Araştırma Makalesi
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YÜKSEKÖĞRETİMDEKİ GENÇ YETİŞKİNLER İÇİN SOSYAL MEDYA YETERLİK ÖLÇEĞİNİN TÜRKÇEYE UYARLANMASI

Yıl 2021, Cilt: 21 Sayı: 4, 1110 - 1126, 15.12.2021
https://doi.org/10.17240/aibuefd.2021..-910030

Öz

Bu araştırmada, yükseköğretimdeki genç yetişkinlerin sosyal medya yeterliklerini değerlendirmeye yönelik Zhu vd. (2020) tarafından geliştirilen “Social Media Competence Scale for College Students”ın (SMCS-CS) Türkçeye uyarlanması amaçlanmıştır. SMCS-CS, 28 madde ve 4 faktörden (teknik kullanılabilirlik, içerik yorumlama, içerik üretme, beklentisel düşünme) oluşan, 5’li Likert tipte geçerli ve güvenilir bir ölçektir. SMCS-CS’nin orijinal formu ve Türkçeye uyarlanan formu her iki dile hâkim bir çalışma grubuna uygulanmış ve iki form arasında yüksek düzeyde istatistiksel olarak anlamlı bir ilişki olduğu belirlenmiştir (r=,895; p<,001). Dil eşdeğerliği sağlanan uyarlanan form, toplam 339 lisans öğrencisine uygulanmıştır. Ancak, 11 katılımcıdan elde edilen veriler, uç değer analiz sonuçlarına göre analizden çıkarılmıştır. Toplam 328 katılımcıdan oluşan veri seti üzerinde doğrulayıcı faktör analizi (DFA) gerçekleştirilmiştir. DFA sonuçlarına göre maddelerin, ilgili faktörler altında istatistiksel olarak anlamlı yük değerlerine sahip olduğu ve model uyum indekslerinin (𝓧2=916,05; sd=341; 𝓧2/sd=2,686; RMSEA=0,072; GFI=0,827; CFI=0,939; SRMR=0,083; NFI=0,906; IFI=0,939; NNFI=0,932) kabul edilebilir değer aralıklarında olduğu belirlenmiştir. Buna ek olarak, yakınsama ve ayırt edici geçerlilik kriterleri ile heterotrait-monotrait (HTMT) korelasyon oranı analiz sonuçları incelenmiştir. Güvenirlik değerlendirmesi için Cronbach alfa (α) katsayıları (0,73 ≤ α ≤ 0,85) incelenmiştir. Sonuçta, orijinal ölçek yapısı uyarlanan form için doğrulanan, geçerli ve güvenilir bir ölçme aracı elde edilmiştir. Ayrıca ileri araştırmalar için öneriler sunulmuş ve araştırmanın sınırlılıkları özetlenmiştir.

Destekleyen Kurum

Bulunmamaktadır.

Proje Numarası

Bulunmamaktadır.

Kaynakça

  • Alber, J. M., Bernhardt, J. M., Stellefson, M., Weiler, R. M., Anderson-Lewis, C., Miller, M. D., & MacInnes, J. (2014). Designing and testing an inventory for measuring social media competency of certified health education specialists. Journal of Medical Internet Research, 17(9), 221-221. https://doi.org/10.2196/jmir.4943
  • Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74-94. https://doi.org/10.1007/BF02723327
  • Barrett, P. (2007). Structural equation modelling: Adjudging model fit. Personality and Individual Differences, 42(5), 815-824. https://doi.org/10.1016/j.paid.2006.09.018
  • Barut Tugtekin, E., & Dursun, Ö. Ö. (2020). Examining virtual identity profiles of social network users with respect to certain variables. Pegem Journal of Education and Instruction, 10(2), 427-464. https://doi.org/10.14527/pegegog.2020.015
  • Benson, V., Morgan, S., & Filippaios, F. (2014). Social career management: Social media and employability skills gap. Computers in Human Behavior, 30, 519-525. https://doi.org/10.1016/j.chb.2013.06.015
  • Boyd, D. M., & Ellison, N. B. (2007). Social network sites: Definition, history, and scholarship. Journal of Computer‐Mediated Communication, 13(1), 210-230. https://doi.org/10.1111/j.1083-6101.2007.00393.x
  • Brown, T. A. (2006). Confirmatory factor analysis for applied research. Guilford Publications.
  • Byrne, B. M. (2006). Structural equation modeling with EQS: Basic concepts, applications, and programming (2nd ed.). Routledge.
  • Cheng, S. (2011). Comparisons of competing models between attitudinal loyalty and behavioral loyalty. International Journal of Business and Social Science, 2(10), 149-166.
  • Clark, L. A., & Watson, D. (1995). Constructing validity: Basic issues in objective scale development. Psychological Assessment, 7(3), 309-319. https://doi.org/10.1037/14805-012
  • Çokluk, Ö., Şekercioğlu, G. & Büyüköztürk, Ş. (2012). Sosyal bilimler için çok değişkenli istatistik: SPSS ve LISREL uygulamaları (2. baskı). Pegem Akademi.
  • Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 18(3), 382-388. https://doi.org/10.1177/002224378101800313
  • Gillin, P. (2009). Secrets of social media marketing: How to use online conversations and customer communities to turbo-charge your business! Quill Driver Books.
  • Gold, A. H., Malhotra, A., & Segars, A. H. (2001). Knowledge management: An organizational capabilities perspective. Journal of Management Information Systems, 18(1), 185-214. https://doi.org/10.1080/07421222.2001.11045669
  • Hair, J., Black, W., Babin, B., & Anderson, R. (2010). Multivariate data analysis (7th ed.). Prentice-Hall.
  • Hallam, C., & Zanella, G. (2017). Online self-disclosure: The privacy paradox explained as a temporally discounted balance between concerns and rewards. Computers in Human Behavior, 68, 217-227. https://doi.org/10.1016/j.chb.2016.11.033
  • Heggestad, E. D., Scheaf, D. J., Banks, G. C., Monroe Hausfeld, M., Tonidandel, S., & Williams, E. B. (2019). Scale adaptation in organizational science research: A review and best-practice recommendations. Journal of Management, 45(6), 2596-2627. https://doi.org/10.1177/0149206319850280
  • Hennig-Thurau, T., Malthouse, E. C., Friege, C., Gensler, S., Lobschat, L., Rangaswamy, A., & Skiera, B. (2010). The impact of new media on customer relationships. Journal of Service Research, 26(3), 311-330. https://doi.org/10.1177/1094670510375460
  • Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115-135. https://doi.org/10.1007/s11747-014-0403-8
  • Hooper, D., Coughlan, J., & Mullen, M. R. (2008). Structural equation modelling: Guidelines for determining model fit. The Electronic Journal of Business Research Methods, 6(1), 53-60. http://doi.org/10.21427/D7CF7R
  • Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indices in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1-55. https://doi.org/10.1080/10705519909540118
  • Kaas, R. A., & Tinsley, H. E. A. (1979). Factor analysis. Journal of Leisure Research, 11, 120-138. https://doi.org/10.1080/00222216.1979.11969385
  • Kline, R. B. (2011). Principles and practice of structural equation modeling (3rd ed.). The Guilford Press.
  • Koc, M., & Barut, E. (2016). Development and validation of New Media Literacy Scale (NMLS) for university students. Computers in Human Behavior, 63, 834-843. https://doi.org/10.1016/j.chb.2016.06.035
  • Lee, A. R., Son, S. M., & Kim, K. K. (2016). Information and communication technology overload and social networking service fatigue: A stress perspective. Computers in Human Behavior, 55, 51-61. https://doi.org/10.1016/j.chb.2015.08.011
  • Lee, C. S., & Ma, L. (2012). News sharing in social media: The effect of gratifications and prior experience. Computers in Human Behavior, 28(2), 331-339. https://doi.org/10.1016/j.chb.2011.10.002
  • Mahajan, P. (2009). Use of social networking in a linguistically and culturally rich India. The International Information & Library Review, 41(3), 129-136. https://doi.org/10.1016/j.iilr.2009.07.004
  • Malhotra N. K., & Dash, S. (2011). Marketing research an applied orientation. Pearson Publishing.
  • Nancy, B., & Grove, S. K. (2001). The practice of nursing research: Conduct, critique, and utilization (4th ed.). W.B. Saunders Company.
  • Pallant, J. (2007). SPSS survival manual: A step by step guide to data analysis using SPSS for Windows (15th ed.). Open University Press, McGraw Hill.
  • Persico, D., Chiorri, C., Ferraris, M., & Pozzi, F. (2016). Effects of social networking on learning: The opinions of Italian university students. In T. Issa, P. Isaias & P. Kommers (Eds.), Social networking and education (pp. 145-163). Springer International Publishing. https://doi.org/10.1007/978-3-319-17716-8_10
  • Schermelleh-Engel, K., Moosbrugger, H., & Müller, 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.
  • Schumacker, R. E., & Lomax, R. G. (1996). A beginner’s guide to structural equation modeling. LEA.
  • Seçer, I. (2015). Psikolojik test geliştirme ve uyarlama süreci: SPSS ve LISREL uygulamaları. Anı Yayıncılık.
  • Sousa, V. D., & Rojjanasrirat, W. (2011). Translation, adaptation and validation of instruments or scales for use in cross‐cultural health care research: A clear and user‐friendly guideline. Journal of Evaluation in Clinical Practice, 17(2), 268-274. https://doi.org/10.1111/j.1365-2753.2010.01434.x
  • Sümer, N. (2000). Yapısal eşitlik modelleri. Türk Psikoloji Yazıları, 3(6), 49-74.
  • Tanaka, J. S., Panter, A. T., Winborne, W. C., & Huba, G. J. (1990). Theory testing in personality and social psychology with structural equation models. In C. Hendrick & M. S. Clark (Eds.), Research methods in personality and social psychology (pp. 217-243). Sage.
  • Teo, T. S. H., Srivastava, S. C., & Jiang, L. (2008). Trust and electronic government success: An empirical study. Journal of Management Information Systems, 25(3), 99-132. https://doi.org/10.2753/MIS0742-1222250303
  • Thompson, B. (2004). Exploratory and confirmatory factor analysis: Understanding concepts and applications. American Psychological Association.
  • Tugtekin, E. B., & Koc, M. (2020). Understanding the relationship between new media literacy, communication skills, and democratic tendency: Model development and testing. New Media & Society, 22(10), 1922-1941. https://doi.org/10.1177/1461444819887705
  • Tugtekin, U., Barut Tugtekin, E., Kurt, A. A., & Demir, K. (2020). Associations between fear of missing out, problematic smartphone use, and social networking services fatigue among young adults. Social Media + Society, 6(4), 1-17. https://doi.org/10.1177/2056305120963760
  • We Are Social (2020). Digital in 2020. https://wearesocial.com/digital-2020
  • We Are Social (2021). Digital 2021: Global overview report. https://wearesocial.com/digital-2021
  • Worthington, R. L., & Whittaker, T. A. (2006). Scale development research: A content analysis and recommendations for best practices. The Counseling Psychologist, 34(6), 806-838. https://doi.org/10.1177/0011000006288127
  • Zhong, B., Hardin, M., & Sun, T. (2011). Less effortful thinking leads to more social networking? The associations between the use of social network sites and personality traits. Computers in Human Behavior, 27(3), 1265-1271. https://doi.org/10.1016/j.chb.2011.01.008
  • Zhu, S., Hao Yang, H., Xu, S., & MacLeod, J. (2020). Understanding social media competence in higher education: Development and validation of an instrument. Journal of Educational Computing Research, 57(8), 1935-1955. https://doi.org/10.1177/0735633118820631

ADAPTATION OF THE SOCIAL MEDIA COMPETENCE SCALE FOR COLLEGE STUDENTS IN HIGHER EDUCATION TO TURKISH

Yıl 2021, Cilt: 21 Sayı: 4, 1110 - 1126, 15.12.2021
https://doi.org/10.17240/aibuefd.2021..-910030

Öz

This study aims to adapt the Social Media Competence Scale for College Students (SMCS-CS) developed by Zhu et al. (2020) to Turkish. The scale is designed to assess the social media competencies of young adults in higher education. The SMCS-CS is a valid and reliable 5-point Likert type scale consisting of 28-items and 4-factors (technical usability, content interpretation, content generation, and anticipatory reflection). The original form of the SMCS-CS and its Turkish version were administered to a bilingual study group, and a high-level statistically significant correlation was found between the original and the adapted version (r=.895; p<.001). The Turkish version was administered to 339 young adults. 11 participants were excluded from the analysis based on the outliers. Confirmatory factor analysis (CFA) was conducted with the data from 328 participants. The CFA revealed that each item had a statistically significant load under related factors and the model goodness of fit indices (𝓧2=916.05; df=341; 𝓧2/df=2.686; RMSEA=0.072; GFI=0.827; CFI=0.939; SRMR=0.083; NFI=0.906; IFI=0.939; NNFI=0.932) were acceptable. In addition, the divergent and convergent criteria and heterotrait-monotrait (HTMT) correlation ratio analysis were conducted. Cronbach’s alpha (α) results for reliability were (0.73 ≤ α ≤ 0.85). The analyses showed that the Turkish version was valid and reliable. The limitations of the study were stated and suggestions for further research were made.

Proje Numarası

Bulunmamaktadır.

Kaynakça

  • Alber, J. M., Bernhardt, J. M., Stellefson, M., Weiler, R. M., Anderson-Lewis, C., Miller, M. D., & MacInnes, J. (2014). Designing and testing an inventory for measuring social media competency of certified health education specialists. Journal of Medical Internet Research, 17(9), 221-221. https://doi.org/10.2196/jmir.4943
  • Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74-94. https://doi.org/10.1007/BF02723327
  • Barrett, P. (2007). Structural equation modelling: Adjudging model fit. Personality and Individual Differences, 42(5), 815-824. https://doi.org/10.1016/j.paid.2006.09.018
  • Barut Tugtekin, E., & Dursun, Ö. Ö. (2020). Examining virtual identity profiles of social network users with respect to certain variables. Pegem Journal of Education and Instruction, 10(2), 427-464. https://doi.org/10.14527/pegegog.2020.015
  • Benson, V., Morgan, S., & Filippaios, F. (2014). Social career management: Social media and employability skills gap. Computers in Human Behavior, 30, 519-525. https://doi.org/10.1016/j.chb.2013.06.015
  • Boyd, D. M., & Ellison, N. B. (2007). Social network sites: Definition, history, and scholarship. Journal of Computer‐Mediated Communication, 13(1), 210-230. https://doi.org/10.1111/j.1083-6101.2007.00393.x
  • Brown, T. A. (2006). Confirmatory factor analysis for applied research. Guilford Publications.
  • Byrne, B. M. (2006). Structural equation modeling with EQS: Basic concepts, applications, and programming (2nd ed.). Routledge.
  • Cheng, S. (2011). Comparisons of competing models between attitudinal loyalty and behavioral loyalty. International Journal of Business and Social Science, 2(10), 149-166.
  • Clark, L. A., & Watson, D. (1995). Constructing validity: Basic issues in objective scale development. Psychological Assessment, 7(3), 309-319. https://doi.org/10.1037/14805-012
  • Çokluk, Ö., Şekercioğlu, G. & Büyüköztürk, Ş. (2012). Sosyal bilimler için çok değişkenli istatistik: SPSS ve LISREL uygulamaları (2. baskı). Pegem Akademi.
  • Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 18(3), 382-388. https://doi.org/10.1177/002224378101800313
  • Gillin, P. (2009). Secrets of social media marketing: How to use online conversations and customer communities to turbo-charge your business! Quill Driver Books.
  • Gold, A. H., Malhotra, A., & Segars, A. H. (2001). Knowledge management: An organizational capabilities perspective. Journal of Management Information Systems, 18(1), 185-214. https://doi.org/10.1080/07421222.2001.11045669
  • Hair, J., Black, W., Babin, B., & Anderson, R. (2010). Multivariate data analysis (7th ed.). Prentice-Hall.
  • Hallam, C., & Zanella, G. (2017). Online self-disclosure: The privacy paradox explained as a temporally discounted balance between concerns and rewards. Computers in Human Behavior, 68, 217-227. https://doi.org/10.1016/j.chb.2016.11.033
  • Heggestad, E. D., Scheaf, D. J., Banks, G. C., Monroe Hausfeld, M., Tonidandel, S., & Williams, E. B. (2019). Scale adaptation in organizational science research: A review and best-practice recommendations. Journal of Management, 45(6), 2596-2627. https://doi.org/10.1177/0149206319850280
  • Hennig-Thurau, T., Malthouse, E. C., Friege, C., Gensler, S., Lobschat, L., Rangaswamy, A., & Skiera, B. (2010). The impact of new media on customer relationships. Journal of Service Research, 26(3), 311-330. https://doi.org/10.1177/1094670510375460
  • Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115-135. https://doi.org/10.1007/s11747-014-0403-8
  • Hooper, D., Coughlan, J., & Mullen, M. R. (2008). Structural equation modelling: Guidelines for determining model fit. The Electronic Journal of Business Research Methods, 6(1), 53-60. http://doi.org/10.21427/D7CF7R
  • Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indices in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1-55. https://doi.org/10.1080/10705519909540118
  • Kaas, R. A., & Tinsley, H. E. A. (1979). Factor analysis. Journal of Leisure Research, 11, 120-138. https://doi.org/10.1080/00222216.1979.11969385
  • Kline, R. B. (2011). Principles and practice of structural equation modeling (3rd ed.). The Guilford Press.
  • Koc, M., & Barut, E. (2016). Development and validation of New Media Literacy Scale (NMLS) for university students. Computers in Human Behavior, 63, 834-843. https://doi.org/10.1016/j.chb.2016.06.035
  • Lee, A. R., Son, S. M., & Kim, K. K. (2016). Information and communication technology overload and social networking service fatigue: A stress perspective. Computers in Human Behavior, 55, 51-61. https://doi.org/10.1016/j.chb.2015.08.011
  • Lee, C. S., & Ma, L. (2012). News sharing in social media: The effect of gratifications and prior experience. Computers in Human Behavior, 28(2), 331-339. https://doi.org/10.1016/j.chb.2011.10.002
  • Mahajan, P. (2009). Use of social networking in a linguistically and culturally rich India. The International Information & Library Review, 41(3), 129-136. https://doi.org/10.1016/j.iilr.2009.07.004
  • Malhotra N. K., & Dash, S. (2011). Marketing research an applied orientation. Pearson Publishing.
  • Nancy, B., & Grove, S. K. (2001). The practice of nursing research: Conduct, critique, and utilization (4th ed.). W.B. Saunders Company.
  • Pallant, J. (2007). SPSS survival manual: A step by step guide to data analysis using SPSS for Windows (15th ed.). Open University Press, McGraw Hill.
  • Persico, D., Chiorri, C., Ferraris, M., & Pozzi, F. (2016). Effects of social networking on learning: The opinions of Italian university students. In T. Issa, P. Isaias & P. Kommers (Eds.), Social networking and education (pp. 145-163). Springer International Publishing. https://doi.org/10.1007/978-3-319-17716-8_10
  • Schermelleh-Engel, K., Moosbrugger, H., & Müller, 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.
  • Schumacker, R. E., & Lomax, R. G. (1996). A beginner’s guide to structural equation modeling. LEA.
  • Seçer, I. (2015). Psikolojik test geliştirme ve uyarlama süreci: SPSS ve LISREL uygulamaları. Anı Yayıncılık.
  • Sousa, V. D., & Rojjanasrirat, W. (2011). Translation, adaptation and validation of instruments or scales for use in cross‐cultural health care research: A clear and user‐friendly guideline. Journal of Evaluation in Clinical Practice, 17(2), 268-274. https://doi.org/10.1111/j.1365-2753.2010.01434.x
  • Sümer, N. (2000). Yapısal eşitlik modelleri. Türk Psikoloji Yazıları, 3(6), 49-74.
  • Tanaka, J. S., Panter, A. T., Winborne, W. C., & Huba, G. J. (1990). Theory testing in personality and social psychology with structural equation models. In C. Hendrick & M. S. Clark (Eds.), Research methods in personality and social psychology (pp. 217-243). Sage.
  • Teo, T. S. H., Srivastava, S. C., & Jiang, L. (2008). Trust and electronic government success: An empirical study. Journal of Management Information Systems, 25(3), 99-132. https://doi.org/10.2753/MIS0742-1222250303
  • Thompson, B. (2004). Exploratory and confirmatory factor analysis: Understanding concepts and applications. American Psychological Association.
  • Tugtekin, E. B., & Koc, M. (2020). Understanding the relationship between new media literacy, communication skills, and democratic tendency: Model development and testing. New Media & Society, 22(10), 1922-1941. https://doi.org/10.1177/1461444819887705
  • Tugtekin, U., Barut Tugtekin, E., Kurt, A. A., & Demir, K. (2020). Associations between fear of missing out, problematic smartphone use, and social networking services fatigue among young adults. Social Media + Society, 6(4), 1-17. https://doi.org/10.1177/2056305120963760
  • We Are Social (2020). Digital in 2020. https://wearesocial.com/digital-2020
  • We Are Social (2021). Digital 2021: Global overview report. https://wearesocial.com/digital-2021
  • Worthington, R. L., & Whittaker, T. A. (2006). Scale development research: A content analysis and recommendations for best practices. The Counseling Psychologist, 34(6), 806-838. https://doi.org/10.1177/0011000006288127
  • Zhong, B., Hardin, M., & Sun, T. (2011). Less effortful thinking leads to more social networking? The associations between the use of social network sites and personality traits. Computers in Human Behavior, 27(3), 1265-1271. https://doi.org/10.1016/j.chb.2011.01.008
  • Zhu, S., Hao Yang, H., Xu, S., & MacLeod, J. (2020). Understanding social media competence in higher education: Development and validation of an instrument. Journal of Educational Computing Research, 57(8), 1935-1955. https://doi.org/10.1177/0735633118820631
Toplam 46 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm Makaleler
Yazarlar

Ufuk Tuğtekin 0000-0003-0129-3477

Proje Numarası Bulunmamaktadır.
Yayımlanma Tarihi 15 Aralık 2021
Gönderilme Tarihi 5 Nisan 2021
Yayımlandığı Sayı Yıl 2021 Cilt: 21 Sayı: 4

Kaynak Göster

APA Tuğtekin, U. (2021). YÜKSEKÖĞRETİMDEKİ GENÇ YETİŞKİNLER İÇİN SOSYAL MEDYA YETERLİK ÖLÇEĞİNİN TÜRKÇEYE UYARLANMASI. Abant İzzet Baysal Üniversitesi Eğitim Fakültesi Dergisi, 21(4), 1110-1126. https://doi.org/10.17240/aibuefd.2021..-910030