fekilde\" geli\u015fim planlamas\u0131na do\u011fru kaymaktad\u0131r (Clow, 2013). Bu geli\u015fim hedeflerinin her geli\u015fim d\u00f6ng\u00fcs\u00fcn\u00fcn ba\u015f\u0131nda planlanamayaca\u011f\u0131 anlam\u0131na gelir; her proje ilerledik\u00e7e yeni ve geli\u015fen \u00f6ncelikler ortaya \u00e7\u0131kmaktad\u0131r. \u00c7evik planlama sistemleri, insanlar\u0131n yeni i\u015f g\u00f6revleri i\u00e7in bu g\u00f6revler ortaya \u00e7\u0131karken ihtiya\u00e7 duyduklar\u0131 bilgileri edindikleri yerde, tam zaman\u0131nda ve uyarlanabilir \u00f6\u011frenmeyi gerektirir. Bununla birlikte, bu, profesyonellerin, i\u015fle ilgili g\u00f6revleri geli\u015ftik\u00e7e \u00f6\u011frenme \u00f6nceliklerini de\u011fi\u015ftirerek kendi \u00f6\u011frenme ve geli\u015fimlerini planlama ve \u00f6z d\u00fczenleme yapabilmeleri gerekti\u011fi anlam\u0131na gelir (Littlejohn vd., 2012).<\/span><\/p>\n\n

PROFESYONELLER NASIL \u00d6\u011eREN\u0130R<\/h2>\n

E\u011fitim ortamlar\u0131nda \u00f6\u011frenme, her bir \u00f6\u011frenenin kazan\u0131mlar\u0131 ve a\u00e7\u0131k pedagojik modellerine odaklanma e\u011filimindedir. Ancak mesleki \u00f6\u011frenme, i\u015fe y\u00f6nelik g\u00f6rev talepleri taraf\u0131ndan y\u00f6nlendirilir ve i\u015f s\u00fcre\u00e7leriyle i\u00e7 i\u00e7edir (Eraut, 2000). \u201cMesleki \u00f6\u011frenme\u201d ile profesyonellerin d\u00fc\u015f\u00fcnme ve mesleki bilgilerini te\u015fvik etmek, i\u015f performans\u0131n\u0131 geli\u015ftirmek ve uygulaman\u0131n bilgilendirilmi\u015f ve g\u00fcncel olmas\u0131n\u0131 sa\u011flamak i\u00e7in kat\u0131ld\u0131\u011f\u0131 faaliyetler anlam\u0131na gelir (Littlejohn ve Margaryan, 2013, s. 2).<\/span><\/p>\n

Profesyoneller \u00f6\u011frenmeyi uygulamal\u0131 e\u011fitim veya \u00f6rg\u00fcn \u00f6\u011frenme olarak d\u00fc\u015f\u00fcnme e\u011filimindedir (Eraut, 2000). Ancak mesleki \u00f6\u011frenmenin i\u015fe y\u00f6nelik g\u00f6revlerle b\u00fct\u00fcnle\u015fti\u011finde daha etkili oldu\u011funa dair kan\u0131tlar da artmaktad\u0131r (bk. \u00f6rne\u011fin, Collin, 2008; Tynjala, 2008; Fuller ve Unwin, 2004; Eraut, 2004). Bu t\u00fcr bir \u00f6\u011frenmenin g\u00fcnl\u00fck i\u015f g\u00f6revlerinden ay\u0131rt edilmesi zordur, bu nedenle profesyoneller \u00f6\u011frenme \u00f6rneklerini fark edemeyebilir (Argyris ve Schon, 1974; Engestrom, 1999).<\/span><\/p>\n

Eraut\u2019un \u00e7al\u0131\u015fmas\u0131 (2004), \u00f6zellikle meslek i\u00e7i \u00f6\u011frenmeyi \u201cama\u00e7l\u0131\u201d ve planlanm\u0131\u015f veya \u201cama\u00e7s\u0131z\u201d ve hali haz\u0131rdaki duruma uygun olarak tan\u0131mlad\u0131\u011f\u0131 i\u015f ba\u015f\u0131 \u00f6\u011frenmenin \u00f6nemi \u00f6n plana \u00e7\u0131kar\u0131r. Tynjala'ya (2008) g\u00f6re, ama\u00e7l\u0131 \u00f6\u011frenme \u00f6nceden planlanm\u0131\u015f ve \u00f6rg\u00fcn \u00f6\u011frenme olarak yap\u0131land\u0131r\u0131lm\u0131\u015f olabilir (\u00f6r. mezuniyet programlar\u0131, s\u0131n\u0131f e\u011fitimi, pratik at\u00f6lyeler, ko\u00e7luk veya mentorluk vb.); di\u011fer formlar\u0131n (\u00f6r. bir i\u015f arkada\u015f\u0131ndan yard\u0131m istemek veya bir uzman\u0131n bir g\u00f6revi yerine getirmesini izlemek vb.) ay\u0131rt edilmesi daha zordur. \u00d6\u011frenme, i\u015f faaliyetinin \u201cama\u00e7lanmam\u0131\u015f\u201d bir sonucu olarak ortaya \u00e7\u0131kabilir (Eraut, 2000). Finans kurulu\u015fundaki bir y\u00f6netici, d\u00fcnya \u00e7ap\u0131ndaki \u015fubelerden yeni meslekta\u015flar ekibine kat\u0131l\u0131rken k\u00fclt\u00fcrleraras\u0131 yetkinliklerini zaman i\u00e7inde art\u0131rabilir (Littlejohn ve Hood, 2016). Profesyoneller, uygulamalar\u0131n\u0131n zaman i\u00e7inde nas\u0131l geli\u015fti\u011fini yans\u0131tana kadar bu t\u00fcr deneysel \u00f6\u011frenmenin fark\u0131nda olmayabilirler. Bu farkl\u0131 mesleki \u00f6\u011frenme bi\u00e7imleri, \u015eekil 23.1'deki tipolojide g\u00f6sterilmektedir.<\/span><\/p>\n

\"\"<\/p>\n<\/a> \u015eekil 23.1. Eraut (2000, 2004) taraf\u0131ndan belirtilen mesleki \u00f6\u011frenme tipolojisi.<\/i><\/span><\/span>\n

\u015eekil 23.1'de farkl\u0131 bilgi t\u00fcrlerinin geli\u015fimini kolayla\u015ft\u0131ran \u00f6\u011frenmeye y\u00f6nelik farkl\u0131 yakla\u015f\u0131mlar g\u00f6sterilmi\u015ftir (Tynjala ve Gijbels, 2012; Littlejohn ve Hood, 2016). \u00d6rne\u011fin e\u011fitim ve uygulamal\u0131 \u00f6\u011fretim teorik ve pratik bilgi \u00f6\u011frenmeye odaklan\u0131rken, ko\u00e7luk ve mentorluk sosyo-k\u00fclt\u00fcrel ve \u00f6z y\u00f6netimli bilgileri \u00f6\u011frenme f\u0131rsatlar\u0131 sa\u011flar. T\u00fcm bu bilgi t\u00fcrleri, i\u015f i\u00e7in yeni uygulamalar\u0131n benimsenmesi i\u00e7in kritik \u00f6neme sahiptir. Uygulamadaki de\u011fi\u015fim, kavramsal ve pratik bilginin olu\u015fturulmas\u0131n\u0131n yan\u0131 s\u0131ra sosyo-k\u00fclt\u00fcrel ve \u00f6z y\u00f6netimli bilginin geli\u015fimini gerektirir (Eraut, 2007). \u00c7oklu bilgi t\u00fcrlerinin in\u015fas\u0131, informal (yap\u0131land\u0131r\u0131lmam\u0131\u015f, i\u015f ba\u015f\u0131nda) \u00f6\u011frenme ile formal (yap\u0131land\u0131r\u0131lm\u0131\u015f, \u00f6nceden planlanm\u0131\u015f) \u00f6\u011frenme etkinliklerinin bir araya getirilmesiyle elde edilir (Harteis ve Billett, 2008). Bu nedenle, i\u015fyeri \u00f6\u011frenmesi, belirli bir i\u015fyerinin imk\u00e2nlar\u0131 ile birlikte, bu imk\u00e2nlar\u0131n bireyin sahip oldu\u011fu beceri ve motivasyonla ili\u015fkilendirilmesi (Billett, 2004; Fuller ve Unwin, 2004) ile \u015fekillenen kar\u015f\u0131l\u0131kl\u0131 bir s\u00fcre\u00e7 (Billett, 2004) olarak \u00e7al\u0131\u015f\u0131r.<\/span><\/p>\n

Mesleki \u00f6\u011frenme s\u00fcre\u00e7leri, e\u011fitim ortamlar\u0131nda oldu\u011fundan daha dinamiktir; yayg\u0131n \u00f6\u011frenme etkinlikleri kendili\u011findendir ve \u00e7o\u011funlukla di\u011ferleri i\u00e7in g\u00f6r\u00fcn\u00fcr de\u011fildir. Bu \u00d6A alan\u0131 i\u00e7in zorluklar ve f\u0131rsatlar sunmaktad\u0131r.<\/span><\/p>\n\n

MESLEK\u0130 \u00d6\u011eRENME ANAL\u0130T\u0130\u011e\u0130 \u0130\u00c7\u0130N B\u0130R V\u0130ZYON<\/h2>\n

Profesyonel ba\u011flamlarda \u00d6A i\u00e7in temel vizyon, her bir uzmana ihtiya\u00e7 duyduklar\u0131 bilgiyle ba\u011flant\u0131 kurmak i\u00e7in hem formal hem de informal \u00f6\u011frenme s\u00fcre\u00e7lerini izlenebilir ve daha a\u00e7\u0131k hale getirmektir (Littlejohn vd., 2012; de Laat ve Schreurs, 2013). Bu vizyon, her bir profesyonelin, ilgili bilgi ve deneyimleri bulmak i\u00e7in insanlarla ve a\u011flarla ba\u011flant\u0131<\/i><\/span> kurarak kolektif bilgiye ba\u011fland\u0131\u011f\u0131 ve katk\u0131da bulundu\u011fu kar\u015f\u0131l\u0131kl\u0131 destek sistemine dayanmaktad\u0131r; bu bilgiyi kullanmak veya t\u00fcketmek<\/i><\/span>, s\u00fcre\u00e7 i\u00e7inde toplulu\u011fa katk\u0131 sunacak geri d\u00f6nen yeni bilgiler olu\u015fturmakt\u0131r<\/i><\/span> (Milligan, Littlejohn ve Margaryan, 2014). Bu eylemler, ba\u015flang\u0131\u00e7ta ki\u015fisel fayda taraf\u0131ndan motive edilmesiyle ortaya \u00e7\u0131kan bireysel faaliyetlerin yan \u00fcr\u00fcnlerinden se\u00e7ici olarak biriktirilen yeniden kullan\u0131labilir bilgiler arac\u0131l\u0131\u011f\u0131yla ortak bir sermaye yarat\u0131r (Convertino, Grasso, DiMicco, De Michelis ve Chi, 2010, s. 15). Bu eylemler \u201cba\u015flang\u0131\u00e7ta ki\u015fisel fayda taraf\u0131ndan motive edilmesiyle ortaya \u00e7\u0131kan bireysel faaliyetlerin yan \u00fcr\u00fcnlerinden se\u00e7ici olarak biriktirilen yeniden kullan\u0131labilir bilgiler arac\u0131l\u0131\u011f\u0131yla ortak bir sermaye\" yaratan bir dizi algoritma, veri madencili\u011fi mekanizmas\u0131 ve analitikler taraf\u0131ndan desteklenecektir (Convertino vd., 2010, s. 15).<\/span><\/p>\n

Mesleki \u00f6\u011frenme, \u00f6\u011frenenin kolektif bilgi ve \u00e7evresi ile ba\u011flant\u0131 kurma ve etkile\u015fime girme konusundaki i\u00e7 motivasyonundan ve bireysel iradesinden etkilenir (Littlejohn ve Hood, 2016), bu nedenle bu vizyonun iki \u00f6nemli bile\u015feni vard\u0131r. Birincisi, bireysel irade ortaya koyulabilmesi i\u00e7in profesyonellerin \u00f6\u011frenmelerinde \u00f6z y\u00f6netim becerisine sahip olmalar\u0131 \u00e7ok \u00f6nemlidir. \u0130kincisi, motivasyonu tetiklemek i\u00e7in, \u00f6\u011frenme (ve \u00f6\u011frenme sistemleri) i\u015f uygulamalar\u0131 ile ayr\u0131\u015ft\u0131r\u0131lmamal\u0131 aksine b\u00fct\u00fcnle\u015ftirilmelidir. Bu vizyona ula\u015fma yolunda, ge\u00e7ti\u011fimiz birka\u00e7 y\u0131l boyunca Mesleki \u00d6A'ya y\u00f6nelik bir dizi yakla\u015f\u0131m geli\u015ftirilmi\u015ftir.<\/span><\/p>\n\n

Uygulamada Analitikler<\/h3>\n

\u00d6A, \u00f6\u011frenme bilimi, bilgisayar biliminden, bilgi biliminden, e\u011fitsel veri madencili\u011finden, bilgi y\u00f6netimi vurgusu\" ve daha yak\u0131n bir zamanda yapay zek\u00e2dan fikirler kullanan \u00e7ok disiplinli bir aland\u0131r (Gillani ve Enyon, 2014). Analitikte ortaya \u00e7\u0131kan alanlar s\u00f6ylem verileri, \u00f6\u011frenenlerin e\u011filim verileri ve biyometri gibi \u00e7oklu veri t\u00fcrlerini i\u00e7eren karma\u015f\u0131k veri k\u00fcmelerinden faydalanmaktad\u0131r (Siemens ve Long, 2011). \u00d6A'da kullan\u0131lan teknikler \u00f6\u011frenenlerin tart\u0131\u015fma ve eylemlerinin yard\u0131mc\u0131 m\u00fcdahaleler i\u00e7in f\u0131rsat sa\u011flad\u0131\u011f\u0131 s\u00f6ylem analizini (Gillani ve Enyon, 2014); \u00f6\u011frenenlerle \u00f6\u011frenme aras\u0131ndaki ili\u015fkiyi izleyen anlamsal analizi, (Wen, Yang ve Rose, 2014), \u00f6\u011frenmeyle ili\u015fkili duygusal \u00f6zellikleri belirleyen \u00f6\u011frenen e\u011filim analiti\u011fi (Buckingham Shum ve Deakin Crick, 2012) ve \u00f6\u011frenenler taraf\u0131ndan sa\u011flanan etiketleri ve puanlamalar\u0131 temel alarak i\u00e7eri\u011fi filtreleyen ve sunan \u00f6neri sistemleri de d\u00e2hil olmak \u00fczere i\u00e7erik analiti\u011fini kapsar. Bu teknikler, profesyonellerin nas\u0131l \u00f6\u011frendiklerini etkileyen karma\u015f\u0131k fakt\u00f6rleri ayr\u0131\u015ft\u0131rmak i\u00e7in kullan\u0131\u015fl\u0131d\u0131r.<\/span><\/p>\n

\u00d6A'na y\u00f6nelik \u00e7e\u015fitli yakla\u015f\u0131mlar, alandaki farkl\u0131 i\u015f ortamlarda test edilmi\u015ftir. Baz\u0131 y\u00f6ntemler, dijital sistemlerde \u00f6\u011frenmenin bir yan \u00fcr\u00fcn\u00fc olarak \u00fcretilen verilere b\u00fcy\u00fck \u00f6nem verir. Di\u011ferleri bireylerin ve gruplar\u0131n yeni bilgileri nas\u0131l \u00f6\u011frendi\u011fini ve geli\u015ftirdi\u011fini inceleyen sosyal \u00f6\u011frenme analiti\u011fi (S\u00d6A) gibi yeni yakla\u015f\u0131mlar kullanmaktad\u0131r. Bu y\u00f6ntemler ve sistemler yeni d\u00fczenleme \u015fekillerinden, farkl\u0131 geri bildirim bi\u00e7imlerinden, \u00f6\u011frenme ve i\u015f i\u00e7in insanlar\u0131n ihtiya\u00e7 duyduklar\u0131 kaynaklar\u0131 bir araya getirmenin say\u0131s\u0131z yollar\u0131ndan yararlanmaktad\u0131r. Bunlar\u0131n bir\u00e7o\u011fu geli\u015fimlerinin erken a\u015famalar\u0131ndad\u0131r ve bu b\u00f6l\u00fcm farkl\u0131 yakla\u015f\u0131mlar\u0131 ve bunlar\u0131n \u00f6\u011frenme ve performans \u00fczerindeki etkilerini incelemektedir.<\/span><\/p>\n\n

An\u0131nda \u00d6\u011frenmeyi H\u0131zland\u0131rma<\/h3>\n

M\u00d6A'na y\u00f6nelik baz\u0131 yakla\u015f\u0131mlar, \u00e7evik yakla\u015f\u0131mlar\u0131n i\u015f ortam\u0131ndaki mesleki \u00f6\u011frenmeye d\u00e2hil edilmesini hedeflemektedir. Bir\u00e7ok kurulu\u015f \u00e7al\u0131\u015fanlar yeni bir y\u00f6ntem \u00f6\u011frendikleri halde bu yeni bilgilerini kullanmad\u0131klar\u0131 ve uygulamalar\u0131na yerle\u015ftirmedikleri takdirde e\u011fitimin etkili olmad\u0131\u011f\u0131n\u0131 kabul etmektedir. \u0130nsanlar\u0131n ihtiya\u00e7 noktas\u0131nda yeni uzmanl\u0131k \u00f6\u011frenmelerini sa\u011flaman\u0131n \u00f6nemini kabul ederek, kurulu\u015flar uzmanl\u0131\u011f\u0131 yakalamak ve yaymak i\u00e7in yollar aramaktad\u0131rlar.<\/span><\/p>\n

Bilgi Yo\u011funluklu E\u011fitim \u0130\u00e7in Giyilebilir Deneyim <\/i><\/span>(BYEGD)1<\/a><\/sup>, ak\u0131ll\u0131 Giyilebilir Teknoloji ile \u00fcretilen verilerin uzmanl\u0131\u011f\u0131 yakalay\u0131p yakalayamad\u0131\u011f\u0131n\u0131 ve ihtiya\u00e7 duydu\u011fu yerde deneyimsiz profesyonellere bilgiyi ula\u015ft\u0131r\u0131p ula\u015ft\u0131ramad\u0131\u011f\u0131n\u0131 ve t\u00fcm bu s\u00fcre\u00e7lerin nas\u0131l ger\u00e7ekle\u015fti\u011fini ara\u015ft\u0131rmaktad\u0131r. BYEGD, \u00fc\u00e7 a\u015famal\u0131 bir s\u00fcrece dayan\u0131r: beceri geli\u015ftirme yollar\u0131n\u0131n haritalanmas\u0131, uzmanl\u0131\u011f\u0131n yakalanmas\u0131 ve sistemle\u015ftirilmesi ve ihtiya\u00e7 duyuldu\u011fu noktada deneyimsiz ki\u015filere uzmanl\u0131k sunulmas\u0131. \u0130lk a\u015famada, uzmanlar ve payda\u015f toplulu\u011fu2<\/a><\/sup> end\u00fcstri i\u00e7in tan\u0131nm\u0131\u015f bir beceri geli\u015ftirme yollar\u0131n\u0131n haritas\u0131n\u0131 \u00e7\u0131kar\u0131r. \u0130kinci a\u015famada, bir grup yaz\u0131l\u0131m geli\u015ftirici, yeni bir i\u015flemsel bilgisinin \u00f6\u011frenilmesinde -\u00f6rne\u011fin \u00f6zellikli bir vanan\u0131n nas\u0131l a\u00e7\u0131laca\u011f\u0131n\u0131n (veya kapat\u0131laca\u011f\u0131n\u0131n) acemileri desteklemek \u00fczere teknoloji ara\u00e7lar\u0131n\u0131 geli\u015ftirmek i\u00e7in- yol haritalar\u0131n\u0131 kullan\u0131r. Son olarak, yetenek ve deneyim acemilere zenginle\u015ftirilmi\u015f bir g\u00f6rsel aray\u00fcz ile aktar\u0131l\u0131r. Ba\u015fa tak\u0131labilen dijital ekranlar gibi ara\u00e7lar, aceminin vanay\u0131 ekranda g\u00fcvenli bir \u015fekilde a\u00e7maya ili\u015fkin talimatlar ile b\u00fct\u00fcnle\u015ftirilmi\u015f olarak g\u00f6rmesini sa\u011flar. Giyilebilir ve g\u00f6rsel cihazlar sayesinde sistem, her profesyonelin dikkatini, kullan\u0131c\u0131 ihtiya\u00e7 analizine dayanarak en \u00e7ok ihtiya\u00e7 duyulan yere y\u00f6nlendirir. Sistem, informal \u00f6\u011frenme s\u00fcre\u00e7lerini izlenebilir ve tan\u0131nabilir hale getirmeyi ama\u00e7lamaktad\u0131r, b\u00f6ylece acemiler h\u0131zl\u0131 bir \u015fekilde uzmanl\u0131k kazanabilir. Bu \u015fekilde, ihtiya\u00e7 ortaya \u00e7\u0131kt\u0131k\u00e7a \u00f6\u011frenme \u00e7evik olabilir.<\/span><\/p>\n

BYEGD projesine 2015 Aral\u0131k ay\u0131nda ba\u015flanm\u0131\u015f ve bu yakla\u015f\u0131m\u0131n etkilili\u011fi ile ilgili de\u011ferlendirmeleri hen\u00fcz yay\u0131nlanmam\u0131\u015ft\u0131r. Bununla birlikte, BYEGD metodolojisindeki uzmanl\u0131k aktar\u0131m\u0131ndaki \u00fc\u00e7 \u00f6nemli ad\u0131mla ili\u015fkilendirilmi\u015f riskler vard\u0131r. \u0130lk olarak, uzmanl\u0131k geli\u015ftirme yollar\u0131n\u0131n modellenmesi zordur. Uzmanlar, uzmanl\u0131\u011f\u0131 do\u011fru bir \u015fekilde yakalamak ve sistemle\u015ftirmek, uzmanl\u0131k geli\u015fimini desteklemek i\u00e7in yollar ve algoritmalar olu\u015fturmaya kat\u0131lmaktad\u0131rlar. Bununla birlikte, bir uzman\u0131n, her aceminin uzmanl\u0131k geli\u015fimine katk\u0131 sa\u011flayacak en uygun \u00f6\u011frenme yolunu anlamas\u0131 zordur, \u00e7\u00fcnk\u00fc bu aceminin \u00f6nceki deneyimine ba\u011fl\u0131d\u0131r. \u0130kincisi, her uzmanl\u0131k sistemle\u015ftirilemez. Ger\u00e7ekli\u011fi art\u0131r\u0131lm\u0131\u015f g\u00f6rsel aray\u00fczler ve i\u015fbirlikli say\u0131sal aray\u00fczler, uzmanl\u0131k geli\u015fimine yard\u0131mc\u0131 olabilir ancak bir ekipman\u0131n en iyi \u015fekilde \u00e7al\u0131\u015ft\u0131\u011f\u0131na y\u00f6nelik \u201ci\u00e7g\u00fcd\u00fcsel\u201d bir uzmanl\u0131\u011f\u0131n geli\u015ftirilmesi zaman al\u0131r. \u00dc\u00e7\u00fcnc\u00fcs\u00fc, bir aceminin basit\u00e7e talimatlar\u0131 izlemektense yeni uzmanl\u0131k \u00f6\u011frenmeye aktif olarak d\u00e2hil olmas\u0131 gerekir. Bu \u00f6zellikle teorik bilgilerle i\u015fin sonu\u00e7lar\u0131n\u0131n tahmin edilmesinin zor oldu\u011fu \u00e7al\u0131\u015fma ortamlar\u0131yla ilgilidir. Bu durumlardaki en etkili \u00f6\u011frenme i\u015f g\u00f6revleriyle b\u00fct\u00fcnle\u015ftirildi\u011finde ortaya \u00e7\u0131kar. Bu nedenle, ortaya \u00e7\u0131kan bir e\u011filim M\u00d6A'y\u0131 i\u015fle b\u00fct\u00fcnle\u015fmi\u015f sistemlere (ortak \u00e7al\u0131\u015fmalarda uzmanlar\u0131 ve acemileri destekleyen ortamlar, daha \u00f6nce de a\u00e7\u0131kland\u0131\u011f\u0131 gibi ak\u0131ll\u0131 sistemler veya gibi art\u0131r\u0131lm\u0131\u015f ger\u00e7eklik ortamlar\u0131) yerle\u015ftirmektir.<\/span><\/p>\n\n

\u00d6rg\u00fctsel A\u011flar\u0131 Kullanma<\/h3>\n

Gayriresm\u00ee mesleki a\u011flara ba\u011flant\u0131 kurarak, insanlar Clow (2013) taraf\u0131ndan tarif edilen \u00e7evik \u00f6\u011frenme t\u00fcr\u00fcn\u00fc ba\u015farabilirler. Mesleki geli\u015fime y\u00f6nelik bu \u00f6zerk, a\u015fa\u011f\u0131dan yukar\u0131ya yakla\u015f\u0131m t\u00fcr\u00fc, profesyonellerin nas\u0131l ve nerede etkile\u015fime girdiklerini ve \u00e7al\u0131\u015fmalar\u0131 hakk\u0131nda fikir al\u0131\u015fveri\u015finde bulunduklar\u0131n\u0131 derinlemesine anlamay\u0131 gerektirir. \u0130nformal \u00f6\u011frenme uygulama ve a\u011flar\u0131n\u0131 g\u00f6r\u00fcn\u00fcr k\u0131lmak M\u00d6A i\u00e7in temel bir ama\u00e7t\u0131r. de Laat ve Schreurs (2013), \u00d6A tekniklerinin resm\u00ee olmayan profesyonel a\u011flar\u0131 g\u00f6rselle\u015ftirebildi\u011fini g\u00f6stermi\u015ftir. Sosyal a\u011f analizine dayanan bir ara\u00e7 kullanarak -a\u011f fark\u0131ndal\u0131\u011f\u0131 gereci (AFG)- tek bir kurulu\u015f i\u00e7inde birden fazla izole edilmi\u015f \u00f6\u011freten a\u011f\u0131n\u0131 tespit ettiler. Daha yeni yap\u0131lan \u00e7al\u0131\u015fmalar, sa\u011fl\u0131k bak\u0131m\u0131 ortamlar\u0131ndaki profesyonel a\u011flar\u0131 izlemek i\u00e7in giyilebilir cihazlar kullanmaktad\u0131r (Endedijk, 2016). Bu gayriresm\u00ee profesyonel a\u011flardan yararlanarak, kurulu\u015flar\u0131n be\u015feri sosyal sermayesini ve \u00f6\u011frenmesini iyile\u015ftirme mekanizmalar\u0131 vard\u0131r. Bununla birlikte, \u00e7al\u0131\u015fma profesyonel a\u011flar aras\u0131ndaki s\u0131n\u0131rl\u0131 ba\u011flant\u0131lar\u0131n kapsam\u0131n\u0131 g\u00f6stermektedir, bu nedenle a\u011flardan yararlanmak i\u00e7in birden fazla y\u00f6nteme ihtiya\u00e7 vard\u0131r.<\/span><\/p>\n

\u00d6\u011frenme Katmanlar\u0131<\/i><\/span>3<\/a><\/span><\/sup> performans\u0131 art\u0131rmak i\u00e7in a\u011flar\u0131 ve ili\u015fkileri bireysel, \u00f6rg\u00fct ve \u00f6rg\u00fctler aras\u0131 seviyelerde kullan\u0131r. Farkl\u0131 Avrupa \u00fclkelerindeki b\u00f6lgesel k\u00fc\u00e7\u00fck ve orta b\u00fcy\u00fckl\u00fckteki i\u015fletmelerin (KOB\u0130'ler) i\u00e7inde ve aras\u0131nda \u00e7al\u0131\u015fan profesyoneller, fikir ve bilgi olu\u015fturmak i\u00e7in web tabanl\u0131, a\u011f ortam\u0131nda \u00e7al\u0131\u015f\u0131r. Sistem, insanlar\u0131 birbirine ba\u011flayarak ve tavsiyelerde bulunarak bilginin birlikte \u00fcretilmesini analiz etmek ve desteklemek i\u00e7in semantik teknolojilerden yararlan\u0131r (Ley vd., 2014).<\/span><\/p>\n

Sa\u011fl\u0131k ve in\u015faat sekt\u00f6rlerinde test edilen teknoloji ortamlar\u0131, profesyonellerin \u00fc\u00e7 d\u00fczeyde birlikte \u00e7al\u0131\u015fma ve \u00f6\u011frenme yollar\u0131n\u0131 g\u00f6stermektedir. \u0130nsanlar birlikte \u00e7al\u0131\u015ft\u0131k\u00e7a, yeni i\u015f g\u00f6revlerini nas\u0131l yerine getireceklerine dair bilin\u00e7li se\u00e7imler yapmalar\u0131na yard\u0131mc\u0131 olmak \u00fczere teknik bilgi (neyi bilirim), i\u015flemsel veya uygulamaya y\u00f6nelik bilgi (nas\u0131l yapar\u0131m) ve bilimsel veya teorik bilgi (neden b\u00f6yle) gibi farkl\u0131 t\u00fcrden bilgiler geli\u015ftirmeyi \u00f6\u011frenirler (Attwell vd., 2013). \u00d6rg\u00fctsel d\u00fczeyde, insanlar farkl\u0131 KOB\u0130'ler aras\u0131nda i\u015f birli\u011fi yaparken, her bir kurulu\u015f bilgi payla\u015f\u0131r ve \u00f6\u011frenir. \u00dc\u00e7\u00fcnc\u00fcs\u00fc, \u015firketler ulusal k\u00fcmelenmeler halinde grupland\u0131r\u0131lm\u0131\u015ft\u0131r, bu nedenle \u00f6\u011frenme \u00f6rg\u00fctler aras\u0131nda ger\u00e7ekle\u015fir (Dennerlein vd., 2015). \u00d6A ara\u00e7lar\u0131, profesyonellerin kendisiyle ve kilit payda\u015flarla birlikte geli\u015ftirilmektedir. A\u00e7\u0131k bir tasar\u0131m k\u00fct\u00fcphanesi,4<\/a><\/sup> profesyonel \u00f6\u011frenmeye y\u00f6nelik fikirleri saklamak ve yaymak i\u00e7in kullan\u0131l\u0131rken, a\u00e7\u0131k bir geli\u015ftirici k\u00fct\u00fcphanesi5<\/a><\/sup>, geli\u015ftiricilerin \u00fczerinde \u00e7al\u0131\u015fmas\u0131 i\u00e7in prototip ara\u00e7lar\u0131 ve kodlar\u0131 bar\u0131nd\u0131r\u0131r. \u00c7ok \u00f6zel rolleri i\u00e7in \u00f6\u011frenme hakk\u0131nda en iyi bilgiye sahip profesyoneller kendilerini prensibi bir\u00e7ok \u00d6A sistemler ve ara\u00e7lar i\u00e7in merkezi.<\/span><\/p>\n\n

\u00d6zel Uzmanl\u0131\u011f\u0131ndan Yararlanma<\/h3>\n

Profesyonellerin \u00e7al\u0131\u015fmalar\u0131nda ve \u00f6\u011frenmelerinde de\u011fi\u015fiklik ve belirsizliklere uyum sa\u011flamalar\u0131 ve bunlarla ba\u015fa \u00e7\u0131kmalar\u0131 i\u00e7in Duyarl\u0131 A\u00e7\u0131k \u00d6\u011frenme Ortamlar\u0131 (DA\u00d6O)6<\/a><\/sup> geli\u015ftirilmektedir (Kirschenmann, Scheffel, Friedrich, Niemann ve Wolpers, 2010). Her \u015feyi kapsayan bir i\u015fletme sistemi kullanmak yerine, \u00f6\u011frenme ortam\u0131 her bir \u00f6\u011frenen taraf\u0131ndan ki\u015fiselle\u015ftirilebilir. Her profesyonel, belirli bir rol i\u00e7in \u00f6\u011frenmeyi destekleyen belirli i\u015flevlere sahip bir dizi web tabanl\u0131 yaz\u0131l\u0131m arac\u0131n\u0131 tarayabilir ve se\u00e7ebilir. Ara\u00e7lar, yeni bile\u015fenler ve i\u015flevler olu\u015fturmak i\u00e7in birle\u015ftirilebilir. Uzman, ara\u00e7lar\u0131n ve kaynaklar\u0131n benzersiz bir kombinasyonunu olu\u015fturarak, \u00e7evreye kendi uzmanl\u0131\u011f\u0131n\u0131 kazand\u0131r\u0131r. Bu ara\u00e7 ve kaynak kombinasyonu, benzer i\u015f ve \u00f6\u011frenme ihtiya\u00e7lar\u0131 olan di\u011fer profesyonelleri desteklemek i\u00e7in \u00e7o\u011falt\u0131labilir ve uyarlanabilir.<\/span><\/p>\n

DA\u00d6O'yi destekleyen temel ilke iyi tan\u0131mlanm\u0131\u015ft\u0131r; uzmanl\u0131k rollerinde, profesyonellerin kendileri \u00f6\u011frenme ihtiya\u00e7lar\u0131na en iyi \u015fekilde karar verebileceklerdir (Kroop, Mikroyannidis ve Wolpers, 2015). Ancak profesyonel bir \u00f6\u011frenme bak\u0131\u015f a\u00e7\u0131s\u0131na g\u00f6re, iki ana genel zorluk vard\u0131r. \u0130lk olarak, profesyoneller kararlar\u0131n\u0131 uygulama becerisine sahip olmayabilirler. DA\u00d6O, mesleki \u00f6\u011frenmenin belirli y\u00f6nlerini destekleyen teknoloji ara\u00e7lar\u0131n\u0131n veya ara\u00e7 gere\u00e7lerin geli\u015ftirilmesine izin veren a\u00e7\u0131k bir \u00e7er\u00e7eveye dayanmaktad\u0131r. Bu ekran ara\u00e7lar\u0131 geli\u015ftiricilerin yeni ara\u00e7lar ve i\u015flevler geli\u015ftirmeleri i\u00e7in te\u015fvik edildi\u011fi a\u00e7\u0131k yar\u0131\u015fmalar yoluyla geli\u015ftirilir. \u0130deal olarak, i\u015f rol\u00fcn\u00fc derinlemesine anlayan geli\u015ftiriciler ekran ara\u00e7lar\u0131 geli\u015ftirecektir : profesyoneller kendileri widget'lerin algoritmalar\u0131n\u0131 yazabiliyorlarsa, uzmanl\u0131klar\u0131 kodun i\u00e7ine g\u00f6m\u00fcl\u00fcr. Bununla birlikte, t\u00fcm profesyoneller kod yazamaz, bu y\u00fczden bir\u00e7ok meslek i\u00e7in ara\u00e7lar\u0131 i\u015f rol\u00fcn\u00fc derinlemesine anlamayan insanlar taraf\u0131ndan geli\u015ftirme e\u011filimindedir. \u0130kinci zorluk, profesyonellerin \u00f6\u011frenme ihtiya\u00e7lar\u0131n\u0131 tan\u0131mlamak ve bunlara g\u00f6re hareket etmek zorunda olmalar\u0131d\u0131r. DA\u00d6O ortam\u0131, \u00f6z y\u00f6netim bir \u00f6\u011frenen olma yolunda bir dersi i\u00e7erir7<\/a><\/sup>. Bununla birlikte, bir problem, \u00f6\u011frenme hedeflerini belirleme stratejileri geli\u015ftirmek gibi, \u00f6z y\u00f6netimin baz\u0131 y\u00f6nlerinin \u00f6\u011frenilebilmesine ra\u011fmen, ya\u015fam boyu s\u00fcren deneyimler yoluyla \u00f6z g\u00fcven gibi di\u011fer \u00f6z y\u00f6netim y\u00f6nlerinin geli\u015ftirilmesidir.<\/span><\/p>\n\n

Aktif \u00d6\u011frenmeyi Te\u015fvik Etmek<\/h3>\n

\u00d6z y\u00f6netimli \u00f6\u011frenme teorisine dayanan di\u011fer iki \u00d6A sistemi \u00f6rne\u011fi LearnB<\/i><\/span> ve Mirror'd\u0131r. LearnB<\/i><\/span> otomotiv end\u00fcstrisinde pilot olmu\u015ftur (Siadaty, Ga\u0161evi\u0107 ve Hatala, 2016). Bu arac\u0131n \u00f6nceki sistemlerle ortak noktas\u0131, profesyonelleri \u00f6\u011frenmelerini kendileri d\u00fczenleme konusunda te\u015fvik etmesidir. Ara\u00e7, \u00f6z y\u00f6netime etki eden fakt\u00f6rler hakk\u0131nda veri toplamak i\u00e7in kullan\u0131lan. \u00f6z y\u00f6netimli \u00f6\u011frenme \u00e7er\u00e7evesi olan \u00d6Y\u00d6@Work etraf\u0131nda tasarlanm\u0131\u015ft\u0131r. Bu fakt\u00f6rler, \u00f6\u011frenme hedeflerinin nas\u0131l planland\u0131\u011f\u0131n\u0131 ve insanlar\u0131n i\u015f i\u00e7in bilgi payla\u015f\u0131rken ve olu\u015ftururken kat\u0131ld\u0131\u011f\u0131 spesifik faaliyetler yelpazesini i\u00e7erir. LearnB, benzer \u00f6\u011frenme ve geli\u015fim hedeflerine sahip insanlar\u0131 belirlemek ve ba\u011flamak i\u00e7in Sosyal Anlam Web teknolojilerini kullanarak bu verileri toplar ve analiz eder (Siadaty vd., 2012). Ortak hedefler, sistemin anlamsal yeteneklerini kullanarak belirlenir ve analiz edilir. Daha sonra, sistem, ba\u015fkalar\u0131n\u0131n \u00f6\u011frenme \u00f6r\u00fcnt\u00fclerine dayanarak, insanlar\u0131n \u00f6\u011frenmeden yarar sa\u011flayabilecekleri konular \u00f6nermek i\u00e7in sosyal teknolojileri kullan\u0131r.<\/span><\/p>\n

LearnB sistemi, profesyonellerin di\u011fer insanlarla ve ilgili bilgilerle potansiyel olarak faydal\u0131 ba\u011flant\u0131lar kurmas\u0131n\u0131 ve de\u011ferlendirmesini sa\u011flayan bir \u201cgeli\u015fimsel radar\u201d i\u015flevi g\u00f6r\u00fcr (Siadaty, Jovanovi\u0107, Ga\u0161evi\u0107, Jeremic ve Holocher-Ertl, 2010; Holocher-Ertl vd., 2012). \u00d6\u011frenme ilerlemelerini takip ederken profesyonellere \u00f6\u011frenme stratejileri konusunda tavsiyede bulunmak i\u00e7in kullan\u0131labilir. Buradaki fikir, insanlar\u0131n benzer deneyime sahip di\u011fer insanlar i\u00e7in etkili olan stratejileri kullanarak etkili bir \u015fekilde \u00f6\u011frenebilecekleridir. Sistem, sadece \u00f6\u011frenme deneyimlerini belgelemekle kalmay\u0131p ayn\u0131 zamanda gelecekte de benzer \u015fekilde \u00f6\u011frenmeden faydalanabilecek ba\u015fkalar\u0131 i\u00e7in bu deneyimleri m\u00fcmk\u00fcn k\u0131lmak i\u00e7in profesyonelleri desteklemektedir. \u00d6\u011frenme deneyimlerini belgeleyerek, ba\u015fkalar\u0131n\u0131n performans\u0131n\u0131 veya k\u0131yaslama \u00f6l\u00e7\u00fctleriyle kar\u015f\u0131la\u015ft\u0131rmak ve kar\u015f\u0131la\u015ft\u0131rmak m\u00fcmk\u00fcnd\u00fcr. \u00d6rne\u011fin, yeni bir prosed\u00fcrde yetkin olman\u0131n ortalama alt\u0131 ayl\u0131k bir deneyime sahip oldu\u011funu bilmek faydal\u0131 olabilir. Di\u011fer yandan, birka\u00e7 saat i\u00e7inde yeni bir beceri \u00f6\u011frenilebilece\u011fini bilmek g\u00fcven verici olabilir (Siadaty vd., 2012).<\/span><\/p>\n

B \u00d6\u011frenmesi deneyi, sistemi profesyonellerin \u00f6z y\u00f6netimli \u00f6\u011frenme becerilerinin aktif geli\u015fimi ile b\u00fct\u00fcnle\u015ftirmenin \u00f6nemini g\u00f6stermi\u015ftir. B \u00d6\u011freneni kullanan profesyoneller, dikkatlerini, \u00e7al\u0131\u015ft\u0131klar\u0131 ortamlardan farkl\u0131 ba\u011flamlarda veya b\u00f6l\u00fcmlerden kaynaklanan, yararl\u0131 bilgilere y\u00f6nelttiler. Ayr\u0131ca, di\u011fer insanlar\u0131n \u00f6\u011frendikleri \u00e7al\u0131\u015fma bi\u00e7imlerini anlamalar\u0131na yard\u0131mc\u0131 olan di\u011fer insanlar\u0131n gayriresm\u00ee \u00e7al\u0131\u015fmalar\u0131 ve \u00f6\u011frenme uygulamalar\u0131 hakk\u0131ndaki verilere eri\u015fimin yararl\u0131 oldu\u011funu da alg\u0131lad\u0131lar. Sosyal ba\u011flamlar\u0131 -\u00f6rne\u011fin, ba\u015fkalar\u0131n\u0131n \u00f6\u011frenmek i\u00e7in yapt\u0131klar\u0131 eylemlerden haberdar olma- hakk\u0131ndaki g\u00fcncellemelerden ve mevcut \u00f6\u011frenme kaynaklar\u0131n\u0131n meslekta\u015flar\u0131 taraf\u0131ndan nas\u0131l kullan\u0131ld\u0131\u011f\u0131 hakk\u0131nda bilgilendirilmekten yararland\u0131klar\u0131n\u0131 alg\u0131lad\u0131lar (Siadaty, 2013). Bununla birlikte, kritik bir nokta, bu profesyonellerin, organizasyonun her i\u015f rol\u00fc i\u00e7in gereken yetkinlikleri \u00f6nceden belirledi\u011fi ve insanlar\u0131n nas\u0131l g\u00f6sterdi\u011fini \u00f6nerdi\u011fi \u00f6neride bulundu\u011fu Clow (2013) taraf\u0131ndan tart\u0131\u015f\u0131lan \u201cyukar\u0131dan a\u015fa\u011f\u0131\u201d yeterlilik sistemleriyle geleneksel bir \u00f6rg\u00fct k\u00fclt\u00fcr\u00fcnde faaliyet g\u00f6sterdikleridir. bu yetenekleri \u00f6\u011frenirler.<\/span><\/p>\n

Mirror8<\/a><\/sup>, profesyonellerin kendi deneyimlerinden ve di\u011fer deneyimlerden \u00f6\u011frenmelerini destekleyen analitik tabanl\u0131 bir sistemdir. Yans\u0131tma, motivasyon ve duyu\u015fsal fakt\u00f6rlerle \u00f6\u011frenmeyi ve performans\u0131 geli\u015ftirebilecek \u00f6z y\u00f6netimli \u00f6\u011frenmenin \u00f6nemli bir bile\u015fenidir (Littlejohn ve Hood, 2016). Ayna sistemi, \u00e7al\u0131\u015fma s\u0131ras\u0131nda informal \u00f6\u011frenmeyi kolayla\u015ft\u0131rmak i\u00e7in tasarlanm\u0131\u015f bir dizi uygulamaya (\u201cAyna\u201d uygulamalar\u0131) dayanmaktad\u0131r (Kump, Knipfer, Pammer, Schmidt ve Maier, 2011). Bu uygulamalar, \u00e7al\u0131\u015fan ayarlar\u0131nda bireysel ve ekip eylemlerinin analizini desteklemek i\u00e7in kullan\u0131lm\u0131\u015ft\u0131r. Bu yans\u0131malar hem bireylerin hem de ekiplerin, hangi uygulamalar\u0131n kurulu\u015flar\u0131 i\u00e7inde en fazla etkiye sahip oldu\u011funu \u00f6\u011frenmelerini sa\u011flad\u0131. De\u011ferlendirme \u00e7al\u0131\u015fmalar\u0131, bireysel ve tak\u0131m \u00f6\u011frenme ile \u00f6rg\u00fctsel \u00f6\u011frenme (insan kaynaklar\u0131 s\u00fcre\u00e7leri, \u00f6d\u00fcller ve promosyonlarla ba\u011flant\u0131l\u0131) aras\u0131nda a\u00e7\u0131k bir ba\u011flant\u0131 bulmu\u015ftur (Knipfer, Kump, Wessel ve Cress, 2013). K\u00fclt\u00fcrdeki ve organizasyon i\u00e7indeki insanlar\u0131n zihniyetlerinde paralel bir de\u011fi\u015fim olmazsa, yeni analitik sistemlerinin s\u0131n\u0131rl\u0131 etkisi olacakt\u0131r.<\/span><\/p>\n\n

SONU\u00c7: GELECEK MESLEK\u0130 \u00d6\u011eRENME ANAL\u0130T\u0130\u011e\u0130<\/h2>\n

Los Angeles'a yeni yakla\u015f\u0131mlar zaten profesyonelleri performanslar\u0131n\u0131 geli\u015ftirmeye desteklemektedir. Bu yakla\u015f\u0131mlar\u0131n analizi gelecekteki \u00e7al\u0131\u015fmalar\u0131 bilgilendirebilecek yeni ortaya \u00e7\u0131kan temalara i\u015faret etmektedir.<\/span><\/p>\n

Analitik i\u00e7in \u00e7e\u015fitli yakla\u015f\u0131mlar, insan zek\u00e2s\u0131n\u0131 geli\u015ftirmek i\u00e7in makine bazl\u0131 analiti\u011fi kullan\u0131r. Bununla birlikte, sistem ile insan aras\u0131ndaki ba\u011flant\u0131 bir\u00e7ok nedenden dolay\u0131 bir risk noktas\u0131d\u0131r. \u00d6ncelikle, profesyoneller \u00f6\u011frenme ihtiya\u00e7lar\u0131n\u0131 tan\u0131mlayabilmeli ve onlara g\u00f6re hareket edebilmelidir, bu nedenle \u00f6z y\u00f6netimli \u00f6\u011frenme yetene\u011fi bir\u00e7ok analitik tekni\u011finin ba\u015far\u0131s\u0131 i\u00e7in kritik \u00f6neme sahiptir. \u0130kincisi, k\u00fclt\u00fcrde ve organizasyon i\u00e7indeki insanlar\u0131n zihniyetlerinde paralel bir de\u011fi\u015fim olmadan, analitik temelli \u00f6\u011frenme sistemlerinin s\u0131n\u0131rl\u0131 etkisi olacakt\u0131r. \u00d6A'ya yakla\u015f\u0131mlar\u0131n uygulanmas\u0131 bu insan unsurlar\u0131n\u0131 g\u00f6z \u00f6n\u00fcnde bulundurmal\u0131d\u0131r.<\/span><\/p>\n

Baz\u0131 \u00d6A teknikleri veri toplamak i\u00e7in a\u011f analizini kullan\u0131r. \u0130\u015fyerinde \u00f6\u011frenme, \u00f6\u011frenme s\u00fcre\u00e7leri \u00f6rg\u00fctsel ve proje hedefleriyle ayn\u0131 \u00e7izgide oldu\u011funda en etkilidir (Kimmerle, Cress ve Held, 2010; Kozlowski ve Klein, 2000). A\u011f analizi, bireysel \u00f6\u011frenme faaliyetlerini ak\u0131ll\u0131ca kurumsal \u00f6\u011frenme hedefleriyle uyumlu hale getirmeyi ama\u00e7lamal\u0131d\u0131r.<\/span><\/p>\n

M\u00d6A'na y\u00f6nelik umut vaat eden di\u011fer yakla\u015f\u0131mlar, yaz\u0131l\u0131m uygulamalar\u0131n\u0131n (veya uygulamalar\u0131n) geli\u015ftirilmesine dayan\u0131r. \u0130deal olarak, belirli bir uzmanl\u0131\u011fa sahip profesyoneller kodu yazar. Bununla birlikte, t\u00fcm profesyoneller kod yazma yetene\u011fine sahip de\u011fildir, bu nedenle, bir\u00e7ok meslek i\u00e7in uygulamalar, i\u015f rol\u00fcn\u00fc derinlemesine anlamayan insanlar taraf\u0131ndan geli\u015ftirmektedir. Bu sorunun teknik olmayan sekt\u00f6rlerde daha yayg\u0131n olmas\u0131 muhtemeldir.<\/span><\/p>\n

Bir\u00e7ok M\u00d6A metodu, yetenek ve \u00f6\u011frenmeyi deneyim yakalama ve yayg\u0131nla\u015ft\u0131rma yoluyla \u00f6\u011frenmek i\u00e7in \u00e7evik yakla\u015f\u0131mlar\u0131 yerle\u015ftirmeyi ama\u00e7lamaktad\u0131r. Bu yakla\u015f\u0131mla ilgili bir tak\u0131m problemler vard\u0131r; \u00f6rne\u011fin, t\u00fcm uzmanl\u0131k alanlar\u0131 kodlanamaz;uzmanl\u0131k geli\u015ftirme yollar\u0131n\u0131 modellemek zordur \u00e7\u00fcnk\u00fc her bireyin yeni bir beceri \u00f6\u011frenmeye aktif olarak d\u00e2hil olmas\u0131 i\u00e7in, kendine \u00f6zg\u00fc bir \u00f6n bilgisi ve mesleki temeli vard\u0131r. Bu zorluklar, analitik \u00e7\u00f6z\u00fcmlerinin sadece yetenek ve deneyim geli\u015ftirmenin teknik ve pratik y\u00f6nlerini ele almakla kalmay\u0131p, ayn\u0131 zamanda duygusal ve g\u00fcd\u00fcsel konularla da ilgilenmesi gerekti\u011fini g\u00f6stermektedir.<\/span><\/p>\n

Ancak emekleme d\u00f6nemindeki mesleki \u00f6\u011frenme analiti\u011fi gelecekteki \u00f6\u011frenme ve \u00e7al\u0131\u015fma i\u00e7in bir temel olu\u015fturmak \u00fczere ayarlanm\u0131\u015ft\u0131r. Ancak profesyonellerin analitik uygulamalarla nas\u0131l \u00f6\u011frendi\u011fi hakk\u0131ndaki bilgilerin uyumuna dikkat edilmelidir.<\/span><\/p>\n\n

KAYNAK\u00c7A<\/h2>\nAttwell, G., Heinemann, L., Deitmer, L., K\u00e4ma\u00e4inen, P. (2013). Developing PLEs to support work practice based learning. In eLearning Papers #35, Nov. 2013. http:\/\/OpenEducationEuropa.eu\/en\/elearning_papers <\/span><\/span>\n\nArgyris, C., & Schon, D. A. (1974). Theory in practice: Increasing professional effectiveness<\/i>. San Francisco, CA: Jossey-Bass, 1974. <\/span><\/span>\n\nBaker, R.S. (2016). Stupid tutoring systems, intelligent humans. International Journal of Artificial Intelligence in Education, 26<\/i>(2), 600\u2013614. <\/span><\/span>\n\nBerendt, B., Vuorikari, R., Littlejohn, A., & Margaryan, A. (2014). Learning analytics and their application in technology-enhanced professional learning. In A. Littlejohn & A. Margaryan (Eds.), Technology-enhanced professional learning: Processes, practices and tools <\/i>(pp. 144\u2013157). London: Routledge. <\/span><\/span>\n\nBoud, D., & Garrick, J. (1999). Understanding learning at work<\/i>. Taylor & Francis US. <\/span><\/span>\n\nBillett, S. (2004). Workplace participatory practices: Conceptualising workplaces as learning environments. Journal of Workplace Learning, 16<\/i>(6), 312\u2013324. <\/span><\/span>\n\nBuckingham Shum, S., & Deakin Crick, R. (2012). Learning dispositions and transferable competencies: Pedagogy, modelling and learning analytics. Proceedings of the 2nd International Conference on Learning Analytics and Knowledge <\/i>(LAK\u201912), 29 April\u20132 May 2012, Vancouver, BC, Canada (pp. 92\u2013101). New York: ACM.<\/span><\/span>\n\nBuckingham Shum, S., & Ferguson, R. (2012). Social learning analytics. Educational Technology & Society, 15<\/i>(3), 3\u201326. <\/span><\/span>\n\nClow, J. (2013) Work practices to support continuous organisational learning. In A. Littlejohn & A. Margaryan (Eds.), Technology-enhanced professional learning: Processes, practices, and tools <\/i>(pp. 17\u201327). London: Routledge. <\/span><\/span>\n\nCollin, K. (2008). Development engineers\u2019 work and learning as shared practice. International Journal of Lifelong Education, 27<\/i>(4), 379\u2013397. <\/span><\/span>\n\nConvertino, G., Grasso, A., DiMicco, J., De Michelis, G., & Chi, E. H. (2010). Collective intelligence in organizations: Towards a research agenda. Proceedings of the 2010 ACM Conference on Computer Supported Cooperative Work <\/i>(CSCW 2010), 6\u201310 February 2010, Atlanta, GA, USA (pp. 613\u2013614). New York: ACM. http:\/\/ research.microsoft.com\/en-us\/um\/redmond\/groups\/connect\/CSCW_10\/docs\/p613.pdf <\/span><\/span>\n\nDennerlein, S., Theiler, D., Marton, P., Santos, P., Cook, J., Lindstaedt, S., & Lex, E. (2015) KnowBrain: An online social knowledge repository for informal workplace learning. Proceedings of the 10th European Conference on Technology Enhanced Learning <\/i>(EC-TEL\u201915), 15\u201317 September 2015, Toledo, Spain. http:\/\/eprints.uwe.ac.uk\/26226 <\/span><\/span>\n\nEndedijk, M. (2016) Presentation at the Technology-enhanced Professional Learning (TePL) Special Interest Group, Glasgow Caledonian University, May 2016. <\/span><\/span>\n\nEraut, M. (2000). Non-formal learning and tacit knowledge in professional work. British Journal of Educational Psychology, 70<\/i>(1), 113\u2013136. <\/span><\/span>\n\nEraut, M. (2004). Informal learning in the workplace. Studies in Continuing Education, 26<\/i>(2), 247\u2013273. <\/span><\/span>\n\nEraut, M. (2007). Learning from other people in the workplace. Oxford Review of Education, 33<\/i>(4), 403\u2013422. <\/span><\/span>\n\nEngestr\u00f6m, Y. (1999). Innovative learning in work teams: Analyzing cycles of knowledge creation in practice. Perspectives on activity theory<\/i>, 377-404. <\/span><\/span>\n\nEngestr\u00f6m, Y. (2008). From teams to knots: Activity-theoretical studies of collaboration and learning at work. Cambridge, UK: Cambridge University Press. <\/span><\/span>\n\nFerguson, R. (2012) Learning analytics: Drivers, developments and challenges. International Journal of Technology Enhanced Learning, 4<\/i>(5\u20136), 304\u2013317. <\/span><\/span>\n\nFuller, A., Ashton, D., Felstead, A., Unwin, L., Walters, S., & Quinn, M. (2003). The impact of informal learning for work on business productivity. London: Department of Trade and Industry. <\/span><\/span>\n\nFuller, A., & Unwin, L. (2004). lntegrating organizational and personal development. Workplace learning in context<\/i>, 126. <\/span><\/span>\n\nGillani, N., & Eynon, R. (2014). Communication patterns in massively open online courses. The Internet and Higher Education, 23, <\/i>18\u201326. <\/span><\/span>\n\nHarteis, C., & Billett, S. (2008). The workplace as learning environment: Introduction. International Journal of Educational Research, 47<\/i>(4), 209\u2013212. <\/span><\/span>\n\nHEC Report (2016) From bricks to clicks: Higher Education Commission Report http:\/\/www.policyconnect.org.uk\/hec\/sites\/site_hec\/files\/report\/419\/fieldreportdownload\/frombrickstoclicks-hecreportforweb.pdf <\/span><\/span>\n\nHolocher-Ertl, T., Fabian, C. M., Siadaty, M., Jovanovi\u0107, J., Pata, K., & Ga\u0161evi\u0107, D. (2011). Self-regulated learners and collaboration: How innovative tools can address the motivation to learn at the workplace? Proceedings of the 6th European Conference on Technology Enhanced Learning: Towards Ubiquitous Learning <\/i>(EC-TEL 2011), 20\u201323 September 2011, Palermo, Italy (pp. 506\u2013511). Springer Berlin Heidelberg. <\/span><\/span>\n\nIBM (2008) Making change work. IBM Global Study. http:\/\/www-07.ibm.com\/au\/pdf\/making_change_work.pdf <\/span><\/span>\n\nde Laat, M., & Schreurs, B. (2013). Visualizing informal professional development networks: Building a case for learning analytics in the workplace. American Behavioral Scientist, 57<\/i>(10), 1421\u20131438.<\/span><\/span>\n\nKimmerle, J., Cress, U., & Held, C. (2010). The interplay between individual and collective knowledge: Technologies for organisational learning and knowledge building. Knowledge Management Research & Practice, 8<\/i>(1), 33\u201344. <\/span><\/span>\n\nKirschenmann, U., Scheffel, M., Friedrich, M., Niemann, K., & Wolpers, M. (2010). Demands of modern PLEs and the ROLE approach. In M. Wolpers, P. A. Kirschner, M. Scheffel, S. N. Lindstaedt, & V. Dimitrova (Eds.), Proceedings of the 5th European Conference on Technology Enhanced Learning, Sustaining TEL: From Innovation to Learning and Practice <\/i>(EC-TEL 2010), 28 September\u20131 October 2010, Barcelona, Spain (pp. 167\u2013182). Springer Berlin Heidelberg. <\/span><\/span>\n\nKozlowski, S. W. J., & Klein, K. J. (2000). A multilevel approach to theory and research in organizations: Contextual, temporal, and emergent processes. In K. J. Klein & S. W. J. Kozlowski (Eds.), Multilevel theory, research and methods in organizations: Foundations, extensions, and new directions <\/i>(pp. 3\u201390). San Francisco, CA: Jossey-Bass. <\/span><\/span>\n\nKnipfer, K., Kump, B., Wessel, D., & Cress, U. (2013). Reflection as a catalyst for organisational learning. Studies in Continuing Education, 35<\/i>(1), 30\u201348. <\/span><\/span>\n\nKroop, S., Mikroyannidis, A., & Wolpers, M. (Eds.). (2015). Responsive open learning environments: Outcomes of research from the ROLE project. Springer. <\/span><\/span>\n\nKump, B., Knipfer, K., Pammer, V., Schmidt, A., & Maier, R. (2011) The role of reflection in maturing organizational know-how. Proceedings of the 1st European Workshop on Awareness and Reflection in Learning Networks <\/i>(@ EC-TEL 2011), 21 September 2011, Palermo, Italy. <\/span><\/span>\n\nLey, T., Cook, J., Dennerlein, S., Kravcik, M., Kunzmann, C., Pata, K., & Trattner, C. (2014). Scaling informal learning at the workplace: A model and four designs from a large-scale design-based research effort. British Journal of Educational Technology, 45<\/i>(6), 1036\u20131048. <\/span><\/span>\n\nLittlejohn, A., & Hood, N. (2016, March 18). How educators build knowledge and expand their practice: The case of open education resources. British Journal of Educational Technology<\/i>. doi: 10.1111 \/ bjet.12438 <\/span><\/span>\n\nLittlejohn, A., & Margaryan, A. (2013). Technology-enhanced professional learning: Mapping out a new domain. In A. Littlejohn & A. Margaryan (Eds.), Technology-enhanced professional learning: Processes, practices, and tools <\/i>(Chapter 1). Taylor & Francis. <\/span><\/span>\n\nLittlejohn, A., Milligan, C., & Margaryan, A. (2012). Charting collective knowledge: Supporting self-regulated learning in the workplace. Journal of Workplace Learning, 24<\/i>(3), 226\u2013238. <\/span><\/span>\n\nMilligan, C., Littlejohn, A., & Margaryan, A. (2014). Workplace learning in informal networks. Reusing Open Resources: Learning in Open Networks for Work, Life and Education<\/i>, 93. <\/span><\/span>\n\nNistor, N., Derntl, M., & Klamma, R. (2015). Learning analytics: Trends and issues of the empirical research of the years 2011\u20132014. Proceedings of the 10th European Conference on Technology Enhanced Learning: Design for Teaching and Learning in a Networked World <\/i>(EC-TEL 2015), 15\u201317 September 2015, Toledo, Spain (pp. 453\u2013459). Springer. <\/span><\/span>\n\nRienties, B., Boroowa, A., Cross, S., Kubiak, C., Mayles, K., & Murphy, S. (2016). Analytics4Action evaluation framework: A review of evidence-based learning analytics interventions at the Open University UK. Journal of Interactive Media in Education, 2016<\/i>(1). www-jime.open.ac.uk\/articles\/10.5334\/jime.394\/galley\/596\/ download\/ <\/span><\/span>\n\nSiadaty, M. (2013). Semantic web-enabled interventions to support workplace learning<\/i>. Doctoral dissertation, Simon Fraser University, Burnaby, BC. http:\/\/summit.sfu.ca\/item\/12795 <\/span><\/span>\n\nSiadaty, M., Ga\u0161evi\u0107, D., & Hatala, M. (2016). Associations between technological scaffolding and micro-level processes of self-regulated learning: A workplace study. Computers in Human Behavior, 55<\/i>, 1007\u20131019. <\/span><\/span>\n\nSiadaty, M., Ga\u0161evi\u0107, D., Jovanovi\u0107, J., Pata, K., Miliki\u0107, N., Holocher-Ertl, T., \u2026 & Hatala, M. (2012). Self-regulated workplace learning: A pedagogical framework and semantic web-based environment. Educational Technology & Society, 15<\/i>(4), 75\u201388.<\/span><\/span>\n\nSiadaty, M., Jovanovi\u0107, J., Ga\u0161evi\u0107, D., Jeremi\u0107, Z., & Holocher-Ertl, T. (2010). Leveraging semantic technologies for harmonization of individual and organizational learning. In M. Wolpers, P. A. Kirschner, M. Scheffel, S. N. Lindstaedt, & V. Dimitrova (Eds.), Proceedings of the 5th European Conference on Technology Enhanced Learning, Sustaining TEL: From Innovation to Learning and Practice <\/i>(EC-TEL 2010), 28 September\u20131 October 2010, Barcelona, Spain (pp. 340\u2013356). Springer Berlin Heidelberg. <\/span><\/span>\n\nSiemens, G. ve Long, P. (2011) Penetrating the fog: Analytics in learning and education. EDUCAUSE Review, 46<\/i>(5), 31\u201340. http:\/\/net.educause.edu\/ir\/library\/pdf\/ERM1151.pdf <\/span><\/span>\n\nTynj\u00e4l\u00e4, P. (2008). Perspectives into learning at the workplace. Educational Research Review, 3<\/i>(2), 130\u2013154. <\/span><\/span>\n\nTynj\u00e4l\u00e4, P., & Gijbels, D. (2012). Changing world: Changing pedagogy. In P. Tynj\u00e4l\u00e4, M.-L. Stenstr\u00f6m, & M. Saarnivaara (Eds.), Transitions and transformations in learning and education <\/i>(pp. 205\u2013222). Springer Netherlands. <\/span><\/span>\n\nWen, M., Yang, D., & Ros\u00e9, C. (2014). Sentiment analysis in MOOC discussion forums: What does it tell us? In J. Stamper et al. (Eds.), Proceedings of the 7th International Conference on Educational Data Mining <\/i>(EDM2014), 4\u20137 July 2014, London, UK. International Educational Data Mining Society. http:\/\/www.cs.cmu.edu\/~mwen\/papers\/edm2014-camera-ready.pdf <\/span><\/span>\n\nWolff, A., Zdrahal, Z., Nikolov, A., & Pantucek, M. (2013, April). Improving retention: Predicting at-risk students by analysing clicking behaviour in a virtual learning environment. Proceedings of the 3rd International Conference on Learning Analytics and Knowledge <\/i>(LAK\u201913), 8\u201312 April 2013, Leuven, Belgium (pp. 145\u2013149). New York: ACM.<\/span><\/span>\n\n
\n\n
\n

1<\/a> https:\/\/wekit-community.org\/<\/span><\/span><\/p>\n\n<\/div>\n

\n

2<\/a> the WEKIT.club<\/span><\/span><\/p>\n\n<\/div>\n

\n

3<\/a> learning\u2013layers.eu<\/span><\/span><\/p>\n\n<\/div>\n

\n

4<\/a> odl.learning-layers.eu<\/span><\/span><\/p>\n\n<\/div>\n

\n

5<\/a> developer.learning-layers.eu<\/span><\/span><\/p>\n\n<\/div>\n

\n

6<\/a> role-project.eu<\/span><\/span><\/p>\n\n<\/div>\n

\n

7<\/a> \u00d6z Denetimli Bir \u00d6\u011frenen Olmada ROL Kursu (http:\/\/www.open.edu\/openlearnworks\/course\/view.php?id=1490)<\/span><\/span><\/p>\n\n<\/div>\n

\n

8<\/a> www.mirror\u2013project.eu<\/span><\/span><\/p>\n\n<\/div>\n","rendered":"

Allison Littlejohn<\/span><\/span><\/p>\n

E\u011fitim Teknolojileri Enstit\u00fcs\u00fc, A\u00e7\u0131k \u00dcniversite, Birle\u015fik Krall\u0131k<\/span><\/span><\/p>\n

DOI: 10.18608\/hla17.023<\/span><\/span><\/p>\n

\u00d6Z<\/h2>\n

Mesleki \u00f6\u011frenme, mesleki faaliyetler, yayg\u0131n e\u011fitim ve \u00f6rg\u00fcn e\u011fitim gibi farkl\u0131 t\u00fcrlerde olabilir. \u00c7al\u0131\u015fanlar a\u011fa ba\u011fl\u0131 farkl\u0131 \u00e7al\u0131\u015fma ortamlar\u0131nda i\u015f birli\u011fi yaparken de\u011fi\u015fik \u015fekillerde dijital ayak izleri ve “\u00f6zel ili\u015fkileri”ne ili\u015fkin veriler b\u0131rak\u0131rlar. Bu veriler \u00e7al\u0131\u015fanlar\u0131n \u00f6\u011frenmelerini desteklemek amac\u0131yla hem \u00f6rg\u00fcn hem de yayg\u0131n \u00f6\u011frenme s\u00fcre\u00e7lerini izlenebilir ve g\u00f6r\u00fcn\u00fcr k\u0131lmak i\u00e7in \u00f6\u011frenme analiti\u011finde (\u00d6A) kullan\u0131labilir. Bu b\u00f6l\u00fcm, mesleki \u00f6\u011frenme analiti\u011fi (M\u00d6A) i\u00e7in bir vizyon ortaya koyarak ve \u00e7al\u0131\u015fma ortamlar\u0131nda fiilen uygulanan analitik \u00f6rneklerini \u00e7\u00f6z\u00fcmleyerek \u00e7al\u0131\u015fanlar\u0131n nas\u0131l \u00f6\u011frendiklerinin g\u00f6z \u00f6n\u00fcnde bulunduruldu\u011fu, mesleki \u00f6\u011frenme analitiklerinde gelinen son noktay\u0131 incelemektedir. \u00d6A, duygusal ve motivasyonel \u00f6\u011frenme konular\u0131n\u0131n yan\u0131 s\u0131ra teknik ve pratik uzmanl\u0131\u011f\u0131 da ele alabilir; bireysel \u00f6\u011frenme faaliyetlerini kurumsal \u00f6\u011frenme hedeflerine g\u00f6re ak\u0131ll\u0131ca d\u00fczenleyebilir. M\u00d6A gelecekteki \u00f6\u011frenme ve \u00e7al\u0131\u015fma i\u00e7in bir temel olu\u015fturmak \u00fczere ayarlanm\u0131\u015ft\u0131r.<\/span><\/span><\/p>\n

Anahtar Kelimeler<\/span>: Mesleki \u00f6\u011frenme, \u00f6rg\u00fcn e\u011fitim, yayg\u0131n e\u011fitim<\/span><\/span><\/p>\n

Mesleki \u00f6\u011frenme, s\u00fcrekli iyile\u015ftirme, yenilik\u00e7ilik ve i\u015f i\u00e7in yeni uygulamalar\u0131n benimsenmesinin kritik bir bile\u015fenidir (Boud ve Garrick, 1999; Fuller vd., 2003; Engestrom, 2008). Belirsiz bir i\u015f ortam\u0131nda, kurulu\u015flar\u0131n s\u00fcrekli de\u011fi\u015fim ile ba\u015fa \u00e7\u0131kmalar\u0131 i\u00e7in s\u00fcrekli \u00f6\u011frenebilmeleri gerekir (IBM, 2008). Mesleki \u00f6\u011frenme, \u00f6rg\u00fcn e\u011fitimden meslekta\u015flarla yap\u0131lan g\u00f6r\u00fc\u015fmelere, i\u015f etkinlikleri yoluyla ger\u00e7ekle\u015fen resm\u00ee olmayan e\u011fitime kadar de\u011fi\u015fen farkl\u0131 bi\u00e7imlerde (Eraut, 2004; Fuller vd., 2003) \u015fekillenir. Bu eylemler, profesyonel \u00f6\u011frenme ve geli\u015fimi iyile\u015ftirmek i\u00e7in kullan\u0131labilecek \u00e7e\u015fitli veriler \u00fcreten farkl\u0131 \u00f6\u011frenme ba\u011flamlar\u0131 olarak alg\u0131lanabilir (Billett, 2004; Littlejohn, Milligan ve Margaryan, 2012). G\u00fcn\u00fcm\u00fcz i\u015fyerlerinde, \u00e7al\u0131\u015fanlar, dijital kaynaklar\u0131 kullanarak, \u00e7e\u015fitli dijital izler ve “t\u0131klama” verileri b\u0131rakarak a\u011fa ba\u011fl\u0131 ortamlarda i\u015f birli\u011fi yapma e\u011filimindedir. Bu farkl\u0131 veri t\u00fcrlerinin analizi potansiyel olarak, \u00e7al\u0131\u015fanlar\u0131n \u00e7ok \u00e7e\u015fitli \u00f6\u011frenme ve uyarlama tarzlar\u0131n\u0131 geli\u015ftirerek ve destekleyerek i\u015flevsel verimlili\u011fi art\u0131rmak i\u00e7in g\u00fc\u00e7l\u00fc bir yol sa\u011flar.<\/span><\/p>\n

Son birka\u00e7 y\u0131ld\u0131r, i\u015fverenler, \u00e7al\u0131\u015fan e\u011fitiminin desteklenmesi ve geli\u015ftirilmesinde \u00f6\u011frenme analiti\u011fi potansiyelinin fark\u0131ndad\u0131rlar (Buckingham Shum ve Ferguson, 2012). \u00d6\u011frenme analiti\u011fi (\u00d6A), \u201c\u00f6\u011frenmeyi ve ger\u00e7ekle\u015fti\u011fi ortamlar\u0131 anlamak ve onlar\u0131n verimini art\u0131rmak amac\u0131yla, \u00f6\u011frenenler ve durumlar\u0131 hakk\u0131ndaki verilerin \u00f6l\u00e7\u00fcm\u00fc, toplanmas\u0131, analizi ve raporlanmas\u0131\u201dn\u0131 ama\u00e7layan, ortaya \u00e7\u0131kmakta olan metodolojik ve \u00e7ok disiplinli bir ara\u015ft\u0131rma alan\u0131d\u0131r (Siemens ve Long, 2011, s. 34).<\/span><\/p>\n

E\u011fitimde \u00d6A’n\u0131n vizyonu, \u00f6\u011frenmeyi desteklemek i\u00e7in veriyi ve uyarlanabilir pedagoji modellerini g\u00fc\u00e7lendirebilecek \u00e7ok y\u00f6nl\u00fc sistemlerdir (Baker, 2016; Berendt, Vuorikari, Littlejohn ve Margaryan, 2014). Bu sistemler, \u00f6\u011frenenlerin hedeflerine ula\u015fmalar\u0131n\u0131 desteklemek i\u00e7in dijital \u00f6\u011frenme etkinli\u011finin bir yan \u00fcr\u00fcn\u00fc olarak \u00fcretilen b\u00fcy\u00fck miktardaki verileri i\u015fler (Ferguson, 2012). Bununla birlikte, \u00fcniversite e\u011fitiminde kullan\u0131lmak \u00fczere geli\u015ftirilen sistemler, y\u00fcksek\u00f6\u011frenimin maliyeti ile ilgili kayg\u0131lara ve kazan\u0131mlar\u0131n etkilili\u011fine odaklanmas\u0131yla \u00e7ok daha basit hale gelmi\u015ftir (Nistor, Derntl ve Klamma, 2015; HEC Report, 2016). Bir\u00e7ok \u00d6A sistemi, \u00f6\u011frenenin \u201cokulu b\u0131rakma riski alt\u0131nda olup olmad\u0131\u011f\u0131n\u0131\u201d tahmin etmek i\u00e7in her bir \u00f6\u011frenenin profilini analiz eden kestirimci modellere dayanmaktad\u0131r (Siemens ve Long, 2011, s. 36; Wolff, Zdrahal, Nikolov ve Pantucek, 2013; Berendt vd.,2014; Nistor vd., 2015). Bu veriler daha sonra \u00e7e\u015fitli g\u00f6sterge panelleri arac\u0131l\u0131\u011f\u0131 ile \u00f6\u011frenenlere veya \u00f6\u011fretmenlere sunulur. Mevcut ara\u015ft\u0131rmalar, bu geri bildirimleri takip etmek i\u00e7in ger\u00e7ekle\u015ftirilen eylemlere odaklanmaktad\u0131r (Rienties vd., 2016).<\/span><\/p>\n

E\u011fitim ortamlar\u0131nda, ders hedefleri \u00f6\u011frenmenin oda\u011f\u0131d\u0131r. Ancak \u00f6rg\u00fctsel ortamlarda proje hedefleri ve \u00f6rg\u00fctsel hedeflere g\u00f6re \u00f6\u011frenme s\u00fcre\u00e7leri uyumlu hale getirilmelidir (Kimmerle, Cress ve Held, 2010). \u00d6\u011frenme, genellikle bir insan kaynaklar\u0131 b\u00f6l\u00fcm\u00fc taraf\u0131ndan denetlenen y\u0131ll\u0131k performans inceleme s\u00fcre\u00e7leri etraf\u0131nda planlanma e\u011filimindedir. Bu t\u00fcr sistemler, b\u00fcy\u00fck gruplar\u0131n standart i\u015f g\u00f6revlerinin oldu\u011fu ve benzer geli\u015ftirme etkinlikleri planlad\u0131klar\u0131 \u00f6rg\u00fctlerde iyi \u00e7al\u0131\u015f\u0131r.<\/span><\/p>\n

Bununla birlikte, bir\u00e7ok kurulu\u015fta, i\u015f rollerinde benzersiz ve ki\u015fiselle\u015ftirilmi\u015f geli\u015fim planlamas\u0131 gerektiren bir uzmanla\u015fmaya gidilmektedir. Bu durumlarda, hedeflerin ve \u00f6nceliklerin ba\u015flang\u0131\u00e7tan itibaren planland\u0131\u011f\u0131 ve s\u0131raland\u0131\u011f\u0131 \u201cyukar\u0131dan a\u015fa\u011f\u0131ya\u201d planlama modelleri etkili olmayabilir. Baz\u0131 kurulu\u015flar, kurumsal sistemleri kullanan yukar\u0131dan a\u015fa\u011f\u0131ya ve ki\u015fiselle\u015ftirilmi\u015f geli\u015fim planlamas\u0131ndan, teknolojilerin kullan\u0131m\u0131n\u0131 temel alan i\u015f birli\u011fine dayal\u0131 etkinlik planlamas\u0131na, proje ekiplerinin zaman i\u00e7inde projenin y\u00f6n\u00fcn\u00fc de\u011fi\u015ftirme takdirine sahip oldu\u011fu “ak\u0131ll\u0131” veya “\u00e7evik bir \u015fekilde” geli\u015fim planlamas\u0131na do\u011fru kaymaktad\u0131r (Clow, 2013). Bu geli\u015fim hedeflerinin her geli\u015fim d\u00f6ng\u00fcs\u00fcn\u00fcn ba\u015f\u0131nda planlanamayaca\u011f\u0131 anlam\u0131na gelir; her proje ilerledik\u00e7e yeni ve geli\u015fen \u00f6ncelikler ortaya \u00e7\u0131kmaktad\u0131r. \u00c7evik planlama sistemleri, insanlar\u0131n yeni i\u015f g\u00f6revleri i\u00e7in bu g\u00f6revler ortaya \u00e7\u0131karken ihtiya\u00e7 duyduklar\u0131 bilgileri edindikleri yerde, tam zaman\u0131nda ve uyarlanabilir \u00f6\u011frenmeyi gerektirir. Bununla birlikte, bu, profesyonellerin, i\u015fle ilgili g\u00f6revleri geli\u015ftik\u00e7e \u00f6\u011frenme \u00f6nceliklerini de\u011fi\u015ftirerek kendi \u00f6\u011frenme ve geli\u015fimlerini planlama ve \u00f6z d\u00fczenleme yapabilmeleri gerekti\u011fi anlam\u0131na gelir (Littlejohn vd., 2012).<\/span><\/p>\n

PROFESYONELLER NASIL \u00d6\u011eREN\u0130R<\/h2>\n

E\u011fitim ortamlar\u0131nda \u00f6\u011frenme, her bir \u00f6\u011frenenin kazan\u0131mlar\u0131 ve a\u00e7\u0131k pedagojik modellerine odaklanma e\u011filimindedir. Ancak mesleki \u00f6\u011frenme, i\u015fe y\u00f6nelik g\u00f6rev talepleri taraf\u0131ndan y\u00f6nlendirilir ve i\u015f s\u00fcre\u00e7leriyle i\u00e7 i\u00e7edir (Eraut, 2000). \u201cMesleki \u00f6\u011frenme\u201d ile profesyonellerin d\u00fc\u015f\u00fcnme ve mesleki bilgilerini te\u015fvik etmek, i\u015f performans\u0131n\u0131 geli\u015ftirmek ve uygulaman\u0131n bilgilendirilmi\u015f ve g\u00fcncel olmas\u0131n\u0131 sa\u011flamak i\u00e7in kat\u0131ld\u0131\u011f\u0131 faaliyetler anlam\u0131na gelir (Littlejohn ve Margaryan, 2013, s. 2).<\/span><\/p>\n

Profesyoneller \u00f6\u011frenmeyi uygulamal\u0131 e\u011fitim veya \u00f6rg\u00fcn \u00f6\u011frenme olarak d\u00fc\u015f\u00fcnme e\u011filimindedir (Eraut, 2000). Ancak mesleki \u00f6\u011frenmenin i\u015fe y\u00f6nelik g\u00f6revlerle b\u00fct\u00fcnle\u015fti\u011finde daha etkili oldu\u011funa dair kan\u0131tlar da artmaktad\u0131r (bk. \u00f6rne\u011fin, Collin, 2008; Tynjala, 2008; Fuller ve Unwin, 2004; Eraut, 2004). Bu t\u00fcr bir \u00f6\u011frenmenin g\u00fcnl\u00fck i\u015f g\u00f6revlerinden ay\u0131rt edilmesi zordur, bu nedenle profesyoneller \u00f6\u011frenme \u00f6rneklerini fark edemeyebilir (Argyris ve Schon, 1974; Engestrom, 1999).<\/span><\/p>\n

Eraut\u2019un \u00e7al\u0131\u015fmas\u0131 (2004), \u00f6zellikle meslek i\u00e7i \u00f6\u011frenmeyi \u201cama\u00e7l\u0131\u201d ve planlanm\u0131\u015f veya \u201cama\u00e7s\u0131z\u201d ve hali haz\u0131rdaki duruma uygun olarak tan\u0131mlad\u0131\u011f\u0131 i\u015f ba\u015f\u0131 \u00f6\u011frenmenin \u00f6nemi \u00f6n plana \u00e7\u0131kar\u0131r. Tynjala’ya (2008) g\u00f6re, ama\u00e7l\u0131 \u00f6\u011frenme \u00f6nceden planlanm\u0131\u015f ve \u00f6rg\u00fcn \u00f6\u011frenme olarak yap\u0131land\u0131r\u0131lm\u0131\u015f olabilir (\u00f6r. mezuniyet programlar\u0131, s\u0131n\u0131f e\u011fitimi, pratik at\u00f6lyeler, ko\u00e7luk veya mentorluk vb.); di\u011fer formlar\u0131n (\u00f6r. bir i\u015f arkada\u015f\u0131ndan yard\u0131m istemek veya bir uzman\u0131n bir g\u00f6revi yerine getirmesini izlemek vb.) ay\u0131rt edilmesi daha zordur. \u00d6\u011frenme, i\u015f faaliyetinin \u201cama\u00e7lanmam\u0131\u015f\u201d bir sonucu olarak ortaya \u00e7\u0131kabilir (Eraut, 2000). Finans kurulu\u015fundaki bir y\u00f6netici, d\u00fcnya \u00e7ap\u0131ndaki \u015fubelerden yeni meslekta\u015flar ekibine kat\u0131l\u0131rken k\u00fclt\u00fcrleraras\u0131 yetkinliklerini zaman i\u00e7inde art\u0131rabilir (Littlejohn ve Hood, 2016). Profesyoneller, uygulamalar\u0131n\u0131n zaman i\u00e7inde nas\u0131l geli\u015fti\u011fini yans\u0131tana kadar bu t\u00fcr deneysel \u00f6\u011frenmenin fark\u0131nda olmayabilirler. Bu farkl\u0131 mesleki \u00f6\u011frenme bi\u00e7imleri, \u015eekil 23.1’deki tipolojide g\u00f6sterilmektedir.<\/span><\/p>\n

\"\"<\/p>\n

<\/a> \u015eekil 23.1. Eraut (2000, 2004) taraf\u0131ndan belirtilen mesleki \u00f6\u011frenme tipolojisi.<\/i><\/span><\/span><\/p>\n

\u015eekil 23.1’de farkl\u0131 bilgi t\u00fcrlerinin geli\u015fimini kolayla\u015ft\u0131ran \u00f6\u011frenmeye y\u00f6nelik farkl\u0131 yakla\u015f\u0131mlar g\u00f6sterilmi\u015ftir (Tynjala ve Gijbels, 2012; Littlejohn ve Hood, 2016). \u00d6rne\u011fin e\u011fitim ve uygulamal\u0131 \u00f6\u011fretim teorik ve pratik bilgi \u00f6\u011frenmeye odaklan\u0131rken, ko\u00e7luk ve mentorluk sosyo-k\u00fclt\u00fcrel ve \u00f6z y\u00f6netimli bilgileri \u00f6\u011frenme f\u0131rsatlar\u0131 sa\u011flar. T\u00fcm bu bilgi t\u00fcrleri, i\u015f i\u00e7in yeni uygulamalar\u0131n benimsenmesi i\u00e7in kritik \u00f6neme sahiptir. Uygulamadaki de\u011fi\u015fim, kavramsal ve pratik bilginin olu\u015fturulmas\u0131n\u0131n yan\u0131 s\u0131ra sosyo-k\u00fclt\u00fcrel ve \u00f6z y\u00f6netimli bilginin geli\u015fimini gerektirir (Eraut, 2007). \u00c7oklu bilgi t\u00fcrlerinin in\u015fas\u0131, informal (yap\u0131land\u0131r\u0131lmam\u0131\u015f, i\u015f ba\u015f\u0131nda) \u00f6\u011frenme ile formal (yap\u0131land\u0131r\u0131lm\u0131\u015f, \u00f6nceden planlanm\u0131\u015f) \u00f6\u011frenme etkinliklerinin bir araya getirilmesiyle elde edilir (Harteis ve Billett, 2008). Bu nedenle, i\u015fyeri \u00f6\u011frenmesi, belirli bir i\u015fyerinin imk\u00e2nlar\u0131 ile birlikte, bu imk\u00e2nlar\u0131n bireyin sahip oldu\u011fu beceri ve motivasyonla ili\u015fkilendirilmesi (Billett, 2004; Fuller ve Unwin, 2004) ile \u015fekillenen kar\u015f\u0131l\u0131kl\u0131 bir s\u00fcre\u00e7 (Billett, 2004) olarak \u00e7al\u0131\u015f\u0131r.<\/span><\/p>\n

Mesleki \u00f6\u011frenme s\u00fcre\u00e7leri, e\u011fitim ortamlar\u0131nda oldu\u011fundan daha dinamiktir; yayg\u0131n \u00f6\u011frenme etkinlikleri kendili\u011findendir ve \u00e7o\u011funlukla di\u011ferleri i\u00e7in g\u00f6r\u00fcn\u00fcr de\u011fildir. Bu \u00d6A alan\u0131 i\u00e7in zorluklar ve f\u0131rsatlar sunmaktad\u0131r.<\/span><\/p>\n

MESLEK\u0130 \u00d6\u011eRENME ANAL\u0130T\u0130\u011e\u0130 \u0130\u00c7\u0130N B\u0130R V\u0130ZYON<\/h2>\n

Profesyonel ba\u011flamlarda \u00d6A i\u00e7in temel vizyon, her bir uzmana ihtiya\u00e7 duyduklar\u0131 bilgiyle ba\u011flant\u0131 kurmak i\u00e7in hem formal hem de informal \u00f6\u011frenme s\u00fcre\u00e7lerini izlenebilir ve daha a\u00e7\u0131k hale getirmektir (Littlejohn vd., 2012; de Laat ve Schreurs, 2013). Bu vizyon, her bir profesyonelin, ilgili bilgi ve deneyimleri bulmak i\u00e7in insanlarla ve a\u011flarla ba\u011flant\u0131<\/i><\/span> kurarak kolektif bilgiye ba\u011fland\u0131\u011f\u0131 ve katk\u0131da bulundu\u011fu kar\u015f\u0131l\u0131kl\u0131 destek sistemine dayanmaktad\u0131r; bu bilgiyi kullanmak veya t\u00fcketmek<\/i><\/span>, s\u00fcre\u00e7 i\u00e7inde toplulu\u011fa katk\u0131 sunacak geri d\u00f6nen yeni bilgiler olu\u015fturmakt\u0131r<\/i><\/span> (Milligan, Littlejohn ve Margaryan, 2014). Bu eylemler, ba\u015flang\u0131\u00e7ta ki\u015fisel fayda taraf\u0131ndan motive edilmesiyle ortaya \u00e7\u0131kan bireysel faaliyetlerin yan \u00fcr\u00fcnlerinden se\u00e7ici olarak biriktirilen yeniden kullan\u0131labilir bilgiler arac\u0131l\u0131\u011f\u0131yla ortak bir sermaye yarat\u0131r (Convertino, Grasso, DiMicco, De Michelis ve Chi, 2010, s. 15). Bu eylemler \u201cba\u015flang\u0131\u00e7ta ki\u015fisel fayda taraf\u0131ndan motive edilmesiyle ortaya \u00e7\u0131kan bireysel faaliyetlerin yan \u00fcr\u00fcnlerinden se\u00e7ici olarak biriktirilen yeniden kullan\u0131labilir bilgiler arac\u0131l\u0131\u011f\u0131yla ortak bir sermaye” yaratan bir dizi algoritma, veri madencili\u011fi mekanizmas\u0131 ve analitikler taraf\u0131ndan desteklenecektir (Convertino vd., 2010, s. 15).<\/span><\/p>\n

Mesleki \u00f6\u011frenme, \u00f6\u011frenenin kolektif bilgi ve \u00e7evresi ile ba\u011flant\u0131 kurma ve etkile\u015fime girme konusundaki i\u00e7 motivasyonundan ve bireysel iradesinden etkilenir (Littlejohn ve Hood, 2016), bu nedenle bu vizyonun iki \u00f6nemli bile\u015feni vard\u0131r. Birincisi, bireysel irade ortaya koyulabilmesi i\u00e7in profesyonellerin \u00f6\u011frenmelerinde \u00f6z y\u00f6netim becerisine sahip olmalar\u0131 \u00e7ok \u00f6nemlidir. \u0130kincisi, motivasyonu tetiklemek i\u00e7in, \u00f6\u011frenme (ve \u00f6\u011frenme sistemleri) i\u015f uygulamalar\u0131 ile ayr\u0131\u015ft\u0131r\u0131lmamal\u0131 aksine b\u00fct\u00fcnle\u015ftirilmelidir. Bu vizyona ula\u015fma yolunda, ge\u00e7ti\u011fimiz birka\u00e7 y\u0131l boyunca Mesleki \u00d6A’ya y\u00f6nelik bir dizi yakla\u015f\u0131m geli\u015ftirilmi\u015ftir.<\/span><\/p>\n

Uygulamada Analitikler<\/h3>\n

\u00d6A, \u00f6\u011frenme bilimi, bilgisayar biliminden, bilgi biliminden, e\u011fitsel veri madencili\u011finden, bilgi y\u00f6netimi vurgusu” ve daha yak\u0131n bir zamanda yapay zek\u00e2dan fikirler kullanan \u00e7ok disiplinli bir aland\u0131r (Gillani ve Enyon, 2014). Analitikte ortaya \u00e7\u0131kan alanlar s\u00f6ylem verileri, \u00f6\u011frenenlerin e\u011filim verileri ve biyometri gibi \u00e7oklu veri t\u00fcrlerini i\u00e7eren karma\u015f\u0131k veri k\u00fcmelerinden faydalanmaktad\u0131r (Siemens ve Long, 2011). \u00d6A’da kullan\u0131lan teknikler \u00f6\u011frenenlerin tart\u0131\u015fma ve eylemlerinin yard\u0131mc\u0131 m\u00fcdahaleler i\u00e7in f\u0131rsat sa\u011flad\u0131\u011f\u0131 s\u00f6ylem analizini (Gillani ve Enyon, 2014); \u00f6\u011frenenlerle \u00f6\u011frenme aras\u0131ndaki ili\u015fkiyi izleyen anlamsal analizi, (Wen, Yang ve Rose, 2014), \u00f6\u011frenmeyle ili\u015fkili duygusal \u00f6zellikleri belirleyen \u00f6\u011frenen e\u011filim analiti\u011fi (Buckingham Shum ve Deakin Crick, 2012) ve \u00f6\u011frenenler taraf\u0131ndan sa\u011flanan etiketleri ve puanlamalar\u0131 temel alarak i\u00e7eri\u011fi filtreleyen ve sunan \u00f6neri sistemleri de d\u00e2hil olmak \u00fczere i\u00e7erik analiti\u011fini kapsar. Bu teknikler, profesyonellerin nas\u0131l \u00f6\u011frendiklerini etkileyen karma\u015f\u0131k fakt\u00f6rleri ayr\u0131\u015ft\u0131rmak i\u00e7in kullan\u0131\u015fl\u0131d\u0131r.<\/span><\/p>\n

\u00d6A’na y\u00f6nelik \u00e7e\u015fitli yakla\u015f\u0131mlar, alandaki farkl\u0131 i\u015f ortamlarda test edilmi\u015ftir. Baz\u0131 y\u00f6ntemler, dijital sistemlerde \u00f6\u011frenmenin bir yan \u00fcr\u00fcn\u00fc olarak \u00fcretilen verilere b\u00fcy\u00fck \u00f6nem verir. Di\u011ferleri bireylerin ve gruplar\u0131n yeni bilgileri nas\u0131l \u00f6\u011frendi\u011fini ve geli\u015ftirdi\u011fini inceleyen sosyal \u00f6\u011frenme analiti\u011fi (S\u00d6A) gibi yeni yakla\u015f\u0131mlar kullanmaktad\u0131r. Bu y\u00f6ntemler ve sistemler yeni d\u00fczenleme \u015fekillerinden, farkl\u0131 geri bildirim bi\u00e7imlerinden, \u00f6\u011frenme ve i\u015f i\u00e7in insanlar\u0131n ihtiya\u00e7 duyduklar\u0131 kaynaklar\u0131 bir araya getirmenin say\u0131s\u0131z yollar\u0131ndan yararlanmaktad\u0131r. Bunlar\u0131n bir\u00e7o\u011fu geli\u015fimlerinin erken a\u015famalar\u0131ndad\u0131r ve bu b\u00f6l\u00fcm farkl\u0131 yakla\u015f\u0131mlar\u0131 ve bunlar\u0131n \u00f6\u011frenme ve performans \u00fczerindeki etkilerini incelemektedir.<\/span><\/p>\n

An\u0131nda \u00d6\u011frenmeyi H\u0131zland\u0131rma<\/h3>\n

M\u00d6A’na y\u00f6nelik baz\u0131 yakla\u015f\u0131mlar, \u00e7evik yakla\u015f\u0131mlar\u0131n i\u015f ortam\u0131ndaki mesleki \u00f6\u011frenmeye d\u00e2hil edilmesini hedeflemektedir. Bir\u00e7ok kurulu\u015f \u00e7al\u0131\u015fanlar yeni bir y\u00f6ntem \u00f6\u011frendikleri halde bu yeni bilgilerini kullanmad\u0131klar\u0131 ve uygulamalar\u0131na yerle\u015ftirmedikleri takdirde e\u011fitimin etkili olmad\u0131\u011f\u0131n\u0131 kabul etmektedir. \u0130nsanlar\u0131n ihtiya\u00e7 noktas\u0131nda yeni uzmanl\u0131k \u00f6\u011frenmelerini sa\u011flaman\u0131n \u00f6nemini kabul ederek, kurulu\u015flar uzmanl\u0131\u011f\u0131 yakalamak ve yaymak i\u00e7in yollar aramaktad\u0131rlar.<\/span><\/p>\n

Bilgi Yo\u011funluklu E\u011fitim \u0130\u00e7in Giyilebilir Deneyim <\/i><\/span>(BYEGD)1<\/a><\/sup>, ak\u0131ll\u0131 Giyilebilir Teknoloji ile \u00fcretilen verilerin uzmanl\u0131\u011f\u0131 yakalay\u0131p yakalayamad\u0131\u011f\u0131n\u0131 ve ihtiya\u00e7 duydu\u011fu yerde deneyimsiz profesyonellere bilgiyi ula\u015ft\u0131r\u0131p ula\u015ft\u0131ramad\u0131\u011f\u0131n\u0131 ve t\u00fcm bu s\u00fcre\u00e7lerin nas\u0131l ger\u00e7ekle\u015fti\u011fini ara\u015ft\u0131rmaktad\u0131r. BYEGD, \u00fc\u00e7 a\u015famal\u0131 bir s\u00fcrece dayan\u0131r: beceri geli\u015ftirme yollar\u0131n\u0131n haritalanmas\u0131, uzmanl\u0131\u011f\u0131n yakalanmas\u0131 ve sistemle\u015ftirilmesi ve ihtiya\u00e7 duyuldu\u011fu noktada deneyimsiz ki\u015filere uzmanl\u0131k sunulmas\u0131. \u0130lk a\u015famada, uzmanlar ve payda\u015f toplulu\u011fu2<\/a><\/sup> end\u00fcstri i\u00e7in tan\u0131nm\u0131\u015f bir beceri geli\u015ftirme yollar\u0131n\u0131n haritas\u0131n\u0131 \u00e7\u0131kar\u0131r. \u0130kinci a\u015famada, bir grup yaz\u0131l\u0131m geli\u015ftirici, yeni bir i\u015flemsel bilgisinin \u00f6\u011frenilmesinde -\u00f6rne\u011fin \u00f6zellikli bir vanan\u0131n nas\u0131l a\u00e7\u0131laca\u011f\u0131n\u0131n (veya kapat\u0131laca\u011f\u0131n\u0131n) acemileri desteklemek \u00fczere teknoloji ara\u00e7lar\u0131n\u0131 geli\u015ftirmek i\u00e7in- yol haritalar\u0131n\u0131 kullan\u0131r. Son olarak, yetenek ve deneyim acemilere zenginle\u015ftirilmi\u015f bir g\u00f6rsel aray\u00fcz ile aktar\u0131l\u0131r. Ba\u015fa tak\u0131labilen dijital ekranlar gibi ara\u00e7lar, aceminin vanay\u0131 ekranda g\u00fcvenli bir \u015fekilde a\u00e7maya ili\u015fkin talimatlar ile b\u00fct\u00fcnle\u015ftirilmi\u015f olarak g\u00f6rmesini sa\u011flar. Giyilebilir ve g\u00f6rsel cihazlar sayesinde sistem, her profesyonelin dikkatini, kullan\u0131c\u0131 ihtiya\u00e7 analizine dayanarak en \u00e7ok ihtiya\u00e7 duyulan yere y\u00f6nlendirir. Sistem, informal \u00f6\u011frenme s\u00fcre\u00e7lerini izlenebilir ve tan\u0131nabilir hale getirmeyi ama\u00e7lamaktad\u0131r, b\u00f6ylece acemiler h\u0131zl\u0131 bir \u015fekilde uzmanl\u0131k kazanabilir. Bu \u015fekilde, ihtiya\u00e7 ortaya \u00e7\u0131kt\u0131k\u00e7a \u00f6\u011frenme \u00e7evik olabilir.<\/span><\/p>\n

BYEGD projesine 2015 Aral\u0131k ay\u0131nda ba\u015flanm\u0131\u015f ve bu yakla\u015f\u0131m\u0131n etkilili\u011fi ile ilgili de\u011ferlendirmeleri hen\u00fcz yay\u0131nlanmam\u0131\u015ft\u0131r. Bununla birlikte, BYEGD metodolojisindeki uzmanl\u0131k aktar\u0131m\u0131ndaki \u00fc\u00e7 \u00f6nemli ad\u0131mla ili\u015fkilendirilmi\u015f riskler vard\u0131r. \u0130lk olarak, uzmanl\u0131k geli\u015ftirme yollar\u0131n\u0131n modellenmesi zordur. Uzmanlar, uzmanl\u0131\u011f\u0131 do\u011fru bir \u015fekilde yakalamak ve sistemle\u015ftirmek, uzmanl\u0131k geli\u015fimini desteklemek i\u00e7in yollar ve algoritmalar olu\u015fturmaya kat\u0131lmaktad\u0131rlar. Bununla birlikte, bir uzman\u0131n, her aceminin uzmanl\u0131k geli\u015fimine katk\u0131 sa\u011flayacak en uygun \u00f6\u011frenme yolunu anlamas\u0131 zordur, \u00e7\u00fcnk\u00fc bu aceminin \u00f6nceki deneyimine ba\u011fl\u0131d\u0131r. \u0130kincisi, her uzmanl\u0131k sistemle\u015ftirilemez. Ger\u00e7ekli\u011fi art\u0131r\u0131lm\u0131\u015f g\u00f6rsel aray\u00fczler ve i\u015fbirlikli say\u0131sal aray\u00fczler, uzmanl\u0131k geli\u015fimine yard\u0131mc\u0131 olabilir ancak bir ekipman\u0131n en iyi \u015fekilde \u00e7al\u0131\u015ft\u0131\u011f\u0131na y\u00f6nelik \u201ci\u00e7g\u00fcd\u00fcsel\u201d bir uzmanl\u0131\u011f\u0131n geli\u015ftirilmesi zaman al\u0131r. \u00dc\u00e7\u00fcnc\u00fcs\u00fc, bir aceminin basit\u00e7e talimatlar\u0131 izlemektense yeni uzmanl\u0131k \u00f6\u011frenmeye aktif olarak d\u00e2hil olmas\u0131 gerekir. Bu \u00f6zellikle teorik bilgilerle i\u015fin sonu\u00e7lar\u0131n\u0131n tahmin edilmesinin zor oldu\u011fu \u00e7al\u0131\u015fma ortamlar\u0131yla ilgilidir. Bu durumlardaki en etkili \u00f6\u011frenme i\u015f g\u00f6revleriyle b\u00fct\u00fcnle\u015ftirildi\u011finde ortaya \u00e7\u0131kar. Bu nedenle, ortaya \u00e7\u0131kan bir e\u011filim M\u00d6A’y\u0131 i\u015fle b\u00fct\u00fcnle\u015fmi\u015f sistemlere (ortak \u00e7al\u0131\u015fmalarda uzmanlar\u0131 ve acemileri destekleyen ortamlar, daha \u00f6nce de a\u00e7\u0131kland\u0131\u011f\u0131 gibi ak\u0131ll\u0131 sistemler veya gibi art\u0131r\u0131lm\u0131\u015f ger\u00e7eklik ortamlar\u0131) yerle\u015ftirmektir.<\/span><\/p>\n

\u00d6rg\u00fctsel A\u011flar\u0131 Kullanma<\/h3>\n

Gayriresm\u00ee mesleki a\u011flara ba\u011flant\u0131 kurarak, insanlar Clow (2013) taraf\u0131ndan tarif edilen \u00e7evik \u00f6\u011frenme t\u00fcr\u00fcn\u00fc ba\u015farabilirler. Mesleki geli\u015fime y\u00f6nelik bu \u00f6zerk, a\u015fa\u011f\u0131dan yukar\u0131ya yakla\u015f\u0131m t\u00fcr\u00fc, profesyonellerin nas\u0131l ve nerede etkile\u015fime girdiklerini ve \u00e7al\u0131\u015fmalar\u0131 hakk\u0131nda fikir al\u0131\u015fveri\u015finde bulunduklar\u0131n\u0131 derinlemesine anlamay\u0131 gerektirir. \u0130nformal \u00f6\u011frenme uygulama ve a\u011flar\u0131n\u0131 g\u00f6r\u00fcn\u00fcr k\u0131lmak M\u00d6A i\u00e7in temel bir ama\u00e7t\u0131r. de Laat ve Schreurs (2013), \u00d6A tekniklerinin resm\u00ee olmayan profesyonel a\u011flar\u0131 g\u00f6rselle\u015ftirebildi\u011fini g\u00f6stermi\u015ftir. Sosyal a\u011f analizine dayanan bir ara\u00e7 kullanarak -a\u011f fark\u0131ndal\u0131\u011f\u0131 gereci (AFG)- tek bir kurulu\u015f i\u00e7inde birden fazla izole edilmi\u015f \u00f6\u011freten a\u011f\u0131n\u0131 tespit ettiler. Daha yeni yap\u0131lan \u00e7al\u0131\u015fmalar, sa\u011fl\u0131k bak\u0131m\u0131 ortamlar\u0131ndaki profesyonel a\u011flar\u0131 izlemek i\u00e7in giyilebilir cihazlar kullanmaktad\u0131r (Endedijk, 2016). Bu gayriresm\u00ee profesyonel a\u011flardan yararlanarak, kurulu\u015flar\u0131n be\u015feri sosyal sermayesini ve \u00f6\u011frenmesini iyile\u015ftirme mekanizmalar\u0131 vard\u0131r. Bununla birlikte, \u00e7al\u0131\u015fma profesyonel a\u011flar aras\u0131ndaki s\u0131n\u0131rl\u0131 ba\u011flant\u0131lar\u0131n kapsam\u0131n\u0131 g\u00f6stermektedir, bu nedenle a\u011flardan yararlanmak i\u00e7in birden fazla y\u00f6nteme ihtiya\u00e7 vard\u0131r.<\/span><\/p>\n

\u00d6\u011frenme Katmanlar\u0131<\/i><\/span>3<\/a><\/span><\/sup> performans\u0131 art\u0131rmak i\u00e7in a\u011flar\u0131 ve ili\u015fkileri bireysel, \u00f6rg\u00fct ve \u00f6rg\u00fctler aras\u0131 seviyelerde kullan\u0131r. Farkl\u0131 Avrupa \u00fclkelerindeki b\u00f6lgesel k\u00fc\u00e7\u00fck ve orta b\u00fcy\u00fckl\u00fckteki i\u015fletmelerin (KOB\u0130’ler) i\u00e7inde ve aras\u0131nda \u00e7al\u0131\u015fan profesyoneller, fikir ve bilgi olu\u015fturmak i\u00e7in web tabanl\u0131, a\u011f ortam\u0131nda \u00e7al\u0131\u015f\u0131r. Sistem, insanlar\u0131 birbirine ba\u011flayarak ve tavsiyelerde bulunarak bilginin birlikte \u00fcretilmesini analiz etmek ve desteklemek i\u00e7in semantik teknolojilerden yararlan\u0131r (Ley vd., 2014).<\/span><\/p>\n

Sa\u011fl\u0131k ve in\u015faat sekt\u00f6rlerinde test edilen teknoloji ortamlar\u0131, profesyonellerin \u00fc\u00e7 d\u00fczeyde birlikte \u00e7al\u0131\u015fma ve \u00f6\u011frenme yollar\u0131n\u0131 g\u00f6stermektedir. \u0130nsanlar birlikte \u00e7al\u0131\u015ft\u0131k\u00e7a, yeni i\u015f g\u00f6revlerini nas\u0131l yerine getireceklerine dair bilin\u00e7li se\u00e7imler yapmalar\u0131na yard\u0131mc\u0131 olmak \u00fczere teknik bilgi (neyi bilirim), i\u015flemsel veya uygulamaya y\u00f6nelik bilgi (nas\u0131l yapar\u0131m) ve bilimsel veya teorik bilgi (neden b\u00f6yle) gibi farkl\u0131 t\u00fcrden bilgiler geli\u015ftirmeyi \u00f6\u011frenirler (Attwell vd., 2013). \u00d6rg\u00fctsel d\u00fczeyde, insanlar farkl\u0131 KOB\u0130’ler aras\u0131nda i\u015f birli\u011fi yaparken, her bir kurulu\u015f bilgi payla\u015f\u0131r ve \u00f6\u011frenir. \u00dc\u00e7\u00fcnc\u00fcs\u00fc, \u015firketler ulusal k\u00fcmelenmeler halinde grupland\u0131r\u0131lm\u0131\u015ft\u0131r, bu nedenle \u00f6\u011frenme \u00f6rg\u00fctler aras\u0131nda ger\u00e7ekle\u015fir (Dennerlein vd., 2015). \u00d6A ara\u00e7lar\u0131, profesyonellerin kendisiyle ve kilit payda\u015flarla birlikte geli\u015ftirilmektedir. A\u00e7\u0131k bir tasar\u0131m k\u00fct\u00fcphanesi,4<\/a><\/sup> profesyonel \u00f6\u011frenmeye y\u00f6nelik fikirleri saklamak ve yaymak i\u00e7in kullan\u0131l\u0131rken, a\u00e7\u0131k bir geli\u015ftirici k\u00fct\u00fcphanesi5<\/a><\/sup>, geli\u015ftiricilerin \u00fczerinde \u00e7al\u0131\u015fmas\u0131 i\u00e7in prototip ara\u00e7lar\u0131 ve kodlar\u0131 bar\u0131nd\u0131r\u0131r. \u00c7ok \u00f6zel rolleri i\u00e7in \u00f6\u011frenme hakk\u0131nda en iyi bilgiye sahip profesyoneller kendilerini prensibi bir\u00e7ok \u00d6A sistemler ve ara\u00e7lar i\u00e7in merkezi.<\/span><\/p>\n

\u00d6zel Uzmanl\u0131\u011f\u0131ndan Yararlanma<\/h3>\n

Profesyonellerin \u00e7al\u0131\u015fmalar\u0131nda ve \u00f6\u011frenmelerinde de\u011fi\u015fiklik ve belirsizliklere uyum sa\u011flamalar\u0131 ve bunlarla ba\u015fa \u00e7\u0131kmalar\u0131 i\u00e7in Duyarl\u0131 A\u00e7\u0131k \u00d6\u011frenme Ortamlar\u0131 (DA\u00d6O)6<\/a><\/sup> geli\u015ftirilmektedir (Kirschenmann, Scheffel, Friedrich, Niemann ve Wolpers, 2010). Her \u015feyi kapsayan bir i\u015fletme sistemi kullanmak yerine, \u00f6\u011frenme ortam\u0131 her bir \u00f6\u011frenen taraf\u0131ndan ki\u015fiselle\u015ftirilebilir. Her profesyonel, belirli bir rol i\u00e7in \u00f6\u011frenmeyi destekleyen belirli i\u015flevlere sahip bir dizi web tabanl\u0131 yaz\u0131l\u0131m arac\u0131n\u0131 tarayabilir ve se\u00e7ebilir. Ara\u00e7lar, yeni bile\u015fenler ve i\u015flevler olu\u015fturmak i\u00e7in birle\u015ftirilebilir. Uzman, ara\u00e7lar\u0131n ve kaynaklar\u0131n benzersiz bir kombinasyonunu olu\u015fturarak, \u00e7evreye kendi uzmanl\u0131\u011f\u0131n\u0131 kazand\u0131r\u0131r. Bu ara\u00e7 ve kaynak kombinasyonu, benzer i\u015f ve \u00f6\u011frenme ihtiya\u00e7lar\u0131 olan di\u011fer profesyonelleri desteklemek i\u00e7in \u00e7o\u011falt\u0131labilir ve uyarlanabilir.<\/span><\/p>\n

DA\u00d6O’yi destekleyen temel ilke iyi tan\u0131mlanm\u0131\u015ft\u0131r; uzmanl\u0131k rollerinde, profesyonellerin kendileri \u00f6\u011frenme ihtiya\u00e7lar\u0131na en iyi \u015fekilde karar verebileceklerdir (Kroop, Mikroyannidis ve Wolpers, 2015). Ancak profesyonel bir \u00f6\u011frenme bak\u0131\u015f a\u00e7\u0131s\u0131na g\u00f6re, iki ana genel zorluk vard\u0131r. \u0130lk olarak, profesyoneller kararlar\u0131n\u0131 uygulama becerisine sahip olmayabilirler. DA\u00d6O, mesleki \u00f6\u011frenmenin belirli y\u00f6nlerini destekleyen teknoloji ara\u00e7lar\u0131n\u0131n veya ara\u00e7 gere\u00e7lerin geli\u015ftirilmesine izin veren a\u00e7\u0131k bir \u00e7er\u00e7eveye dayanmaktad\u0131r. Bu ekran ara\u00e7lar\u0131 geli\u015ftiricilerin yeni ara\u00e7lar ve i\u015flevler geli\u015ftirmeleri i\u00e7in te\u015fvik edildi\u011fi a\u00e7\u0131k yar\u0131\u015fmalar yoluyla geli\u015ftirilir. \u0130deal olarak, i\u015f rol\u00fcn\u00fc derinlemesine anlayan geli\u015ftiriciler ekran ara\u00e7lar\u0131 geli\u015ftirecektir : profesyoneller kendileri widget’lerin algoritmalar\u0131n\u0131 yazabiliyorlarsa, uzmanl\u0131klar\u0131 kodun i\u00e7ine g\u00f6m\u00fcl\u00fcr. Bununla birlikte, t\u00fcm profesyoneller kod yazamaz, bu y\u00fczden bir\u00e7ok meslek i\u00e7in ara\u00e7lar\u0131 i\u015f rol\u00fcn\u00fc derinlemesine anlamayan insanlar taraf\u0131ndan geli\u015ftirme e\u011filimindedir. \u0130kinci zorluk, profesyonellerin \u00f6\u011frenme ihtiya\u00e7lar\u0131n\u0131 tan\u0131mlamak ve bunlara g\u00f6re hareket etmek zorunda olmalar\u0131d\u0131r. DA\u00d6O ortam\u0131, \u00f6z y\u00f6netim bir \u00f6\u011frenen olma yolunda bir dersi i\u00e7erir7<\/a><\/sup>. Bununla birlikte, bir problem, \u00f6\u011frenme hedeflerini belirleme stratejileri geli\u015ftirmek gibi, \u00f6z y\u00f6netimin baz\u0131 y\u00f6nlerinin \u00f6\u011frenilebilmesine ra\u011fmen, ya\u015fam boyu s\u00fcren deneyimler yoluyla \u00f6z g\u00fcven gibi di\u011fer \u00f6z y\u00f6netim y\u00f6nlerinin geli\u015ftirilmesidir.<\/span><\/p>\n

Aktif \u00d6\u011frenmeyi Te\u015fvik Etmek<\/h3>\n

\u00d6z y\u00f6netimli \u00f6\u011frenme teorisine dayanan di\u011fer iki \u00d6A sistemi \u00f6rne\u011fi LearnB<\/i><\/span> ve Mirror’d\u0131r. LearnB<\/i><\/span> otomotiv end\u00fcstrisinde pilot olmu\u015ftur (Siadaty, Ga\u0161evi\u0107 ve Hatala, 2016). Bu arac\u0131n \u00f6nceki sistemlerle ortak noktas\u0131, profesyonelleri \u00f6\u011frenmelerini kendileri d\u00fczenleme konusunda te\u015fvik etmesidir. Ara\u00e7, \u00f6z y\u00f6netime etki eden fakt\u00f6rler hakk\u0131nda veri toplamak i\u00e7in kullan\u0131lan. \u00f6z y\u00f6netimli \u00f6\u011frenme \u00e7er\u00e7evesi olan \u00d6Y\u00d6@Work etraf\u0131nda tasarlanm\u0131\u015ft\u0131r. Bu fakt\u00f6rler, \u00f6\u011frenme hedeflerinin nas\u0131l planland\u0131\u011f\u0131n\u0131 ve insanlar\u0131n i\u015f i\u00e7in bilgi payla\u015f\u0131rken ve olu\u015ftururken kat\u0131ld\u0131\u011f\u0131 spesifik faaliyetler yelpazesini i\u00e7erir. LearnB, benzer \u00f6\u011frenme ve geli\u015fim hedeflerine sahip insanlar\u0131 belirlemek ve ba\u011flamak i\u00e7in Sosyal Anlam Web teknolojilerini kullanarak bu verileri toplar ve analiz eder (Siadaty vd., 2012). Ortak hedefler, sistemin anlamsal yeteneklerini kullanarak belirlenir ve analiz edilir. Daha sonra, sistem, ba\u015fkalar\u0131n\u0131n \u00f6\u011frenme \u00f6r\u00fcnt\u00fclerine dayanarak, insanlar\u0131n \u00f6\u011frenmeden yarar sa\u011flayabilecekleri konular \u00f6nermek i\u00e7in sosyal teknolojileri kullan\u0131r.<\/span><\/p>\n

LearnB sistemi, profesyonellerin di\u011fer insanlarla ve ilgili bilgilerle potansiyel olarak faydal\u0131 ba\u011flant\u0131lar kurmas\u0131n\u0131 ve de\u011ferlendirmesini sa\u011flayan bir \u201cgeli\u015fimsel radar\u201d i\u015flevi g\u00f6r\u00fcr (Siadaty, Jovanovi\u0107, Ga\u0161evi\u0107, Jeremic ve Holocher-Ertl, 2010; Holocher-Ertl vd., 2012). \u00d6\u011frenme ilerlemelerini takip ederken profesyonellere \u00f6\u011frenme stratejileri konusunda tavsiyede bulunmak i\u00e7in kullan\u0131labilir. Buradaki fikir, insanlar\u0131n benzer deneyime sahip di\u011fer insanlar i\u00e7in etkili olan stratejileri kullanarak etkili bir \u015fekilde \u00f6\u011frenebilecekleridir. Sistem, sadece \u00f6\u011frenme deneyimlerini belgelemekle kalmay\u0131p ayn\u0131 zamanda gelecekte de benzer \u015fekilde \u00f6\u011frenmeden faydalanabilecek ba\u015fkalar\u0131 i\u00e7in bu deneyimleri m\u00fcmk\u00fcn k\u0131lmak i\u00e7in profesyonelleri desteklemektedir. \u00d6\u011frenme deneyimlerini belgeleyerek, ba\u015fkalar\u0131n\u0131n performans\u0131n\u0131 veya k\u0131yaslama \u00f6l\u00e7\u00fctleriyle kar\u015f\u0131la\u015ft\u0131rmak ve kar\u015f\u0131la\u015ft\u0131rmak m\u00fcmk\u00fcnd\u00fcr. \u00d6rne\u011fin, yeni bir prosed\u00fcrde yetkin olman\u0131n ortalama alt\u0131 ayl\u0131k bir deneyime sahip oldu\u011funu bilmek faydal\u0131 olabilir. Di\u011fer yandan, birka\u00e7 saat i\u00e7inde yeni bir beceri \u00f6\u011frenilebilece\u011fini bilmek g\u00fcven verici olabilir (Siadaty vd., 2012).<\/span><\/p>\n

B \u00d6\u011frenmesi deneyi, sistemi profesyonellerin \u00f6z y\u00f6netimli \u00f6\u011frenme becerilerinin aktif geli\u015fimi ile b\u00fct\u00fcnle\u015ftirmenin \u00f6nemini g\u00f6stermi\u015ftir. B \u00d6\u011freneni kullanan profesyoneller, dikkatlerini, \u00e7al\u0131\u015ft\u0131klar\u0131 ortamlardan farkl\u0131 ba\u011flamlarda veya b\u00f6l\u00fcmlerden kaynaklanan, yararl\u0131 bilgilere y\u00f6nelttiler. Ayr\u0131ca, di\u011fer insanlar\u0131n \u00f6\u011frendikleri \u00e7al\u0131\u015fma bi\u00e7imlerini anlamalar\u0131na yard\u0131mc\u0131 olan di\u011fer insanlar\u0131n gayriresm\u00ee \u00e7al\u0131\u015fmalar\u0131 ve \u00f6\u011frenme uygulamalar\u0131 hakk\u0131ndaki verilere eri\u015fimin yararl\u0131 oldu\u011funu da alg\u0131lad\u0131lar. Sosyal ba\u011flamlar\u0131 -\u00f6rne\u011fin, ba\u015fkalar\u0131n\u0131n \u00f6\u011frenmek i\u00e7in yapt\u0131klar\u0131 eylemlerden haberdar olma- hakk\u0131ndaki g\u00fcncellemelerden ve mevcut \u00f6\u011frenme kaynaklar\u0131n\u0131n meslekta\u015flar\u0131 taraf\u0131ndan nas\u0131l kullan\u0131ld\u0131\u011f\u0131 hakk\u0131nda bilgilendirilmekten yararland\u0131klar\u0131n\u0131 alg\u0131lad\u0131lar (Siadaty, 2013). Bununla birlikte, kritik bir nokta, bu profesyonellerin, organizasyonun her i\u015f rol\u00fc i\u00e7in gereken yetkinlikleri \u00f6nceden belirledi\u011fi ve insanlar\u0131n nas\u0131l g\u00f6sterdi\u011fini \u00f6nerdi\u011fi \u00f6neride bulundu\u011fu Clow (2013) taraf\u0131ndan tart\u0131\u015f\u0131lan \u201cyukar\u0131dan a\u015fa\u011f\u0131\u201d yeterlilik sistemleriyle geleneksel bir \u00f6rg\u00fct k\u00fclt\u00fcr\u00fcnde faaliyet g\u00f6sterdikleridir. bu yetenekleri \u00f6\u011frenirler.<\/span><\/p>\n

Mirror8<\/a><\/sup>, profesyonellerin kendi deneyimlerinden ve di\u011fer deneyimlerden \u00f6\u011frenmelerini destekleyen analitik tabanl\u0131 bir sistemdir. Yans\u0131tma, motivasyon ve duyu\u015fsal fakt\u00f6rlerle \u00f6\u011frenmeyi ve performans\u0131 geli\u015ftirebilecek \u00f6z y\u00f6netimli \u00f6\u011frenmenin \u00f6nemli bir bile\u015fenidir (Littlejohn ve Hood, 2016). Ayna sistemi, \u00e7al\u0131\u015fma s\u0131ras\u0131nda informal \u00f6\u011frenmeyi kolayla\u015ft\u0131rmak i\u00e7in tasarlanm\u0131\u015f bir dizi uygulamaya (\u201cAyna\u201d uygulamalar\u0131) dayanmaktad\u0131r (Kump, Knipfer, Pammer, Schmidt ve Maier, 2011). Bu uygulamalar, \u00e7al\u0131\u015fan ayarlar\u0131nda bireysel ve ekip eylemlerinin analizini desteklemek i\u00e7in kullan\u0131lm\u0131\u015ft\u0131r. Bu yans\u0131malar hem bireylerin hem de ekiplerin, hangi uygulamalar\u0131n kurulu\u015flar\u0131 i\u00e7inde en fazla etkiye sahip oldu\u011funu \u00f6\u011frenmelerini sa\u011flad\u0131. De\u011ferlendirme \u00e7al\u0131\u015fmalar\u0131, bireysel ve tak\u0131m \u00f6\u011frenme ile \u00f6rg\u00fctsel \u00f6\u011frenme (insan kaynaklar\u0131 s\u00fcre\u00e7leri, \u00f6d\u00fcller ve promosyonlarla ba\u011flant\u0131l\u0131) aras\u0131nda a\u00e7\u0131k bir ba\u011flant\u0131 bulmu\u015ftur (Knipfer, Kump, Wessel ve Cress, 2013). K\u00fclt\u00fcrdeki ve organizasyon i\u00e7indeki insanlar\u0131n zihniyetlerinde paralel bir de\u011fi\u015fim olmazsa, yeni analitik sistemlerinin s\u0131n\u0131rl\u0131 etkisi olacakt\u0131r.<\/span><\/p>\n

SONU\u00c7: GELECEK MESLEK\u0130 \u00d6\u011eRENME ANAL\u0130T\u0130\u011e\u0130<\/h2>\n

Los Angeles’a yeni yakla\u015f\u0131mlar zaten profesyonelleri performanslar\u0131n\u0131 geli\u015ftirmeye desteklemektedir. Bu yakla\u015f\u0131mlar\u0131n analizi gelecekteki \u00e7al\u0131\u015fmalar\u0131 bilgilendirebilecek yeni ortaya \u00e7\u0131kan temalara i\u015faret etmektedir.<\/span><\/p>\n

Analitik i\u00e7in \u00e7e\u015fitli yakla\u015f\u0131mlar, insan zek\u00e2s\u0131n\u0131 geli\u015ftirmek i\u00e7in makine bazl\u0131 analiti\u011fi kullan\u0131r. Bununla birlikte, sistem ile insan aras\u0131ndaki ba\u011flant\u0131 bir\u00e7ok nedenden dolay\u0131 bir risk noktas\u0131d\u0131r. \u00d6ncelikle, profesyoneller \u00f6\u011frenme ihtiya\u00e7lar\u0131n\u0131 tan\u0131mlayabilmeli ve onlara g\u00f6re hareket edebilmelidir, bu nedenle \u00f6z y\u00f6netimli \u00f6\u011frenme yetene\u011fi bir\u00e7ok analitik tekni\u011finin ba\u015far\u0131s\u0131 i\u00e7in kritik \u00f6neme sahiptir. \u0130kincisi, k\u00fclt\u00fcrde ve organizasyon i\u00e7indeki insanlar\u0131n zihniyetlerinde paralel bir de\u011fi\u015fim olmadan, analitik temelli \u00f6\u011frenme sistemlerinin s\u0131n\u0131rl\u0131 etkisi olacakt\u0131r. \u00d6A’ya yakla\u015f\u0131mlar\u0131n uygulanmas\u0131 bu insan unsurlar\u0131n\u0131 g\u00f6z \u00f6n\u00fcnde bulundurmal\u0131d\u0131r.<\/span><\/p>\n

Baz\u0131 \u00d6A teknikleri veri toplamak i\u00e7in a\u011f analizini kullan\u0131r. \u0130\u015fyerinde \u00f6\u011frenme, \u00f6\u011frenme s\u00fcre\u00e7leri \u00f6rg\u00fctsel ve proje hedefleriyle ayn\u0131 \u00e7izgide oldu\u011funda en etkilidir (Kimmerle, Cress ve Held, 2010; Kozlowski ve Klein, 2000). A\u011f analizi, bireysel \u00f6\u011frenme faaliyetlerini ak\u0131ll\u0131ca kurumsal \u00f6\u011frenme hedefleriyle uyumlu hale getirmeyi ama\u00e7lamal\u0131d\u0131r.<\/span><\/p>\n

M\u00d6A’na y\u00f6nelik umut vaat eden di\u011fer yakla\u015f\u0131mlar, yaz\u0131l\u0131m uygulamalar\u0131n\u0131n (veya uygulamalar\u0131n) geli\u015ftirilmesine dayan\u0131r. \u0130deal olarak, belirli bir uzmanl\u0131\u011fa sahip profesyoneller kodu yazar. Bununla birlikte, t\u00fcm profesyoneller kod yazma yetene\u011fine sahip de\u011fildir, bu nedenle, bir\u00e7ok meslek i\u00e7in uygulamalar, i\u015f rol\u00fcn\u00fc derinlemesine anlamayan insanlar taraf\u0131ndan geli\u015ftirmektedir. Bu sorunun teknik olmayan sekt\u00f6rlerde daha yayg\u0131n olmas\u0131 muhtemeldir.<\/span><\/p>\n

Bir\u00e7ok M\u00d6A metodu, yetenek ve \u00f6\u011frenmeyi deneyim yakalama ve yayg\u0131nla\u015ft\u0131rma yoluyla \u00f6\u011frenmek i\u00e7in \u00e7evik yakla\u015f\u0131mlar\u0131 yerle\u015ftirmeyi ama\u00e7lamaktad\u0131r. Bu yakla\u015f\u0131mla ilgili bir tak\u0131m problemler vard\u0131r; \u00f6rne\u011fin, t\u00fcm uzmanl\u0131k alanlar\u0131 kodlanamaz;uzmanl\u0131k geli\u015ftirme yollar\u0131n\u0131 modellemek zordur \u00e7\u00fcnk\u00fc her bireyin yeni bir beceri \u00f6\u011frenmeye aktif olarak d\u00e2hil olmas\u0131 i\u00e7in, kendine \u00f6zg\u00fc bir \u00f6n bilgisi ve mesleki temeli vard\u0131r. Bu zorluklar, analitik \u00e7\u00f6z\u00fcmlerinin sadece yetenek ve deneyim geli\u015ftirmenin teknik ve pratik y\u00f6nlerini ele almakla kalmay\u0131p, ayn\u0131 zamanda duygusal ve g\u00fcd\u00fcsel konularla da ilgilenmesi gerekti\u011fini g\u00f6stermektedir.<\/span><\/p>\n

Ancak emekleme d\u00f6nemindeki mesleki \u00f6\u011frenme analiti\u011fi gelecekteki \u00f6\u011frenme ve \u00e7al\u0131\u015fma i\u00e7in bir temel olu\u015fturmak \u00fczere ayarlanm\u0131\u015ft\u0131r. Ancak profesyonellerin analitik uygulamalarla nas\u0131l \u00f6\u011frendi\u011fi hakk\u0131ndaki bilgilerin uyumuna dikkat edilmelidir.<\/span><\/p>\n

KAYNAK\u00c7A<\/h2>\n

Attwell, G., Heinemann, L., Deitmer, L., K\u00e4ma\u00e4inen, P. (2013). Developing PLEs to support work practice based learning. In eLearning Papers #35, Nov. 2013. http:\/\/OpenEducationEuropa.eu\/en\/elearning_papers <\/span><\/span><\/p>\n

Argyris, C., & Schon, D. A. (1974). Theory in practice: Increasing professional effectiveness<\/i>. San Francisco, CA: Jossey-Bass, 1974. <\/span><\/span><\/p>\n

Baker, R.S. (2016). Stupid tutoring systems, intelligent humans. International Journal of Artificial Intelligence in Education, 26<\/i>(2), 600\u2013614. <\/span><\/span><\/p>\n

Berendt, B., Vuorikari, R., Littlejohn, A., & Margaryan, A. (2014). Learning analytics and their application in technology-enhanced professional learning. In A. Littlejohn & A. Margaryan (Eds.), Technology-enhanced professional learning: Processes, practices and tools <\/i>(pp. 144\u2013157). London: Routledge. <\/span><\/span><\/p>\n

Boud, D., & Garrick, J. (1999). Understanding learning at work<\/i>. Taylor & Francis US. <\/span><\/span><\/p>\n

Billett, S. (2004). Workplace participatory practices: Conceptualising workplaces as learning environments. Journal of Workplace Learning, 16<\/i>(6), 312\u2013324. <\/span><\/span><\/p>\n

Buckingham Shum, S., & Deakin Crick, R. (2012). Learning dispositions and transferable competencies: Pedagogy, modelling and learning analytics. Proceedings of the 2nd International Conference on Learning Analytics and Knowledge <\/i>(LAK\u201912), 29 April\u20132 May 2012, Vancouver, BC, Canada (pp. 92\u2013101). New York: ACM.<\/span><\/span><\/p>\n

Buckingham Shum, S., & Ferguson, R. (2012). Social learning analytics. Educational Technology & Society, 15<\/i>(3), 3\u201326. <\/span><\/span><\/p>\n

Clow, J. (2013) Work practices to support continuous organisational learning. In A. Littlejohn & A. Margaryan (Eds.), Technology-enhanced professional learning: Processes, practices, and tools <\/i>(pp. 17\u201327). London: Routledge. <\/span><\/span><\/p>\n

Collin, K. (2008). Development engineers\u2019 work and learning as shared practice. International Journal of Lifelong Education, 27<\/i>(4), 379\u2013397. <\/span><\/span><\/p>\n

Convertino, G., Grasso, A., DiMicco, J., De Michelis, G., & Chi, E. H. (2010). Collective intelligence in organizations: Towards a research agenda. Proceedings of the 2010 ACM Conference on Computer Supported Cooperative Work <\/i>(CSCW 2010), 6\u201310 February 2010, Atlanta, GA, USA (pp. 613\u2013614). New York: ACM. http:\/\/ research.microsoft.com\/en-us\/um\/redmond\/groups\/connect\/CSCW_10\/docs\/p613.pdf <\/span><\/span><\/p>\n

Dennerlein, S., Theiler, D., Marton, P., Santos, P., Cook, J., Lindstaedt, S., & Lex, E. (2015) KnowBrain: An online social knowledge repository for informal workplace learning. Proceedings of the 10th European Conference on Technology Enhanced Learning <\/i>(EC-TEL\u201915), 15\u201317 September 2015, Toledo, Spain. http:\/\/eprints.uwe.ac.uk\/26226 <\/span><\/span><\/p>\n

Endedijk, M. (2016) Presentation at the Technology-enhanced Professional Learning (TePL) Special Interest Group, Glasgow Caledonian University, May 2016. <\/span><\/span><\/p>\n

Eraut, M. (2000). Non-formal learning and tacit knowledge in professional work. British Journal of Educational Psychology, 70<\/i>(1), 113\u2013136. <\/span><\/span><\/p>\n

Eraut, M. (2004). Informal learning in the workplace. Studies in Continuing Education, 26<\/i>(2), 247\u2013273. <\/span><\/span><\/p>\n

Eraut, M. (2007). Learning from other people in the workplace. Oxford Review of Education, 33<\/i>(4), 403\u2013422. <\/span><\/span><\/p>\n

Engestr\u00f6m, Y. (1999). Innovative learning in work teams: Analyzing cycles of knowledge creation in practice. Perspectives on activity theory<\/i>, 377-404. <\/span><\/span><\/p>\n

Engestr\u00f6m, Y. (2008). From teams to knots: Activity-theoretical studies of collaboration and learning at work. Cambridge, UK: Cambridge University Press. <\/span><\/span><\/p>\n

Ferguson, R. (2012) Learning analytics: Drivers, developments and challenges. International Journal of Technology Enhanced Learning, 4<\/i>(5\u20136), 304\u2013317. <\/span><\/span><\/p>\n

Fuller, A., Ashton, D., Felstead, A., Unwin, L., Walters, S., & Quinn, M. (2003). The impact of informal learning for work on business productivity. London: Department of Trade and Industry. <\/span><\/span><\/p>\n

Fuller, A., & Unwin, L. (2004). lntegrating organizational and personal development. Workplace learning in context<\/i>, 126. <\/span><\/span><\/p>\n

Gillani, N., & Eynon, R. (2014). Communication patterns in massively open online courses. The Internet and Higher Education, 23, <\/i>18\u201326. <\/span><\/span><\/p>\n

Harteis, C., & Billett, S. (2008). The workplace as learning environment: Introduction. International Journal of Educational Research, 47<\/i>(4), 209\u2013212. <\/span><\/span><\/p>\n

HEC Report (2016) From bricks to clicks: Higher Education Commission Report http:\/\/www.policyconnect.org.uk\/hec\/sites\/site_hec\/files\/report\/419\/fieldreportdownload\/frombrickstoclicks-hecreportforweb.pdf <\/span><\/span><\/p>\n

Holocher-Ertl, T., Fabian, C. M., Siadaty, M., Jovanovi\u0107, J., Pata, K., & Ga\u0161evi\u0107, D. (2011). Self-regulated learners and collaboration: How innovative tools can address the motivation to learn at the workplace? Proceedings of the 6th European Conference on Technology Enhanced Learning: Towards Ubiquitous Learning <\/i>(EC-TEL 2011), 20\u201323 September 2011, Palermo, Italy (pp. 506\u2013511). Springer Berlin Heidelberg. <\/span><\/span><\/p>\n

IBM (2008) Making change work. IBM Global Study. http:\/\/www-07.ibm.com\/au\/pdf\/making_change_work.pdf <\/span><\/span><\/p>\n

de Laat, M., & Schreurs, B. (2013). Visualizing informal professional development networks: Building a case for learning analytics in the workplace. American Behavioral Scientist, 57<\/i>(10), 1421\u20131438.<\/span><\/span><\/p>\n

Kimmerle, J., Cress, U., & Held, C. (2010). The interplay between individual and collective knowledge: Technologies for organisational learning and knowledge building. Knowledge Management Research & Practice, 8<\/i>(1), 33\u201344. <\/span><\/span><\/p>\n

Kirschenmann, U., Scheffel, M., Friedrich, M., Niemann, K., & Wolpers, M. (2010). Demands of modern PLEs and the ROLE approach. In M. Wolpers, P. A. Kirschner, M. Scheffel, S. N. Lindstaedt, & V. Dimitrova (Eds.), Proceedings of the 5th European Conference on Technology Enhanced Learning, Sustaining TEL: From Innovation to Learning and Practice <\/i>(EC-TEL 2010), 28 September\u20131 October 2010, Barcelona, Spain (pp. 167\u2013182). Springer Berlin Heidelberg. <\/span><\/span><\/p>\n

Kozlowski, S. W. J., & Klein, K. J. (2000). A multilevel approach to theory and research in organizations: Contextual, temporal, and emergent processes. In K. J. Klein & S. W. J. Kozlowski (Eds.), Multilevel theory, research and methods in organizations: Foundations, extensions, and new directions <\/i>(pp. 3\u201390). San Francisco, CA: Jossey-Bass. <\/span><\/span><\/p>\n

Knipfer, K., Kump, B., Wessel, D., & Cress, U. (2013). Reflection as a catalyst for organisational learning. Studies in Continuing Education, 35<\/i>(1), 30\u201348. <\/span><\/span><\/p>\n

Kroop, S., Mikroyannidis, A., & Wolpers, M. (Eds.). (2015). Responsive open learning environments: Outcomes of research from the ROLE project. Springer. <\/span><\/span><\/p>\n

Kump, B., Knipfer, K., Pammer, V., Schmidt, A., & Maier, R. (2011) The role of reflection in maturing organizational know-how. Proceedings of the 1st European Workshop on Awareness and Reflection in Learning Networks <\/i>(@ EC-TEL 2011), 21 September 2011, Palermo, Italy. <\/span><\/span><\/p>\n

Ley, T., Cook, J., Dennerlein, S., Kravcik, M., Kunzmann, C., Pata, K., & Trattner, C. (2014). Scaling informal learning at the workplace: A model and four designs from a large-scale design-based research effort. British Journal of Educational Technology, 45<\/i>(6), 1036\u20131048. <\/span><\/span><\/p>\n

Littlejohn, A., & Hood, N. (2016, March 18). How educators build knowledge and expand their practice: The case of open education resources. British Journal of Educational Technology<\/i>. doi: 10.1111 \/ bjet.12438 <\/span><\/span><\/p>\n

Littlejohn, A., & Margaryan, A. (2013). Technology-enhanced professional learning: Mapping out a new domain. In A. Littlejohn & A. Margaryan (Eds.), Technology-enhanced professional learning: Processes, practices, and tools <\/i>(Chapter 1). Taylor & Francis. <\/span><\/span><\/p>\n

Littlejohn, A., Milligan, C., & Margaryan, A. (2012). Charting collective knowledge: Supporting self-regulated learning in the workplace. Journal of Workplace Learning, 24<\/i>(3), 226\u2013238. <\/span><\/span><\/p>\n

Milligan, C., Littlejohn, A., & Margaryan, A. (2014). Workplace learning in informal networks. Reusing Open Resources: Learning in Open Networks for Work, Life and Education<\/i>, 93. <\/span><\/span><\/p>\n

Nistor, N., Derntl, M., & Klamma, R. (2015). Learning analytics: Trends and issues of the empirical research of the years 2011\u20132014. Proceedings of the 10th European Conference on Technology Enhanced Learning: Design for Teaching and Learning in a Networked World <\/i>(EC-TEL 2015), 15\u201317 September 2015, Toledo, Spain (pp. 453\u2013459). Springer. <\/span><\/span><\/p>\n

Rienties, B., Boroowa, A., Cross, S., Kubiak, C., Mayles, K., & Murphy, S. (2016). Analytics4Action evaluation framework: A review of evidence-based learning analytics interventions at the Open University UK. Journal of Interactive Media in Education, 2016<\/i>(1). www-jime.open.ac.uk\/articles\/10.5334\/jime.394\/galley\/596\/ download\/ <\/span><\/span><\/p>\n

Siadaty, M. (2013). Semantic web-enabled interventions to support workplace learning<\/i>. Doctoral dissertation, Simon Fraser University, Burnaby, BC. http:\/\/summit.sfu.ca\/item\/12795 <\/span><\/span><\/p>\n

Siadaty, M., Ga\u0161evi\u0107, D., & Hatala, M. (2016). Associations between technological scaffolding and micro-level processes of self-regulated learning: A workplace study. Computers in Human Behavior, 55<\/i>, 1007\u20131019. <\/span><\/span><\/p>\n

Siadaty, M., Ga\u0161evi\u0107, D., Jovanovi\u0107, J., Pata, K., Miliki\u0107, N., Holocher-Ertl, T., \u2026 & Hatala, M. (2012). Self-regulated workplace learning: A pedagogical framework and semantic web-based environment. Educational Technology & Society, 15<\/i>(4), 75\u201388.<\/span><\/span><\/p>\n

Siadaty, M., Jovanovi\u0107, J., Ga\u0161evi\u0107, D., Jeremi\u0107, Z., & Holocher-Ertl, T. (2010). Leveraging semantic technologies for harmonization of individual and organizational learning. In M. Wolpers, P. A. Kirschner, M. Scheffel, S. N. Lindstaedt, & V. Dimitrova (Eds.), Proceedings of the 5th European Conference on Technology Enhanced Learning, Sustaining TEL: From Innovation to Learning and Practice <\/i>(EC-TEL 2010), 28 September\u20131 October 2010, Barcelona, Spain (pp. 340\u2013356). Springer Berlin Heidelberg. <\/span><\/span><\/p>\n

Siemens, G. ve Long, P. (2011) Penetrating the fog: Analytics in learning and education. EDUCAUSE Review, 46<\/i>(5), 31\u201340. http:\/\/net.educause.edu\/ir\/library\/pdf\/ERM1151.pdf <\/span><\/span><\/p>\n

Tynj\u00e4l\u00e4, P. (2008). Perspectives into learning at the workplace. Educational Research Review, 3<\/i>(2), 130\u2013154. <\/span><\/span><\/p>\n

Tynj\u00e4l\u00e4, P., & Gijbels, D. (2012). Changing world: Changing pedagogy. In P. Tynj\u00e4l\u00e4, M.-L. Stenstr\u00f6m, & M. Saarnivaara (Eds.), Transitions and transformations in learning and education <\/i>(pp. 205\u2013222). Springer Netherlands. <\/span><\/span><\/p>\n

Wen, M., Yang, D., & Ros\u00e9, C. (2014). Sentiment analysis in MOOC discussion forums: What does it tell us? In J. Stamper et al. (Eds.), Proceedings of the 7th International Conference on Educational Data Mining <\/i>(EDM2014), 4\u20137 July 2014, London, UK. International Educational Data Mining Society. http:\/\/www.cs.cmu.edu\/~mwen\/papers\/edm2014-camera-ready.pdf <\/span><\/span><\/p>\n

Wolff, A., Zdrahal, Z., Nikolov, A., & Pantucek, M. (2013, April). Improving retention: Predicting at-risk students by analysing clicking behaviour in a virtual learning environment. Proceedings of the 3rd International Conference on Learning Analytics and Knowledge <\/i>(LAK\u201913), 8\u201312 April 2013, Leuven, Belgium (pp. 145\u2013149). New York: ACM.<\/span><\/span><\/p>\n

\n
\n

1<\/a> https:\/\/wekit-community.org\/<\/span><\/span><\/p>\n<\/div>\n

\n

2<\/a> the WEKIT.club<\/span><\/span><\/p>\n<\/div>\n

\n

3<\/a> learning\u2013layers.eu<\/span><\/span><\/p>\n<\/div>\n

\n

4<\/a> odl.learning-layers.eu<\/span><\/span><\/p>\n<\/div>\n

\n

5<\/a> developer.learning-layers.eu<\/span><\/span><\/p>\n<\/div>\n

\n

6<\/a> role-project.eu<\/span><\/span><\/p>\n<\/div>\n

\n

7<\/a> \u00d6z Denetimli Bir \u00d6\u011frenen Olmada ROL Kursu (http:\/\/www.open.edu\/openlearnworks\/course\/view.php?id=1490)<\/span><\/span><\/p>\n<\/div>\n

\n

8<\/a> www.mirror\u2013project.eu<\/span><\/span><\/p>\n<\/div>\n","protected":false},"author":1,"menu_order":6,"template":"","meta":{"pb_show_title":"on","pb_short_title":"","pb_subtitle":"","pb_authors":[],"pb_section_license":""},"chapter-type":[48],"contributor":[],"license":[],"class_list":["post-101","chapter","type-chapter","status-publish","hentry","chapter-type-numberless"],"part":73,"_links":{"self":[{"href":"https:\/\/acikkitap.com.tr\/oaek\/wp-json\/pressbooks\/v2\/chapters\/101","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\/101\/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\/101\/metadata\/"}],"wp:attachment":[{"href":"https:\/\/acikkitap.com.tr\/oaek\/wp-json\/wp\/v2\/media?parent=101"}],"wp:term":[{"taxonomy":"chapter-type","embeddable":true,"href":"https:\/\/acikkitap.com.tr\/oaek\/wp-json\/pressbooks\/v2\/chapter-type?post=101"},{"taxonomy":"contributor","embeddable":true,"href":"https:\/\/acikkitap.com.tr\/oaek\/wp-json\/wp\/v2\/contributor?post=101"},{"taxonomy":"license","embeddable":true,"href":"https:\/\/acikkitap.com.tr\/oaek\/wp-json\/wp\/v2\/license?post=101"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}