SavedAdd your journal

Journals / Yükseköğretim Dergisi / 2021 / Cilt: 11 - Sayı: 2

Investigation of Trends in National and International Studies in Higher Education by Means of Big Data and Data Mining: 1965–2019

Yüksekö¤retim Alan›nda Yap›lan Ulusal ve Uluslararas› Çal›flmalardaki E¤ilimlerin Büyük Veri ve Veri Madencili¤i ile ‹ncelenmesi: 1965–2019

Onur İŞBULAN
Nazire Burçin HAMUTOĞLU
Mübin KIYICI
Pages
276–296
Publication Date
2022-11-05
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

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

The findings were discussed, and some suggestions, such as using different methods, focusing on policy-making rather than the current sit- uation in higher education, and focusing on digitalization in higher edu- cation, were made for future studies.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Studies carried out in the field of higher education have taken on the mis- sion of solving the problems of higher education institutions on a global level.
📊
Key Findings & Data:In this study, the national and international studies related to higher education between 1965 and 2019 that were included in the ERIC database were examined from a scientometric point of view.
💡
Conclusion & Impact:The findings were discussed, and some suggestions, such as using different methods, focusing on policy-making rather than the current sit- uation in higher education, and focusing on digitalization in higher edu- cation, were made for future studies.
🔬Design:Research Article
📍Scope:2019 Verileri
⚙️Variables:Domain Parameters

Abstract

Studies carried out in the field of higher education have taken on the mis- sion of solving the problems of higher education institutions on a global level. This enables institutions to have different perspectives, to keep themselves up-to-date, and to approach problems in higher education with a visionary perspective. In this study, the national and international studies related to higher education between 1965 and 2019 that were included in the ERIC database were examined from a scientometric point of view. The results obtained were evaluated thematically. Analyzing the big data at the micro level in line with the research purpose revealed the trends in the studies conducted in the field of higher education from past to present. Considering these trends, the higher education studies in Turkey mostly focused on the concept of attitude, predominantly employed quantitative methods, and aimed at revealing the existing situ- ation rather than being innovative. 371,771 studies/articles related to higher education in the ERIC database were examined by their type, sub- ject, title, author, target group, and research location. The results obtained differed periodically in their international and national dimen- sions. The findings were discussed, and some suggestions, such as using different methods, focusing on policy-making rather than the current sit- uation in higher education, and focusing on digitalization in higher edu- cation, were made for future studies.

Özet

Geçmiflten günümüze yüksekö¤retim alan›nda yap›lmakta olan çal›flmalar yüksekö¤retim kurumlar›n›n sorunlar›n› küresel düzlemde ele alarak çözme misyonunu üstlenmektedir. Bu durum, kurumlar›n farkl› bak›fl aç›lar›na sa- hip olmalar›na, kendilerini güncel tutmalar›na ve yüksekö¤retimdeki sorun- lara vizyoner bir bak›fl aç›s› ile yaklafl›mlar›na olanak sa¤lamaktad›r. Bu çal›fl- mada 1965–2019 y›llar› aras›nda yüksekö¤retim ile ilgili ulusal ve uluslarara- s› alanda yap›lan ve ERIC veri taban›nda yer alan çal›flmalar bilimetrik bak›fl aç›s› ile incelenmifltir. Elde edilen sonuçlar ise tematik olarak de¤erlendiril- mifltir. Bu amaç kapsam›nda büyük veri mikro düzeyde analiz edilerek elde edilen bulgular ile birlikte, yüksekö¤retim alan›nda geçmiflten günümüze ya- p›lan çal›flmalardaki e¤ilimler ortaya konulmaktad›r. E¤ilimler dikkate al›n- d›¤›nda, Türkiye’de yap›lan yüksekö¤retim çal›flmalar›n›n genelde tutum üzerine yo¤unlaflt›¤›, nicel yöntemlerin fazlaca kullan›ld›¤›, yenilikçi çal›fl- malardan ziyade var olan durumun ortaya konuldu¤u çal›flmalar göze çarp- maktad›r. Çal›flmada ERIC veri taban›nda yer alan yüksekö¤retim ile ilgili 371.771 çal›flma/makale; türüne, alanlar›na, bafll›klar›na, yazarlar›na, hedef kitlelerine ve yap›ld›¤› yere göre incelenmifltir. Elde edilen sonuçlar›n dö- nemsel olarak uluslararas› ve ulusal boyutta birbirinden farkl›laflt›¤› gözlen- mifltir. Çal›flmada elde edilen bulgular tart›fl›larak, gelecek çal›flmalara ve araflt›rmac›lara yönelik önerilerde bulunulmufltur. Bu öneriler aras›nda fark- l› yöntemlerin kullan›lmas› gerekti¤i, var olan durumdan ziyade yüksekö¤re- tim alan›nda politika gelifltirici çal›flmalara ihtiyaç oldu¤u ve yüksekö¤retim- de dijitalleflme gibi çal›flmalara odaklan›lmas› gibi öneriler yer almaktad›r.

🔖

Cite This Article

İŞBULAN, O., HAMUTOĞLU, N. B., KIYICI, M. (2022). Investigation of Trends in National and International Studies in Higher Education by Means of Big Data and Data Mining: 1965–2019. Yükseköğretim Dergisi, Cilt: 11 - Sayı: 2, 276–296. https://ajindex.com/articles/647672

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (14)

  1. Al, U., Sezen, U., & Soydal, ‹. (2019). Türkiye’nin bilimsel yay›nlar›n›n sos- yal a¤ analizi yöntemiyle de¤erlendirilmesi. Ankara: Hacettepe Üniversi- tesi Bilgi ve Belge Yönetimi Bölümü. Eriflim adresi http://www. openaccess.hacettepe.edu.tr:8080/xmlui/bitstream/handle/11655/ 11897/F1_SOBAG110K044. pdf?sequence=1 (1 Kas›m 2020).
  2. Altbach, P. G. (2005). Globalization and the university: Myths and realities in an unequal world. The NEA 2005 Almanac of Higher Education. Eriflim adresi http://www.nea.org/assets/ img/PubAlmanac/ALM_05_06.pdf (8 Eylül 2020).
  3. Aslan, E. (2014). Türkiye’de akademik aç›k eriflim dergi yay›nc›l›¤› ve çeviribilim alan›ndaki aç›k eriflim dergiler. Diyalog - Interkulturelle Zeitschrift für Germanistik, 2(1), 144–155. Ayd›n, A., Selvitopu, A., & Kaya, M. (2018). Türkiye’de yüksekö¤retim yönetimi alan›nda üretilen doktora tezlerine iliflkin bir inceleme. Yüksekö¤retim ve Bilim Dergisi, 8(2), 305–313.
  4. Bearman, M., Smith, C. D., Carbone, A., Slade, S., Baik, C., Hughes- Warrington, M., & Neumann, D. L. (2012). Systematic review methodology in higher education. Higher Education Research & Development, 31(5), 625–640.
  5. Bird, S., Klein, E., &. Loper, E. (2009). Natural language processing with Python. Sebastopol, CA: O’Reilly Media Inc. Chen, C. P., & Zhang, C. Y. (2014). Data-intensive applications, chal- lenges, techniques and technologies: A survey on big data. Information Sciences, 275, 314–347.
  6. Chen, M., Mao, S., & Liu, Y. (2014). Big data: A survey. Mobile Networks and Applications, 19, 171–209.
  7. Davi, A., Haughton, D., Nasr, N., Shah, G., Skaletsky, M., & Spack, R. (2005). A review of two text-mining packages: SAS text mining and wordstat. The American Statistician, 59(1), 89–103.
  8. Erdem, A. R. (2006). Dünyadaki yüksekö¤retimin de¤iflimi. Selçuk Üniver- sitesi Sosyal Bilimler Enstitüsü Dergisi, 15, 299–314.
  9. Fan, J., Han, F., & Liu, H. (2014). Challenges of big data analysis. National Science Review, 1(2), 293–314.
  10. Feinerer, I., Hornik, K., & Meyer, D. (2008). Text mining infrastructure in R. Journal of Statistical Software, 25(5), 1–54.
  11. Gandomi, A., & Haider, M. (2015). Beyond the hype: Big data concepts, methods, and analytics. International Journal of Information Management, 35(2), 137–144.
  12. Gülmez, D., & Yavuz, M. (2019).
  13. Türkiye, Amerika Birleflik Devletleri ve Birleflik Krall›k yüksekö¤retim kurumlar›n›n amaç ve yap› boyutlar› bak›m›ndan de¤erlendirilmesi. Yüksekö¤retim ve Bilim Dergisi, 9(1), 144–155.
  14. Hashem, I. A. T., Yaqoob, I., An