Adapting Social Media Behavior Scales To Turkish: Validity and Reliability Analysis

Yıl 2019, , 217 - 234, 31.12.2019

Emel Dikbaş Torun

https://doi.org/10.31123/akil.620551

Cited By: 4

Öz

In this study, it is aimed to adapt the two scales, the outside school social media behavior

(OSSMB) and inside school social media behavior scale (ISSMB) into Turkish, which were developed by Lu et.al (2018). OSSMB includes 21 items, and ISSMB includes 10 items. OSSMB Scale has four sub-dimensions: Consuming, Communicating,

Creating, and Sharing. The OSSMB scale has three sub-dimensions: Consuming, Creating, and Sharing. The first part of the study data was collected with the participation

of 806 university students attending a public university in the Aegean Region. Further data were collected from 365 students for confirmatory factor analysis of the scales. Data were collected from 1171 students in total. The Turkish version of the scale was started with a language validity study. The translation and back-translation stages of the Turkish version of the scale were performed by three language experts and three field experts. After language validity, Kaiser-Meyer_Olkin, Bartlett’s, Exploratory

Factor Analysis (AFA), Confirmatory Factor Analysis (CFA) and Cronbach’s Alpha reliability and validity analyzes were performed. In the results, the factor loads of all items were good (above .61), and the total variances explained for both scales were high (ISSMB: 67.64% OSSMB: 56.71). The internal consistency values of both scales are acceptable for all factors. The factor structures obtained from the exploratory factor analysis have been confirmed by the confirmatory factor analysis with valid and reliable

measurement scales measuring the difference between the social media use of young people in Turkey within and outside the school.

Anahtar Kelimeler

Social Media, Instagram, Whatsapp, Facebook, Validity and Reliability, Scale Adaptation

Sosyal Medya Davranışları Ölçeğinin Türkçe Formunun Geliştirilmesi: Geçerlik ve Güvenirlik Çalışması

Öz

Bu
çalışmada, Lu ve arkadaşları tarafından (2018) İngilizce olarak geliştirilen, gençlerin
okul içi ve okul dışındaki sosyal medya davranışlarını ölçen iki farklı ölçeğin
Türkçe formunun geliştirilmesiyle, Türkiye’de üniversite öğrencilerinin sosyal
medya kullanımı davranışlarının çeşitli değişkenler açısından incelenmesi
amaçlanmıştır. Üniversite Öğrencilerinin Okul Dışı Sosyal Medya Davranışları
Ölçeği (ODSMD) 21 madde; Üniversite öğrencilerinin Okul İçi Sosyal Medya
Davranışları Ölçeği (OİSMD) ise 10 maddedir. ODSMD Ölçeği; tüketme, iletişim,
oluşturma ve paylaşma olmak üzere dört faktörlü; OİSMD Ölçeği; tüketme,
oluşturma ve paylaşma olmak üzere üç faktörlü yapıdadır.  Çalışma verileri, Ege Bölgesi’ndeki bir
devlet üniversitesine devam eden toplam 806 üniversite öğrencisinin katılımıyla
toplanmıştır.  Dil eşdeğerliği
sağlandıktan sonra ölçeklerin geçerlik ve güvenirlik çalışmaları yapılmıştır. Kaiser-Meyer-Olkin,
Bartlett’s, Açımlayıcı Faktör Analizi (AFA), Doğrulayıcı Faktör Analizi (DFA)
ve Cronbach’s Alpha testleri ile ölçeklerin geçerlik ve güvenirlik hesaplamaları
yapılmıştır. Sonuçlarda, tüm maddelerin faktör yüklerinin iyi olduğu ve her iki
ölçek için de açıklanan toplam varyansın yeterli düzeyde olduğu (OİSMD: %61,35.
ODSMD: %55,17) görülmüştür. İki ölçeğin de iç tutarlılık değerlerinin tüm
faktörler için kabul edilebilir düzeyde olduğu görülmüştür. Açımlayıcı faktör analizleri
ile elde edilen sonuçlar, doğrulayıcı faktör analizleri ile doğrulanarak
Türkiye’de üniversite öğrencilerinin sosyal medya kullanım davranışlarının okul
içinde ve dışındayken nasıl farklılaştığını ölçen geçerli ve güvenilir bir ölçme
aracı elde edilmiştir.  

Anahtar Kelimeler

sosyal medya, Instagram, Whatsapp, Facebook, Geçerlik ve Güvenirlik, Ölçek Uyarlama

Kaynakça

• Baym, N. K. (2015). Social media and the struggle for society. Social Media + Society 1(1), 1-2.
• Bentler, P. M. & Bonett, D.G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88, 588-606.
• Bentler, P. M. (1980). Multivariate analysis with latent variables: Casual modeling. Annual Review of Psychology, 31, 419-456.
• Bolton, R., Parasuraman, A., Hoefnagels, A., Migchels, N., Kabadayı, S., Gruber, T., Komarova, Y., Solnet, D. (2013). Understanding generation Y and their use of social media: A review and research agenda. Journal of Service Management, 24, (3), pp. 245-267.
• Browne, M. W., & Cudeck, R. (1993). Alternative Ways of assesing Model Fit. K.A. Bollen and J. S. Long (Eds.) Testing structural Equation Models (pp.136-162). Bevelry Hills, CA: Sage.
• Bogozzi, R. P. &Yi,Y. (1998). On the Evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74-94.
• Büyüköztürk, Ş. (2010). Sosyal Bilimler İçin veri analizi el kitabı. Ankara: Pegem Akademi Yayınları.
• Byrne, B. M. & Campbell, T.L. (1999). Cross-cultural comparisons and the presumption of equivalent measurement and theoretical structure: A look beneath the surface. Journal of Cross-Cultural Psychology, 30, 555-574.
• Fox, J., & Moreland, J. J. (2015). The dark side of social networkin sites: An exploration of the relational and psychological stressors associated with facebook use and affordances. Computers in Human Behavior, 45, 168-176. Hair, J., Black, W., Babin, B., Anderson, R. (2014). Multivariate data analysis, Pearson New International Edition, USA: Pearson.
• Hair, J., Black, W., Babin, B., Anderson, R. (2014). Multivariate Data Analysis, Pearson New International Edition, USA: Pearson.
• Hu, L. & Bentler, P. (1999). Cut off criteria for fitness ındexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: a Multidisciplinary Journal, 6 (19, pp. 1-55.
• Huang, C. (2018). Social network site use and academic achievement: A meta analysis. Computers & Education, 119, 76-83.
• Hutcheson G., & Sofroniou N. (1999). The multivariate social scientist: Introductory statistics using generalized linear models. Sage Publications, Thousand Oaks, CA.
• Jöreskog, K. G., & Sörbom, d. (1993). Lisrel 8: User’s guide. Chicago: Scientific Software.
• Jöreskog, K. G. (1999). How Large Can a Standardized Coefficent Be? Unpublished Technical Report. Son Erişim Tarihi 09.12.2018 http://www.ssicentral.com/lisrel/techdocs/HowLargeCanaStandardized%20Coefficientbe.pdf
• Junco, R. (2012b). Too much face and not enough books: The relationship between multiple indices of Facebook use and academic performance. Computers in Human Behavior 28(1), 187-198.
• Lenhart, A., Purcell, K., Smith, A., Zickuhr, K. (2010). Social Media and Mobile Internet Use Among Teens and Young Adults. Pew Internet and American Life Project, Washington, DC.
• Kirschner, P. A., & Karpinski, A. C. (2010). Facebook and academic performance. Computers in Human Behavior 26(6), 1237-1245.
• Lips, M., Eppel, E., Mcrae, H., Starkey, L., Sylvester, A., Parore, P., & Barlow, L. (2017). Understanding children’s use and experience with digital technologies. Final Research Report. Son Erişim Tarihi: Mayıs, 2019: https://www.victoria.ac.nz/__data/assets/pdf_file/0003/960177/Understanding-children-use-and-experience-of-digital-technologies-2017-v2.pdf
• Liu L.Y., Sidani, J. E., Shensa, A., Radovic, A., Miller, E., Colditz, J.B.,… Primack, B. A. (2016). Association between social media use and depression among U.S. young adults. Depression and Anxiety, 33(4), 323-331.
• Lu, J., Hao, Q., & Jing, M. (2016). Consuming, sharing and creating content: How young students use social media ın and outside school? Computers in Human Behavior, 64, 55-64.
• Lu, J., Luo, J., Liang, L., Jing, M. (2018). Measuring adolescents’ social media behavior outside and ınside of school: Development and validation of two scales. Journal of Educational Computing Research 0(0) 1-23.
• Luckin, R., Clark, W., Graber R., Logan, K., Mee, A., & Oliver, M. (2009). Do Web 2.0 tools really open the door to learning? Practices, perceptioms and profiles of 11-16 year-old students. Learning, Media and Technology, 34(2), 87-104.
• March, H. W., Hau, K.t.,Artelt,C., Baumert, J., & Peschar, J. L. (2006). OECD’s brief self report measure of educational psychology’s most useful affective constructs: Cross-cultural, psychometric comparisons across 25 countries. International Journal of Testing, 6(4), 311-360).
• Quan-Haase, A., & Young, A. L. (2010). Uses and Gratifications of Social Media: A Comparison of Facebook and Instant Messaging. Bulletin of Science, Technology & Society, 30(5), 350-361.
• Perrin, A. (2015). Social Media Usage: 2005-2015. Pew Research Center, Washington, DC. Son erişim tarihi: Mayıs 2019. https://www.pewinternet.org/2015/10/08/social-networking-usage-2005-2015/
• Rideout, V. (2015). The Common Sense Census: Media Use by Tweens and Teens. Common Sense Media. Son erişim tarihi: 20 Mayıs 2019. https://www.commonsensemedia.org/sites/default/files/uploads/research/census_researchreport.pdf
• Schermelleh-Engel, K. & Moosbrugger, H. (2003). Evaluating the fit of structural equation models: Tests of significance and descriptive goodness of fit measures. Methods of Psychological Research Online, 8(2), 23-74.
• Tavşancıl, E., Keser, H. (2002). İnternete yönelik Likert titpi bir tutum ölçeğinin geliştirilmesi. Ankara Üniversitesi Eğitim bilimleri Fakültesi Dergisi, 34(1-2), 45-60.
• Wang, S. K., Hsu H. Y., Campbell T., Coster D. C. & Longhurst, M. (2014). An investigation of middle school science teachers and students use of technology inside and outside of classrooms: Considering whether digital natives are more technology savvy than their teachers. Educational Technology Research and Development, 62(6), 637-662.