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Journals / Eğitim Teknolojisi Kuram ve Uygulama / 2025 / Cilt: 15 Sayı: 2

INTERNET SKILLS: A SCALE ADAPTATION STUDY

İNTERNET BECERİLERİ: BİR ÖLÇEK UYARLAMA ÇALIŞMASI

Tuba Kopuz(Milli Eğitim Bakanlığı)0000-0001-6418-4580
Ayşe Aktaş(RECEP TAYYİP ERDOĞAN ÜNİVERSİTESİ)0000-0002-8838-9561
İlknur Reisoğlu(RECEP TAYYİP ERDOĞAN ÜNİVERSİTESİ)0000-0002-6485-254X
Yiğit Emrah Turgut(RECEP TAYYİP ERDOĞAN ÜNİVERSİTESİ)0000-0002-6306-4090
Alper Aslan(MUNZUR ÜNİVERSİTESİ)0000-0003-2970-6114
Pages
189–209
Publication Date
2025-07-19
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Based on the findings, the 20-item version of the scale was confirmed to be valid and reliable for use within the Turkish context.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This study aims to adapt the Internet Skills Scale, originally developed by Van Deursen et al. in 2016 to the Turkish cultural context and to examine its psychometric properties.
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Key Findings & Data:The original scale comprises 35 items across five factors.
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Conclusion & Impact:Based on the findings, the 20-item version of the scale was confirmed to be valid and reliable for use within the Turkish context.
🔬Design:Modeling & Simulation
📍Scope:2016 Verileri
⚙️Variables:internet becerileri · ölçek uygulama · Türk kültürü

Abstract

This study aims to adapt the Internet Skills Scale, originally developed by Van Deursen et al. in 2016 to the Turkish cultural context and to examine its psychometric properties. The original scale comprises 35 items across five factors. To explore the factor structure in the Turkish context, exploratory factor analysis was conducted with data from 307 internet users. The original 5-factor structure was reduced to four factors due to the analysis. It was determined that all factors explained 68.4% of the variance. Confirmatory factor analysis was conducted with 300 participants to test the suitability of the resulting 4-factor structure for Turkish culture. Confirmatory factor analysis results supported the 4-factor structure, and the fit indices indicated acceptable, good, and excellent model fit. Convergent and discriminant validity analyses were also conducted to assess construct validity, and the results were found to be within acceptable ranges. Based on the findings, the 20-item version of the scale was confirmed to be valid and reliable for use within the Turkish context.

Özet

Bu çalışmanın amacı Van Deursen vd. tarafından 2016 yılında geliştirilen İnternet Becerileri Ölçeğini Türk kültürüne uyarlamak ve ilgili ölçeğin psikometrik özelliklerini sınamaktır. Orijinal ölçek 35 madde ve beş faktörlü bir yapıya sahiptir. Ölçeğin faktör yapısını Türkiye örnekleminde incelemek amacıyla İnternet kullanıcısı olan 307 kişi ile açımlayıcı faktör analizi gerçekleştirilmiştir. Gerçekleştirilen analiz sonucunda orijinal ölçekte beş faktörden oluşan yapının dört faktör altında toplandığı görülmüştür. Tüm faktörlerin varyansın %68.4’ünü açıkladığı belirlenmiştir. Ortaya çıkan dört faktörlü yapının Türk kültürüne uygunluğunu test etmek amacıyla 300 kişi ile doğrulayıcı faktör analizi gerçekleştirilmiştir. Analiz sonucunda dört faktörlü yapının korunduğu görülmüştür. DFA sonucunda elde edilen uyum indekslerinin kabul edilebilir, iyi ve mükemmel uyum aralığında oldukları belirlenmiştir. Yapı geçerliliğini belirlemek için birleşim geçerliği ve ayrışım geçerliği analiz sonuçlarının da uygun aralıklarda olduğu tespit edilmiştir. Elde edilen bulgular sonucunda 20 maddeden oluşan formun Türk kültürüne uygunluğu kanıtlanmış ve ölçeğin Türkçe formunun geçerliği ve güvenirliği sağlanmıştır.

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Cite This Article

Kopuz, T., Aktaş, A., Reisoğlu, İ., Turgut, Y. E., Aslan, A. (2025). INTERNET SKILLS: A SCALE ADAPTATION STUDY. Eğitim Teknolojisi Kuram ve Uygulama, Cilt: 15 Sayı: 2, 189–209. https://doi.org/10.17943/etku.1620507

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References (62)

  1. Abbate, J. (2000). Inventing the internet. MIT Press.
  2. Abbate, J. (2017). What and where is the Internet? (Re) defining Internet histories. Internet Histories, 1(1-2), 8-14. https://doi.org/10.1080/24701475.2017.1305836
  3. Ala-Mutka, K. (2011). Mapping digital competence: Towards a conceptual understanding. Publications Office of the European Union.
  4. Bauer, A. T., & Ahooei, E. M. (2018). Rearticulating internet literacy. Journal of Cyberspace Studies, 2(1), 29-53. https://doi.org/10.22059/jcss.2018.245833.1012
  5. Bawden, D. (2001). Information and digital literacies: a review of concepts. Journal of Documentation, 57(2), 218-259. http://doi.org/10.1108/EUM0000000007083
  6. Brown, T. A. (2006). Confirmatory factor analysis for applied research. Guilford Publication.
  7. Brown, T. A. (2015). Confirmatory factor analysis for applied research. Guilford Publication.
  8. Campbell, D. T., & Fiske, D. W. (1959). Convergent and discriminant validation by the multitrait-multimethod matrix. Psychological Bulletin, 56(2), 8-105. http://doi: 10.1037/h0046016
  9. Castro, M. A. D., Baltar, V. T., Selem, S. S. A. D. C., Marchioni, D. M. L., & Fisberg, R. M. (2015). Empirically derived dietary patterns: interpretability and construct validity according to different factor rotation methods.
  10. Cadernos de Saude Publica, 31, 298-310. https://doi.org/10.1590/0102-311X00070814
  11. Comrey, A. L. (1988). Factor-analytic methods of scale development in personality and clinical psychology. Journal of Consulting and Clinical Psychology, 56(5), 754–761. https://doi.org/10.1037/0022-006X.56.5.754
  12. Cooper, C. (2019). Psychological testing: Theory and practice. Routledge.
  13. Creswell, J. W. (2017). Research design: Qualitative, quantitative and mixed method approaches. Eğiten Book.
  14. Çokluk, Ö., Şekercioğlu, G. & Büyüköztürk, Ş. (2016). Multivariate statistics for social sciences: SPSS and LISREL applications. Pegem Academy.
  15. Ersöz, B. (2020). New generation web paradigm: Web 4.0. Journal of Computer Science and Technologies, 1(2), 58-65.
  16. Fabrigar, L. R., & Wegener, D. T. (2012). Exploratory factor analysis. Oxford University Press.
  17. Farrell, A. M. (2010). Insufficient discriminant validity: A comment on Bove, Pervan, Beatty, and Shiu (2009). Journal of Business Research, 63(3), 324-327. https://doi.org/10.1016/j.jbusres.2009.05.003
  18. Field, A. (2024). Discovering statistics using IBM SPSS statistics. SAGE Publications.
  19. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50. https://doi.org/10.1177/002224378101800104
  20. Global Kids Online. (2025a, April 28). Quantitative tools. http://globalkidsonline.net/tools/ survey/
  21. Global Kids Online. (2025b, April 28). Research results. http://globalkidsonline.net/results/
  22. Gorsuch, R. L. (1974). Factor analysis. Toronto: W. B. Saunders.
  23. Grošelj, D., van Deursen, A. J. M., Dolničar, V., Burnik, T., & Petrovčič, A. (2021). Measuring internet skills in a general population: A large-scale validation of the short Internet Skills Scale in Slovenia. The Information Society, 37(2), 63-81. https://doi.org/10.1080/01972243.2020.1862377
  24. Güneş, F. & Deveci, T. (2022). Adult education and lifelong learning. Pegem Academy.
  25. Gürbüz, S. (2019). Structural equation modeling with Amos. Seçkin. Haigh, T., Russell, A. L., & Dutton, W. H. (2015). Histories of the Internet: Introducing a special issue of information & culture. Information & Culture, 50(2), 143-159.
  26. Hargittai, E., & Hsieh, Y. P. (2012). Succinct survey measures of web-use skills. Social Science Computer Review, 30(1), 95-107. https://doi.org/10.1177/08944393103971
  27. Helsper, E. (2008). Digital inclusion: an analysis of social disadvantage and the information society. Department for Communities and Local Government.
  28. Helsper, E. J., & Eynon, R. (2013). Distinct skill pathways to digital engagement. European Journal of Communication, 28(6), 696-713. https://doi.org/10.1177/0267323113499
  29. Hair, J. F., Jr., Black, W. C., Babin, B. J. & Anderson, R. E. (2010). Multivariate data analysis (7th ed.). Prentice Hall.
  30. Hair, J.F., Hult, G.T.M., Ringle, C.M. & Sarstedt, M. (2014). A primer on partial least squares structural equation modeling (PLS-SEM). SAGE Publications.
  31. Hair, J. F., Babin, B. J., Anderson, R. E., & Black, W. C. (2019). Multivariate data analysis. Cengage Learning.
  32. Hooper, D., Coughlan, J., & Mullen, M. R. (2008). Structural equation modelling: Guidelines for determining model fit. Electronic Journal of Business Research Methods, 6(1), 52–60.
  33. Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling. A Multidisciplinary Journal, 6(1), 1–55.
  34. Johansson, S., Gulliksen, J., & Gustavsson, C. (2021). Disability digital divide: the use of the internet, smartphones, computers and tablets among people with disabilities in Sweden. Universal Access in the Information Society, 20(1), 105-120. https://doi.org/10.1007/s10209-020-00714-x
  35. Johnson, B., & Christensen, L. B. (2014). Educational research: quantitative, qualitative, and mixed approaches (Fifth edition). SAGE.
  36. Kaiser, H. F. (1970). A second generation little jiffy. Psychometrika, 35(4), 401–415. https://doi.org/10.1007/BF02291817
  37. Kline, R. B. (2011). Principles and practice of structural equation modeling. Guilford Publications.
  38. Koeske, G. F. (1994). Some recommendations for improving measurement validation in social work research. Journal of Social Service Research, 18(3-4), 43-72.
  39. Mota, F. P. B., & Cilento, I. (2020). Competence for internet use: Integrating knowledge, skills, and attitudes. Computers and Education Open, 1, 100015. https://doi.org/10.1016/j.caeo.2020.100015
  40. Orçan, F. (2018). Exploratory and confirmatory factor analysis: Which one to use first? Journal of Measurement and Evaluation in Education and Psychology, 9(4), 414-421. https://doi.org/10.21031/epod.394323
  41. Potosky, D. (2007). The Internet knowledge (iKnow) measure. Computers in Human Behavior, 23(6), 2760-2777. https://doi.org/10.1016/j.chb.2006.05.003
  42. Rouquette, A., & Falissard, B. (2011). Sample size requirements for the internal validation of psychiatric scales. International journal of methods in psychiatric research, 20(4), 235-249. https://doi.org/10.1002/mpr.352
  43. Scheerder, A., Van Deursen, A., & Van Dijk, J. (2017). Determinants of Internet skills, uses and outcomes. A systematic review of the second-and third-level digital divide. Telematics and Informatics, 34(8), 1607-1624. https://doi.org/10.1016/j.tele.2017.07.007
  44. 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.
  45. Schumacker, R. E., & Lomax, R. G. (2010). A beginner's guide to structural equation modeling (3th ed.). Routledge.
  46. Soroya, S. H., Ahmad, A.S., Ahmad, S., & Soroya, M. S. (2021). Mapping internet literacy skills of digital natives: A developing country perspective. PLoS One 16(4), e0249495. https://doi.org/10.1371/journal.pone.0249495
  47. STATISTA, (2023a, 16 November). Internet users worldwide 2013-2028. https://www.statista.com /forecasts/1146844/internet-users-in-the-world
  48. STATISTA, (2023b, 16 November). Digital Banks: market data & analysis. https://www.statista.com/study/137396/digital-banks-report/
  49. Steiger, J. H. (2007). Understanding the limitations of global fit assessment in structural equation modeling. Personality and Individual Differences, 42(5), 893–898. https://doi.org/10.1016/j.paid.2006.09.017
  50. Streiner, D. L. (1994). Figuring out factors: The use and misuse of factor analysis. Canadian Journal of Psychiatry, 39(3), 135–140. https://doi.org/10.1177/070674379403900303
  51. Tabachnick, B. G., & Fidell, L. S. (2001). Using multivariate statistics (4th ed.). Allyn & Bacon.
  52. Tabachnick, B. G., & Fidell, L. S. (2020). Using multivariate statistics (M. Baloğlu, Trans.). Nobel Publishing.
  53. Turkish Statistical Institute (TSI). (2023, December 15). Survey on information and communication technology (ICT) usage in households and by individuals, 2023. https://data.tuik.gov.tr/Bulten/Index?p=Hanehalki-Bilisim-Teknolojileri-(BT)-Kullanim-Arastirmasi-2023-49407
  54. Van Deursen, A. J., & Van Dijk, J. A. (2009a). Using the Internet: Skill related problems in users’ online behavior. Interacting with Computers, 21(5-6), 393-402. https://doi.org/10.1016/j.intcom.2009.06.005
  55. Van Deursen, A. J., & Van Dijk, J. A. (2009b). Improving digital skills for the use of online public information and services. Government Information Quarterly, 26(2), 333-340. https://doi.org/10.1016/j.giq.2008.11.002
  56. Van Deursen, A. J., & Van Dijk, J. A. (2010). Measuring internet skills. International Journal of Human-Computer Interaction, 26(10), 891-916. https://doi.org/10.1080/10447318.2010.496338
  57. Van Deursen, A., & Van Dijk, J. (2011). Internet skills and the digital divide. New Media & Society, 13(6), 893-911. https://doi.org/10.1177/1461444810386774
  58. Van Deursen, A. J., Helsper, E. J., & Eynon, R. (2016). Development and validation of the Internet Skills Scale (ISS). Information, Communication & Society, 19(6), 804-823. https://doi.org/10.1080/1369118X.2015.1078834
  59. Van Dijk, J. A., & Van Deursen, A. J. (2014). Digital skills: Unlocking the information society. Springer.
  60. Van Laar, E., Van Deursen, A. J., Van Dijk, J. A., & De Haan, J. (2020). Determinants of 21st-century skills and 21st-century digital skills for workers: A systematic literature review. Sage Open, 10(1), 1-14. https://doi.org/10.1177/2158244019900176
  61. We Are Social. (2023, November 16). Digital around the world in 2023. https://wearesocial.com/uk/blog/2023/01/digital-2023/
  62. Yasmine, D. I., Colombijn, F., Deursen, A. J. V., & van Ingen, E. (2025). Internet skills, digital engagement, and outcomes among urban youth in Jakarta, Indonesia: Incorporating a Global South context in measuring digital inequality. Information, Communication & Society, 1-21. https://doi.org/10.1080/1369118X.2025.2479778