PEN Academic Publishing   |  ISSN: 1554-5210

Original article | International Journal of Progressive Education 2019, Vol. 15(2) 44-64

Analysis of Scientific Studies on Item Response Theory by Bibliometric Analysis Method

Gökhan Aksu & Cem Oktay Güzeller

pp. 44 - 64   |  DOI: https://doi.org/10.29329/ijpe.2019.189.4   |  Manu. Number: MANU-1812-22-0002

Published online: April 06, 2019  |   Number of Views: 25  |  Number of Download: 116


Abstract

The purpose of this study is to analyze the studies, which include Item Response Theory among the keywords, available in the Web of Science database between 1980-2018 through bibliometric analysis method. A total of 1,367 academic works has been analyzed. The authors, journals and countries having the highest number of studies in the field and their interrelations on the network in terms of collaboration have been determined through common citation analysis performed using Citespace II software. In addition, a word analysis was also conducted to determine most frequently used concepts in the field. As a result of the study it was found that the authors that have made the biggest contribution to the field are De Ayala, Embretson, Reckase, Reise and Chalmers; in addition, the countries making the biggest contribution are respectively US, Netherland, Canada, Spain and China. The number of citations that US got, which is the country that received the highest number of citations with 687 citations, is 7 times higher than Netherland, which is the second most cited country. Moreover, it was found that the journals that were mostly cited are respectively Psychometrika, Appl Psych Measurement, Item Response Theory, J Edu Measurement and Educ Psychol Measurement. As a result of the word analysis based on most repeated words, which was performed for the purpose of determining most popular subjects on the field, it was found that most frequently used words are item response theory, classical test theory, model, validation, reliability, validity and Rasch model

Keywords: Item Response Theory, Citespace II, Bibliometric Analysis, Cite, Analysis


How to Cite this Article?

APA 6th edition
Aksu, G. & Guzeller, C.O. (2019). Analysis of Scientific Studies on Item Response Theory by Bibliometric Analysis Method . International Journal of Progressive Education, 15(2), 44-64. doi: 10.29329/ijpe.2019.189.4

Harvard
Aksu, G. and Guzeller, C. (2019). Analysis of Scientific Studies on Item Response Theory by Bibliometric Analysis Method . International Journal of Progressive Education, 15(2), pp. 44-64.

Chicago 16th edition
Aksu, Gokhan and Cem Oktay Guzeller (2019). "Analysis of Scientific Studies on Item Response Theory by Bibliometric Analysis Method ". International Journal of Progressive Education 15 (2):44-64. doi:10.29329/ijpe.2019.189.4.

References
  1. Abdi, A., Idris, N., Alguliyev, R. M. & Aliguliyev, R. M. (2018). Bibliometric Analysis of IP&M Journal (1980–2015), Journal of Scientometric Research, 7 (1), 54-62. [Google Scholar]
  2. Barabási, A. L. (2002) Linked: How Everything Is Connected to Everything Else. New York: Basic Books. [Google Scholar]
  3. Barnes, 1.A ( 1954). Class and committees in a Norwegian island parish. Human Relations, 7, 39-58. [Google Scholar]
  4. Barnes, J. A. & Harary, F. (1983). Graph theory in network analysis. Social Network, 5, 235-244. [Google Scholar]
  5. Borgatti, S.B., Everett, M.G. & Johnson, J.C. (2013). Analyzing Social Networks. UK: Sage Publications. [Google Scholar]
  6. Borgatti, S., & Halgin, D. S. (2011). On network theory. Organization Science, 22, 1168–1181. [Google Scholar]
  7. Borgman, C. L. (1999). Books, bytes, and behavior: Rethinking scholarly communication for a global information infrastructure. Information Services & Use, 19, 117-121. [Google Scholar]
  8. Butts, C. T. (2008). Social network analysis: A methodological introduction, Asian Journal of Social Psychology, 11, 13-41. [Google Scholar]
  9. Cartwright, D. (ed.) (1959). Studies in Social Power, Ann Arbor, Ml: Institute for Social Research. [Google Scholar]
  10. Chen C. (2005). CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature. JASIST.  [Google Scholar]
  11. Crocker, L. & Algina, J. (1986). Introduction to classical and modern test theory (First edition). California: Thomson Learning. [Google Scholar]
  12. Crossley, N., Prell, C. & Scott, J. (2009). Social Network Analysis: Introduction to Special Edition, Methodological Innovations Online, 4, 1-7. [Google Scholar]
  13. Dorogovtsev, S. N. & Mendes, J. F. F. (2002). Evolution of networks, Advances Phys51 (4), 1079–1187. [Google Scholar]
  14. Duijin, M.A.J. & Vermunt, J. K. (2006). What Is Special About Social Network Analysis?, Methodology 2006, 2 (1), 2-6. [Google Scholar]
  15. Freeman, L. C. (2004) The Development of Social Network Analysis: A Study in the Sociology of Science. Vancouver: Empirical Press. [Google Scholar]
  16. Glanzel, W. (2012). Bibliometric methods for detecting and analysing emerging research topics, El profesional de la información, 21 (2), 194-201. [Google Scholar]
  17. Güzeller, C. O. & Çeliker, N. (2017). Geçmişten Günümüze Gastronomi Bilimi: Bibliyometrik Bir Analiz, Journal of Tourism and Gastronomy Studies, 5 (2), 88-102. [Google Scholar]
  18. Hambleton, R. K., & Swaminathan, H. (1985). Item response theory: Principles and applications. Boston: Kluwer. [Google Scholar]
  19. Hogan, B., Carrasco, J. A. & Wellman, B. (2007). Visualizing Personal Networks: Working with Participant-Aided Sociograms, Field Methods 19 (2), 116-144. [Google Scholar]
  20. Jain S, Basavaraj P, Singla A, Singh K, Kundu H, Vashishtha V. (2015). Bibliometric analysis of Journal of Clinical and Diagnostic Research (Dentistry Section; 2007-2014). Journal of Clinical and Diagnostic Research. 9 (4), 47-51. [Google Scholar]
  21. Jamali, M. & Abolhassani, H. (2006). Different Aspects of Social Network Analysis, in: IEEE/WIC/ACM International Conference on Web Intelligence, 66–72. [Google Scholar]
  22. Liao, H., Tang, M., Luo, L., Li, C., Chiclana, F. ve Zeng, X.J. (2018), A Bibliometric Analysis and Visualization of Medical Big Data Research, Sustainability, 10 (166), 1-18. [Google Scholar]
  23. Liu, D.D., Liu, S.L. & Zhang, J. H. (2014). Visualization analysis of research hotspots based on CiteSpace II: taking medical devices as an example, Medical Devices: Evidence and Research, 7, 357-361.  [Google Scholar]
  24. Liu, W. & Shen, H. (2013). CiteSpace II: Idiom Studies Development Trends, Journal of Arts and Humanities (JAH), 2 (2), 85-97. [Google Scholar]
  25. Martinez, M.A., Cobo, M.J., Herrera, M. & Herrera-Viedma, E. (2015). Analyzing the Scientific volution of Social Work Using Science Mapping, Research on Social Work Practice, 25(2), 257-277. [Google Scholar]
  26. Martino, F. & Spoto, A. (2006). Social Network Analysis: A brief theoretical review and further perspectives in the study of Information Technology, PsychNology Journal, 4 (1), 53-86. [Google Scholar]
  27. McPherson, M., Smith-Lovin, L., & Cook, J. M. (2001). Birds of a feather: Homophily in social networks. Annual Review of Sociology, 27, 415–444. [Google Scholar]
  28. Moreno, J.L. (1946). Sociogram and sociomatrix: A note to the paper by Forsyth and Katz. Sociometry, 9, 348-349. [Google Scholar]
  29. Mincer, M. & Niewiadomska-Szynkiewicz, E. (2012). Application of Social Network Analysis to the Investigation of Interpersonal Connections, Journal of Telecommunications and information technology, 2, 83-91. [Google Scholar]
  30. OECD, (2017).  PISA 2015 Technical Report: Scaling PISA data, OECD Publishing, Paris. [Google Scholar]
  31. Pritchard, A. (1969). Statistical Bibliography or Bibliometrics. Journal of Documentation, 25 (4), 348–349. [Google Scholar]
  32. Reise, S. P., Ainsworth, A. T. & Haviland, M. G. (2005). Item Response theory. Fundamentals, applications, and promise in psychological research. Current Directions in Psychological Science, 14 (2), 95-101. [Google Scholar]
  33. Sünbül, Ö. ve Erkuş, A. (2013). Madde Parametrelerinin Değişmezliğinin Çeşitli Boyutluluk Özelliği Gösteren Yapılarda Madde Tepki Kuramına Göre İncelenmesi, Mersin Üniversitesi Eğitim Fakültesi Dergisi, 9 (2), 378-398. [Google Scholar]
  34. Synnestvedt M, Chen C, Holmes J. (2005). CiteSpace II: visualization and knowledge discovery in bibliographic databases, AMIA AnnuSymp Proc 2005, 724-728. [Google Scholar]
  35. Tsay, M. Y. (2011). A Bibliometric Analysis on the Journal of Information Science, Journal of Library and Information Science Research, 5 (2), 1-28. [Google Scholar]
  36. Van Leeuwen T. N. (2004). Second generation bibliometric indicators: the improvement of existing and development of new bibliometric indicators for research and journal performance assessment procedures [dissertation]. Leiden. [Google Scholar]
  37. Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications. New York: Cambridge University Press. [Google Scholar]
  38. Wasserman, S. & Faust, K. (2009) Social Network Analysis: Methods and Applications, USA: Cambridge University Press. [Google Scholar]
  39. Wasserman, S., & Robbins, G. (2005). An introduction to random graphs, dependence graphs, and p*. In P. J. Carrington, J. Scott, & S. Wasserman, (eds.). Models and Methods in Social Network Analysis. Cambridge: Cambridge University Press. [Google Scholar]
  40. Watts, D. J. (2004) Six Degrees. New York: W. W. Norton. [Google Scholar]
  41. Wimmer, A. & Min, B. (2006). From empire to nation-state: Explaining wars in the modern world, 1816–2001. American Sociological Review, 71 (6), 867–897. [Google Scholar]
  42. Wölfer, R., Faber, N. S. & Hewstone, M. (2015). Social Network Analysis in the Science of Groups: Cross-Sectional and Longitudinal Applications for Studying Intra and Intergroup Behavior, Theory, Research, and Practice, 19 (1), 45–61. [Google Scholar]
  43. Wu, Y. T. (2013). Research trends in technological pedagogical content knowledge (TPACK) research: A review of empirical studies published in selected journals from 2002 to 2011. British Journal of Educational Technology, 44 (3), 73-76. [Google Scholar]
  44. Yalçın, H. & Yayla, K. (2016). Teknolojik Pedagojik Alan Bilgisi Konusunda Yapılan Araştırmaların Bibliyometrik Analizi ve Bilimsel İletişim, Eğitim ve Bilim, 41 (188), 291-307. [Google Scholar]
  45. Zhang, H., Huang, M., Quing, X., Li, G. & Tian, C. (2017) Bibliometric Analysis of Global Remote Sensing Research during 2010–2015, International Journal of Geo information, 6 (332), 1-19. [Google Scholar]