BİT'lerin Eğitimde Karma Yöntem Araştırmalarında Kullanımının Yöntemsel Açıdan Değerlendirilmesi

Abstract

Bu fenomenolojik araştırmanın amacı, Bilgi ve İletişim Teknolojilerinin (BİT) eğitimde karma yöntem araştırmalarında kullanımının eğitim araştırmacıları tarafından yöntemsel açıdan değerlendirilmesidir. Eğitim alanından 12 araştırmacı ile yarı-yapılandırılmış görüşmeler yapılmıştır. Veriler tematik içerik analizi ile analiz edilmiştir. Eğitim alanından araştırmacılarla yapılan görüşmelerde dokuz tema belirlenmiştir. BİT'lerin en çok vurgulanan katkısının veri toplama ile ilgili olduğu bulgusuna ulaşılmıştır. Temalardan altısı, yeni veri toplama araçlarına olan ihtiyacı ve BİT'lerin karma araştırma yöntemleri için büyük, derinlemesine ve orijinal veriler toplayarak, verilerin sağlaması ve dönüştürülmesi üzerindeki olumlu değerlendirmeleri açıklamaktadır. İki tema araştırmacıların karma araştırma yöntemindeki rolü ile ilgilidir. Eğitim alanındaki araştırmacılar, BİT'lerin karma araştırma yöntemlerinde kullanılmasının araştırmacılar arasındaki işbirliğini destekleyebileceğini ve araştırmacının sınırlılıklarını azaltabileceğini savunmaktadır. Son olarak, eğitim alanındaki araştırmacılar, yeni karma araştırma yöntemi modellerinin keşfedilmesinin dijital çağdaki kritik öneminin altını çizmektedir.

Keywords

• Eğitim araştırmacısı
• karma yöntem araştırması (KYA)
• bilimsel araştırmalarda bilgi ve iletişim teknolojileri (BİT)

Methodological Evaluation of the Use of ICTs in Mixed Method Research in Education

Abstract

The purpose of this phenomenological research was to evaluate the use of Information and Communication Technologies (ICTs) in mixed method research (MMR) in education from a educational researchers’ methodological perspective. Semi-structured interviews were conducted with 12 educational researchers. The data were analyzed by thematic content analysis. Nine themes were identified in the interviews with educational researchers. The most emphasized contribution of ICTs was found to be about data collection. Six of the themes explained the need for new data collection tools and positive evaluations of ICTs on triangulation and transformation of data by collecting massive, in-depth and original data for MMRs. Two themes were about the role of the researcher in MMRs. Educational researchers argued that the use of ICTs in MMRs can support collaborations among researchers and reduce researcher limitations. Finally, educational researchers underlined the critical importance of the discovery of new MMR models in digital age.

Keywords

• Educational researcher
• mixed method research (MMR)
• information and communication technologies (ICTs) in scientific research

References

1. Alt, D. (2018). Science teachers' conceptions of teaching and learning, ICT efficacy, ICT professional development and ICT practices enacted in their classrooms. Teaching and Teacher Education, 73, 141-150.
2. Best, S. J. and Krueger, B. S. (2004). Internet data collection, quantitative applications in the social sciences, Thousand Oaks: Sage Publications.
3. Baltar, F. and Brunet, I. (2012). Social research 2.0: virtual snowball sampling method using Facebook. Internet Research, 22(1), 57-74.
4. Bhatti, R. (2013). Impact of ICT on social science faculty members’ information usage pattern at Bahauddin Zakariya University, Multan. Library Philosophy and Practice. 928.
5. Birnbaum, M.H. (2004). Human research and data collection via the Internet. Annual Review of Psychology, 55, 803-832.
6. Bond, D., & Ramsey, E. (2010). The role of information and communication technologies in using projective techniques as survey tools to meet the challenges of bounded rationality. Qualitative Market Research: An International Journal, 13(4), 430-440.
7. Borgman, C. L. (2006). What can studies of e-learning teach us about collaboration in e-research? Some findings from digital library studies. Computer Supported Cooperative Work, 15(4), 359-383.
8. Buchanan, E. A., & Hvizdak, E. E. (2009). Online survey tools: Ethical and methodological concerns of human research ethics committees. Journal of Empirical Research on Human Research Ethics, 4(2), 37-48.

9. Campbell, D. T., & Fiske, D. W. (1959). Convergent and discriminant validation by the multitrait-multimethod matrix. Psychological Bulletin, 56, 81-105.
10. Dutton, W. H. (2013). The social shaping of digital research. International Journal of Social Research Methodology, 16(3), 177-195.
11. Fielding, N. G. (2012). Triangulation and mixed methods designs data integration with new research technologies. Journal of Mixed Methods Research, 6(2), 124-136. DOI: 10.1177/1558689812437101
12. Fung, H. P. (2013). Effects of information and communication technology on social science research. Africa Development and Resources Research Institute (ADRRI), 1, 1- 8.
13. Germanakos, P., & Belk, M. (2016). Human-centred web adaptation and personalization. Springer.
14. Granello, D. H. and Wheaton, J.E. (2004). Online data collection: Strategies for research. Journal of Counselling and Development, 82, 387-394.
15. Hackett E. J. (2011). Possible dreams: Research technologies and transformation of the human sciences. In Nagy Hesse-Biber S. (Ed.), The handbook of emergent technologies in social research (pp. 25-46). Oxford, England: University Press.
16. Harris, A. M. (2016). Video as method. Oxford University Press.
17. Hesse-Biber, S., & Griffin, A. J. (2013). Internet-mediated technologies and mixed methods research problems and prospects. Journal of Mixed Methods Research, 7(1), 43-61. DOI: 10.1177/1558689812451791
18. Juhaňák, L., Zounek, J., Záleská, K., Bárta, O., & Vlčková, K. (2019). The relationship between the age at first computer use and students' perceived competence and autonomy in ICT usage: A mediation analysis. Computers & Education, 141, 1-14.
19. Keusch, F. (2013). The role of topic interest and topic salience in online panel web surveys. International Journal of Market Research, 55(1), 59-80.
20. Kılınç, H., & Fırat, M. (2017). Opinions of expert academicians on online data collection and voluntary participation in social sciences research. Educational Sciences: Theory & Practice, 17(5).
21. Marsh, E. E. & White, M. D. (2006). Content analysis: A flexible methodology. Library Trends, 55(1), 22-45.
22. Matthijsse, S. M., de Leeuw, E. D., & Hox, J. J. (2015). Internet panels, professional respondents, and data quality. Methodology, 11, 81-88. DOI: 10.1027/1614- 2241/a000094.
23. Maxwell, J. A. (2016). Expanding the history and range of mixed methods research. Journal of Mixed Methods Research, 10(1), 12-27.
24. Miles, M. B., & Huberman, A. M. (1994). Qualitative data analysis: An expande sourcebook. Thousand Oaks, CA: Sage.
25. Misra, R., Panda, B., & Tiwary, M. (2016). Big data and ICT applications: A study. In Proceedings of the Second International Conference on Information and Communication Technology for Competitive Strategies (pp. 1-6).
26. O’Halloran, K. L., Tan, S., Pham, D. S., Bateman, J., & Moere, A. V. (2016). A digital mixed methods research design integrating multimodal analysis with data mining and information visualization for big data analytics. Journal of Mixed Methods Research, 1-20. DOI: 10.1177/1558689816651015
27. Padayachee, K. (2017). A snapshot survey of ICT integration in South African schools. South African Computer Journal, 29(2), 36-65.
28. Palinkas, L. A., Horwitz, S. M., Green, C. A., Wisdom, J. P., Duan, N., & Hoagwood, K. (2015). Purposeful sampling for qualitative data collection and analysis in mixed method implementation research. Administration and Policy in Mental Health and Mental Health Services Research, 42(5), 533-544.
29. Pinto, R. M., Wall, M. M., & Spector, A. Y. (2014). Modeling the structure of partnership between researchers and front-line service providers: Strengthening collaborative public health research. Journal of Mixed Methods Research, 8(1), 83-106.
30. Stanton, J. M. and S. G. Rogelberg (2001). Using internet/intranet web pages to collect organizational research data. Organizational Research Methods, 4, 200–217.
31. Topp, N. and Pawloski, B. (2002). Online data collection. Journal of Science Education and Technology, 11(2), 173–178.
32. Verma, C. (2017). Educational data mining to examine mindset of educators towards ICT knowledge. International Journal of Data Mining and Emerging Technologies, 7(2), 53-60.
33. Wishart, J. and Thomas, M. (2015). Introducing e-research in educational contexts, digital methods and issues arising. International Journal of Research & Method in Education, 38(3), 223-229.