BAĞLANTICILIK TEORİSİ VE ÖĞRETMEN ADAYLARININ ÖĞRENME AĞLARININ SOSYAL AĞ ANALİZİ
Bu araştırmanın temel amacı, öğretmen adaylarının yeni öğrenmelerde en çok hangi kaynaklardan yararlandıklarını belirlemek ve sınıf içi etkileşimlerde öğrenme ağlarının örüntüsünü ortaya çıkarmaktır. Sosyal ağ analizi ve nitel araştırma yaklaşımlarının birlikte kullanıldığı karma araştırma yaklaşımıyla yürütülen araştırma, 2015-2016 öğretim yılında Sinop Üniversitesi Eğitim Fakültesinde öğretmen yetiştirme programı içinde yer alan 56 öğrencinin katılımı ile gerçekleştirilmiştir. Araştırmanın örneklemi amaçlı örnekleme ile belirlenmiştir. Araştırmanın örneklemini belirtilen dönemde sınıf yönetimi dersine devam eden öğretmen adayları oluşturmuştur. Araştırmanın verileri araştırmacı tarafından oluşturulan veri formu ile yarı-yapılandırılmış görüşme tekniği ile toplanmıştır. Araştırmanın analizlerinde nitel verilerde betimsel analiz; sosyal ağ verilerinde UCINET 6.0 yazılımı ile ağ yapısı, yoğunluk, kümeleme, karşılılıklılık, geçişlilik, klik analizler ve bağlantıların gücünün analizinde derece, yakınlık, arasındalık ve özvektör merkeziliği gibi sosyal ağ analizine özgü merkezilik ölçümlerinden yararlanılmıştır. Araştırmanın bulgularına göre öğretmen adayları öğrenmelerinde en çok dijital kaynaklardan yararlanmaktadır. Öğretim elemanlarından sorma ikinci; akranlarından öğrenmeler üçüncü, yazılı kaynaklardan öğrenmeler dördüncü sırada yer almıştır. Öğretmen adayları dijital kaynaklar içinde en çok kolay erişilebilir hazır kaynaklardan yararlanmaktadır. Makale, tezler gibi bilimsel nitelikli dijital kaynaklardan yararlanma çok düşük bulunmuştur. Araştırmanın sosyal ağ analizi bulguları da bu bulguları desteklemiştir. Nitel kısımda akranlar en düşük düzeyde öğrenme kaynağı olarak tanımlanmıştır. Sosyal ağ analizi bulgularına göre sınıf içi öğrenme etkileşimlerinin oluşturduğu öğrenme ağının yoğunluğu düşük bulunmuştur. Ağ içinde öne çıkan aktörler, klikler, ağ içinde parçalanmalar söz konusudur. Ağ yapısı gevşek yapılanmıştır ve dış bağlantılarla desteklenmektedir. Sosyal ağ analizi verileri, öğretmenin sınıfta öğrenme süreçlerini yapılandırırken daha verilere dayalı kararlar almasını ve doğru aktörler için doğru müdahalelerde bulunmasını sağlayacaktır. Araştırma bulguları, bağlantıcılık ve ağ yaklaşımlarının öğrenme ve öğrenme odaklı sınıf içi etkileşimleri derinlemesine ortaya koyma potansiyelinin yüksek olduğunu göstermektedir. Öğrenme ağlarını derinlemesine inceleyen daha fazla araştırmaya ihtiyaç vardır. Yeni araştırmalar karşılaştırmalı değerlendirmeler yapma fırsatı sağlayacaktır.
CONNECTIVIZM THEORY AND SOCIAL NETWORK ANALYSIS OF LEARNING NETWORKS OF TEACHER CANDIDATES
In the 21st century, the world is rapidly changing and transforming. These changes and transformed factors also transform education. Connectivism is a new theory that has been proposed as the learning theory of the 21st century. Advocates of Connectivizm Theory have taken complexity sciences and network approaches as sources and outlets for them and have based their learning theories on the principles of complex science. Connectivity is the unification of the principles put forward by chaos, network, complexity and self-organization theories. The main purpose of this research is to identify the most likely sources of teacher candidates for new learning and to reveal the pattern of learning networks in classroom interactions. The research, which is carried out by a mixed research approach which is used together with social network analysis and qualitative research approaches, was carried out with the participation of 56 students who were included in teacher training program in Sinop University Faculty of Education in 2015-2016 school year. The sampling of the study was determined by sampling. The sample of the research was composed of prospective teachers who continued to class management class in the specified period. The data of the research was collected by the data form created by the researcher and the semi-structured interview technique. In the analysis of the research, descriptive analysis of qualitative data, social networking, UCINET 6.0 software was used to measure the centrality of social network analysis such as the network structure and the strength, degree, intensity, interrelation of connections. According to the findings of the research, prospective teachers are mostly benefiting from digital resources in their learning. Learners from peers ranked third, learners from written sources ranked fourth. Social network analysis findings of the research also supported these findings. In the qualitative part, peers are defined as the lowest level of learning resources. According to social network analysis findings, the density of learning network formed by in-class learning interactions was found low. There are actors, clikers, fragmented in the network that stand out in the network. Compared to the number of actors and connections in learning networks and friendship networks, the number of connections in the learning network was found to be higher than the number of connections in the friendship network, although the learning network was found as 56 actors and friendship network as 83 actors. The first had 109 connections between 56 actors, while the second had 106 connections between 83 actors. Apart from this, in the analysis of density, clustering, reciprocity and transitivity, it is found that the learning network is more tightly connected (strong relations) and active than the network of friendships. In the study, the density of learning networks of teacher candidates was found low. In the analysis of the clique made in the research, it was found that the teacher candidates had 19 cliques in the learning network and 15 cliques in the friendship network. This indicates that there are prominent actors in the network. As a matter of fact, in the measure of centrality, 23BT is the most central actor of the learning network and 25EV is the most central actor of the friendship network. Research findings show that connectivity and networking approaches have the potential to reveal in-class interactions within the learning and learning focus. In this research, firstly, it has been revealed how much the students' learning resources are digitized and how much they see their friends as a source of learning. It is understood that the evaluation of learning processes in the light of connective theory can contribute to understanding and explaining learning processes as well as constructing learning behaviors, or at least bringing a new point of view.
___
- Astin, A. W. (1984). Student involvement: A developmental theory for higher education. Journal of
College Student Persistence, 25, 4, p.p. 75-127.
- Balcı, A. (2003). Eğitim örgütlerine yeni bakış açıları: Kuram Araştırma İlişkisi II, Kuram ve
Uygulamada Eğitim Yönetimi, 9,33, ss.26-61.
- Barabasi, A.L. (2010). Bağlantılar. İstanbul: Optimist Yayınları.
- Bell, F. (2011). Connectivism: Its place in theory-informed research and innovation in technology
enabled learning. International Review of Research in Open and Distance Learning, 12, 3,
p.p.98–118.
- Black, R. (2008). Beyond the classroom : Building new school networks. Victoria, Australia:ACER
Press.
- Borgatti, S.P.; Everett, M.G. & Freeman, L.C. (2002). UCINET for Windows, version 6.59: Software
for social network analysis. Harvard, MA: Analytic Technologies.
- Borgatti, S.P. (2002). Netdraw network visualization, Harvard, MA: Analytic Technologies.
- Boyd, D. M.& Ellison, N. B. (2007). Social network sites: Definition, history, and scholarship.
Journal of Computer-Mediated Communication, 13, 1, p.p. 304-309. Erişim adresi:
http://jcmc.indiana.edu/vol13/issue1/boyd.ellison.html
- Bozkurt, A. (2013). Açık ve uzaktan öğretim: Web 2.0 ve sosyal ağların etkileri. Akademik Bilişim
23-25 Ocak, Akdeniz Üniversitesi, Antalya. Erişim adresi: http://www.academia.
edu/2536910/Acik_ve_Uzaktan_
- Brewe, E.; Kramer, L. & Sawtelle, V. (2012). Investigating student communities with network
analysis of interactions in a physics learning center. Phys Rev Spec Top Phys Educ Res 8,
p.p. 1001-1009
- Brewe, E.; Sawtelle, Kramer, L.H., O’Brien, G.E., Rodriguez, I. & Pamela, P. (2010). Toward equity
through participation in modeling instruction in introductory university physics. Physical
Review Special Topics-Physics Education Research, 6, 1,p.p. 101-06.
- Brewe, E.; Traxler, A; Garza, J. & Kramer, L.H. (2013). Extending positive class results across
multiple instructors and multiple classes of modeling instruction. Physical Review Special
Topics-Physics Education Research, 9, 2, p.p. 201-16.
- Brewe, E. (2008). Modeling theory applied: Modeling instruction in introductory physics. American
Journal of Physics, 76, 12, p.p. 1155–1160.
- Bruun, J. & Brewe E. (2013). Talking and learning physics: predicting future grades from network
measures and Force concept inventory pretest scores. Phys Rev Spec Top Phys Educ Res, 9,
p.p. 201-09.
- Brunello, G., Paola, M. & Scoppa, V. (2010). Peer effects in higher education: does the field of study
matter. Econ Inq., 48, p.p. 621–634.
- Burt, R.S. (1992). Structural holes: The social structure of competition. Cambridge, MA: Harvard
University Press.
- Carrington, P.J., Scott, J. & Wasserman, S. (2005). Models and methods in social network
analysis.N.Y: Cambridge University Press.
- Castells, M. (2008). Ağ toplumunun yükselişi, enformasyon çağı: Ekonomi, toplum ve kültür.
İstanbul: İstanbul Bilgi Üniversitesi.
- Chiristakis, N.A. & Fowler, J.H. (2012). Sosyal ağların şaşırtıcı gücü ve yaşantımızı biçimlendiren
etkisi. İstanbul: Varlık Yayınları.
- Cilliers, P. (2004). A framework for understanding complex systems. In P. Andriani & G. Passiante
(Eds.), Complexity theory and the management of networks: proceedings of the workshop on
organisational networks as distributed systems of knowledge (pp. 3-27). London: Imperial
College Press.
- Clarà, M & Barberà, E. (2014). Three problems with the connectivist conception of learning. Journal
of Computer Assisted Learning. 30, 3, pp.197-206.
- Coursera https://www.coursera.org/ (Çevrimiçi)
- Coveney, P. (2003). Self-organization and complexity: A new age for theory, computation and
experiment. Paper presented at the Nobel symposium on self-organization at Karolinska
Institutet, Stockholm.
- Creswell, J.W. (2012). Educational research: planning, conducting, and evaluating quantitative and
qualitative research. Boston: Pearson Education, Inc.
Cross, R. & Parker, A. (2004). Sosyal şebekelerin saklı gücü. İstanbul: Henkel Yayıncılık.
- Daly, A. J., Moolenaar, N. M., Bolivar, J. M. & Burke, P. (2010). Relationships in reform: The roleof
teachers’ social networks. Journal of Educational Administration, 48, 3, p.p.359–391.
- Degenne, A. & Forse, M. (1999). Introducing social networks. London: Sage.
Duncan GJ, Boisjoly J, Kremer M, Levy DM & Eccles J. (2005). Peer effects in drug use and sex
among college students. Journal of Abnormal Child Psychology, 33, p.p.375–385.
- Downes, S. (2011). Connectivism’ and connective knowledge.
http://www.huffingtonpost.com/stephen-downes/connectivism-
andconnecti_b_804653.html.
Erişim
adresi:
- Downey, C., Muijs, D.& Brookman, A. (2017). Southampton Education School EU Daphne
IIIProject. (Dr Chris Downey and Dr Christian Bokhove). Social network analysis: applications for education research. Southampton Education School Seminar Series 16th
March 2017
- Downey, C.,.& Bokhove, C. (2017). Social network analysis: applications for education research.
Southampton Education School Seminar Series 16th March 2017
- Drucker, P.F. (2014). 21. yüzyıl için yönetim tartışmaları. 4. Baskı. İstanbul: Epsilon.
- Erdamar, G. (2010). Öğretmen adaylarının ders çalışma stratejilerini etkileyen bazı değişkenler.
Hacettepe Üniversitesi Eğitim Fakültesi Dergisi (H. U. Journal of Education), 38, s.s. 82-
93. Erişim adresi: http://www.efdergi.hacettepe.edu.tr/yonetim/icerik/makaleler/445-
published.pdf
- Ersoy, A. & Yılmaz, F. (2015). Çocukların internette araştırma yaparken karşılaştıkları olumsuz
deneyimleri ve bu deneyimlere yönelik tepkileri. Turkish Studies-International Periodical
for the Languages, Literature and History of Turkish or Turkic. 10, 11, Summer, p.p. 629-
650.
ISSN:
1308-2140,
www.turkishstudies.net,
DOI
Number:
http://dx.doi.org/10.7827/TurkishStudies.8640
- Everett, M. & Borgatti, S. (2005). Extending centrality. In P.J. Carrington, J. Scott and S. Wasserman
(Eds.), Models and methods in social network analysis (pp. 57‒76). New York: Cambridge
University Pres.
- Forsyth, D.R. (2006). Group dynamics. (4th. ed.) Belmont: Thomson Wadsworth.
- Freeman, L.C. (2004). The development of social network analysis: A study in the socıology of
scıence. Vancouver: ΣP Empirical Press.
- Galaskiewicz, J. (1996). The new network analysis and its application to organizational theory and
behavior. In D. Iacobucci (ed.), Networks and marketing, pp. 19–31. Thousand Oaks, CA:
Sage.
- Goldstein, J. A. (2008). Conceptual foundations of complexity science: Development and main
constructs. In M. Uhl-Bien & R. Marion (Eds.), Complexity leadership, Part 1: Conceptual
foundations (pp. 17-48). Charlotte, NC: IAP – Information Age Publishing Inc.
- Granovetter, M. (1973). The strength of weak ties. American Journal of Sociology, 78, p.p. 1360–
80.
- Grunspan, D.Z., Wiggins, B.L., Goodreau, S.M. (2014). Research methods understanding
classrooms through social network analysis: A primer for social network analysis in
education research. CBE—Life Sciences Education. 13, p.p.167–178.
- Gülbahar, Y.; Kalelioğlu, F. & Madran, O. (2010). Sosyal ağların eğitim amaçlı kullanımı. Erişim
adresi: http://orcun.madran.net/yayinlar/sosyal_aglarin_egitim_amacli_kullanimi.pdf
- Gürsakal, N. (2009) Sosyal ağ analizi. Bursa: Dora Yayınları.
- Hamid, S., Chang, S.& Kurnia, S. (2009). Identifying the use of online Social networking in higher
education. In same places, different spaces. Auckland: Erişim adresi:
http://www.ascilite.org.au/conferences/auckla nd09/procs/hamid-poster.pdf
- Hansen, M. T. (2002). Knowledge networks: Explaining effective knowledge sharing in multiunit
companies. Organization Science, 13, 3, 232‒248.
- Jackson, D. & Temperley, J. (2007) ‘From professional learning community to networked learning
community’, in L. Stoll and K.S. Louis (eds) Professional learning communities: Divergence, depth and dilemmas (pp. 45–62), Maidenhead, UK: Open University Press
/McGraw-Hill Education.
- Jones, C. (2015). Networked learning an educational paradigm for the age of digital networks. NY:
Springer, ISBN 978-3-319-01934-5 (eBook)
- Kapucu, N; Yuldashev, F. ; Demiroz, F. & Arslan, T. (2010). Social network analysis (SNA)
applications in evaluating MPA classes. Journal of Public Affairs Education. 16,4, p.p. 541–
563.
- Kayabaşı ve Özerbaş, (2017). Öğrenme-öğretme süreçlerinde öğrenme nesnelerinin kullanım
düzeylerine yönelik öğretmen görüşleri. Türk Bilim Araştırma Vakfı, TÜBAV Bilim, 10, 2,
s.s. 126-141.
- Keleş, A. & Keleş, A. (2018). Nesnelerin internetinn getirdiği yenilikler ve sorunları. Turkish
Studies-Information Technologies & Applied Sciences. 13, 13, Spring, p.p. 53-66. ISSN:
1308-2140,
www.turkishstudies.net,
DOI
Number:
http://dx.doi.org/10.7827/TurkishStudies.13872
- Kilduff, M. & Tsai, W. (2007) Social networks and organizations. London: SAGE Publications. Kop,
R., & Hill, A. (2008). Connectivism: Learning theory of the future or vestige of the past?
International Review of Research in Open and Distance Learning, 9, 3, Erişim adresi:
http://www.irrodl.org/index.php/irrodl/article/view/523/1103
- Kotler, P. ve Caslione, J.A. (2009). Kaos yönetimi: Çalkantılar çağında yönetim ve pazarlama (Çev.
Kıvanç Dündar). İstanbul: Optimist Yayınları.
- Krackhardt, D. (1998). Simmelian ties: Super strong and sticky. In R. Kramer and M. Neale (eds),
Power and influence in organizations, pp. 21–38. Thousand Oaks, CA: Sage.
- Krackhardt, D., & Hanson, J. R. (1993). Informal networks: The company behind the chart. Harvard
Business Review, 71, 4, 104‒113.
- Küçükahmet, L. (1987). Öğrencilerin çalışma alışkanlıkları ve tutumları, üniversite öğrencileri
üzerine bir araştırma. Ankara: Ankara Üniversitesi Eğitim Bilimleri Fakültesi Yayınları.
- Lynch, M. (2017). What is a personal learning network? The Tech Edvocate. August 5, 2017, Erişim
adresi: https://www.thetechedvocate.org/personal-learning-network/
- Marion, R. (2008). Complexity theory for organization and organizational leadership. In M. Uhl-
Bien & R. Marion (Eds.), Complexity leadership: Conceptual foundations (pp. 1‒15).
Charlotte, NC: IAP – Information Age Publishing Inc.
- Marsden, P.V. (2005). Recent developments in Network measurement models and methods in social
network analysis. In P.J. Carrington, J. Scott and S. Wasserman. Models and methods in
social network analysis (p.p. 8-30). New York: Cambridge University Pres.
- McCormick,R., Fox, A., Carmichael, P. & Procter, R.
understandingeducational networks. NewYork: Routledge.
(2011).
Researching
and
- Moolenaar, N.M. (2012). A social network perspective on teacher collaboration in schools: Theory,
methodology and applications. American Journal of Education. 119, p.p. 7-39.
- Moolenaar, N.M. & Daly, A.J. (2012). Social networks in education: Exploring the social side of the
reform equation. American Journal of Education. 119, 1, p.p. 1-6.
- Morgan, G. (1998). Yönetim ve örgüt teorilerinde metafor. İstanbul: MESS, Yayın No:280.
- Murray, C. (2008). Schools and social networking: Fear or education?’, Synergy Perspectives:Local,
6, 1, pp. 8-12.
- Nora, A. (2003). Access to higher education for hispanic students: Real or illusory? In J. Castellanos
and L. Jones, editor, The majority in the minority: Expanding the representation of Latina
faculty, administrators and students in higher education. Sterling, VA: Stylus Publishing.
- O’Brien, M., Varga-Atkins, T., Qualter, A., Burton, D., Campbell, A. & Jones, E. (2008). The
Liverpool learning networks: Developing, deepening, delivering. Final Report of the
Liverpool Learning Networks Research Project. University of Liverpool.
- Öztaş, N. (2003). Karmaşıklık bilimleri: Kaosun kıyısında bilim ve yönetim. İçinde M. Acar ve H.
Özgür. (Eds.), Çağdaş kamu yönetimi I. (s.s. 45‒73). Ankara: Nobel Yayınevi.
- Öztaş, N. ve Acar, M. (2004). Ağbağ analizine giriş: Kavramlar ve yöntemler. İçinde M. Acar ve H.
Özgür. (Eds.), Çağdaş kamu yönetimi II. (s.s. 288‒316). Ankara: Nobel Yayınevi.
- Penuel, W.R., Fishman, B.J., Yamaguchi, R. & Gallagher, L.P. (2007). What makes professional
development effective? Strategies that foster curriculum implementation. American
Educational Research Journal, 44,4, p.p. 921–58.
- Penuel, W.R, Riel, M., Krause, A.E. & Frank, K.A. (2009). Analyzing teachers professional
interactions in a school as social capital: A social network approach. Teachers College
Record, 111, 1, p.p. 124–63.
- Penuel, W.R., Frank, K.A. & Krause, A. (2010). Between leaders and teachers: Using social network
analysis to examine the effects of distributed leadership. In Social network theoryand
educational change, (Eds.) Alan J. Daly. Cambridge, MA: Harvard University Press
- Sarsar, F., Başbay, M. ve A. Başbay, A.
(2015). Öğrenme-öğretme sürecinde sosyal
medyakullanımı. Mersin Üniversitesi Eğitim Fakültesi Dergisi, 11, 2, ss. 418-431.
- Sánchez, R.A., Cortijo, V., & Javed, U. (2014). Students' perceptions of Facebook for
academicpurposes. Computers & Education, 70, p.p.138-149.
- Sawtelle, V.; Brewe, E.; Kramer, L.H.; Singh, C.; Sabella, M. & Rebello, S. (2010).
Positiveimpacts
of modeling instruction on self-efficacy. In Proceedings of Physics Education Research
Conference.
- Saylan, N. (1998). Öğretmen adaylarının etkili öğrenme-verimli ders çalışma yeterlilikleri ve
buyeterliliklerin kaynakları. Selçuk Üniversitesi Eğitim Fakültesi VII. Eğitim Bilimleri
Kongresi, II. Cilt, Konya.
- Scott, J. (2000). Social network analysis: A handbook. London: Sage.
- Siemens, G. (2004). Connectivism: A learning theory for the digital age. Erişim adresi: http://
www.elearnspace.org/Articles/connectivism.html.
- Siemens, G. (2005). Connectivism: Learning as network-creation.
http://www.elearnspace. org/Articles/networks.html.
Erişim
adresi:
- Spiller, P. (2017). Finlandiya, Müfredat devrimi: Finlandiya eğitim sistemini nasıl değiştiriyor, BBC,
29 Mayıs 2017, https://www.bbc.com/turkce/haberler-40082945).
- Stinebrickner R, Stinebrickner TR (2006). What can be learned about peer effects using college
roommates? Evidence from new survey data and students from disadvantaged backgrounds.
Journal of Public Econ, 90, p.p.1435–1454.
- Tınmaz, H. (2012). Social networking websites as an innovative framework for connectivism.
Contemporary Educational Technology, 3,3,p.p. 234-245.
- Tinto, V. (1997). Classrooms as communities: Exploring the educational character of student
persistence. Journal of Higher Education, 68, 6. p.p. 1011-22.
- Tuncer, M. & Özüt, A. (2012). Sınıf öğretmeni adaylarının eğitsel internet kullanımına yönelik öz
yeterlik inançları. Turkish Studies- International Periodical For The Languages, Literature
and History of Turkish or Turkic. 7, 2, Spring, p.p. 1079-1091. ISSN: 1308-2140,
www.turkishstudies.net
- Tüz, M. (2004). Değişim ve kaos ortamında işletme davranışı. İstanbul: Alfa Akademi.
- Verhagen,
P.
(2006).
Connectivism:
a
new
learning
theory?.
Erişim
adresi:http://www.surfspace.nl/nl/Redactieomgeving/Publicaties/Documents/Connectivism
%20a%20new%20theory.pdf
- Wellman, B. (1988). Structural analysis: From method and metaphor to theory and substance. In
B.Wellman and S.D. Berkowitz (eds), Social structures: A network approach, (pp. 19–61).
Cambridge: Cambridge University Press.
- Williams, E.A., Zwolak, J.P., Dou, R. & Brewe, E. (2017). Engagement, integration, involvement:
supporting academic performance and developing a classroom social network. Erişim adresi:
https://arxiv.org/pdf/1706.04121.pdf
- Wilson J. (2007). Peer effects and cigarette use among college students. Econ Journal, 35, p.p. 233–
247.
- Uhl-Bien, M., Marion, R., & McKelvey, B. (2007). Complexity leadership theory: Shifting
leadership from the industrial age to the knowledge era. The Leadership Quarterly, 18, 4,
p.p. 298-318.
- Ushakov, K.M. & Kukso, K.N. (2015). Advantages of social network analysis in educational
research. Russian Education & Society, 57, 10, pp. 871–888.
- Uğurlu, Z. (2013). Eğitim örgütlerinin örgütsel ağbağ düzeneğindeki konumunun işbirliği
düzeylerine etkisi. Ankara: Ankara Üniversitesi Eğitim Bilimleri Enstitüsü, Yayınlanmamış
Doktora Tezi.
- Uğurlu, Z. (2016). The effect of the position of educational organizations within the social network
on their collaboration levels. Universal Journal of Educational Research, 4,12A, p.p. 226‒
254.
- Vural, Z. B. A., ve Bat, M. (2010). Yeni bir iletişim ortamı olarak sosyal medya: Ege Üniversitesi
İletişim Fakültesine yönelik bir araştırma. Journal of Yasar University, 20, 5, s.s.3348-3382.
- Yıldırım, A. ve Şimşek, H. (2003). Sosyal bilimlerde nitel araştırma yöntemleri. Ankara: Seçkin
Yayıncılık.