MODELING THE CONTRIBUTION OF DISTANCE EDUCATION TO STUDENTS’ PREPARATION FOR THE PROFESSIONS

Year 2021, Volume: 22 Issue: 1, 106 - 119, 31.12.2020

Mustafa Cavus Betul Kan Kılınc Berna Yazıcı Seda Tekelı Guler Gunsoy Bulent Gunsoy Caglar Karaduman

https://doi.org/10.17718/tojde.849890

Cited By: 1

Abstract

There is an increasing interest in predicting the contribution level of open and distance learning to students’
career, in order to perceive the pathway for higher quality standards. For this purpose, Anadolu University
Faculty of Open Education, which can be considered a leader in its field, to learners’ professions and their
career goals, organized a research project in which a questionnaire was conducted involving approximately
17,000 associate and undergraduate students to build a database of responses. The data was used to determine
the contribution level of the open education programs. The five ordered-level contributions were recorded to
a response variable. Demographical, educational and economic variables were successfully used in mapping
the categorical responses using the ordinal logistic regression analysis method (OLR). The results, unlike
other studies, indicate that there is a positive relationship between family size and the contribution level of
distance education on students’ preparation for the professions. In a novel way, the socioeconomic level of
the students is considered in the OLR model as an economic factor. As a consequence, the students with
moderate and higher socioeconomic levels demonstrated superior levels of contribution.

Keywords

Distance education, life goals, profession,, ordinal logistic regression

References

• Allmendiger, J. (1989). Educational systems and labor market outcomes. European Sociological Review, 5(3), 231-250. Retrieved from https://www.jstor.org/stable/pdf/522338.
• pdf?refreqid=excelsior%3A08741828201010 760f17550232ee988c Baez, J. E. (2008). Does more mean better? sibling sex composition and the link between family size and children’s quality. IZA Discussion Paper Series, No. 3472. Retrieved January 21, 2019 from http:// ftp.iza.org/dp3472.pdf
• Bagger, J., Birchenall, J. A., Mansour, H., & Urzúa, S. (2013). Education, birth order, and family size. IZA Discussion Paper Series, No. 7454. Retrieved January 21, 2019 from http://ftp.iza.org/dp7454. pdf
• Blaabæk, E. H., Jæger, M. M., Molitoris, J. (2017). Family size and children’s educational attainment: identification from the extended family. Population Association of America Annual Meeting. 2017. Retrieved from https://paa.confex.com/paa/2017/mediafile/ExtendedAbstract/Paper12491/PAA_ Blaab aek_Jaeger_Molitoris.pdf
• Boccanfuso, D., Larouche, A., & Trandafir, M. (2015). Quality of higher education and the labor market in developing countries: evidence from an education reform in Senegal. World Development, 74(1), 412-424. doi.org/10.1016/j.worlddev.2015.05.007.
• Bougma, M., LeGrand, T. K., & Kobiané, J. F. (2015). Fertility decline and child schooling in urban settings of Burkina Faso. Demography, 52(1), 281-313. doi: 10.1007/s13524- 014-0355-0.
• Clark, A. E., Frijters, P. & Shields M. A. (2006). Income and happiness: Evidence, explanations and economic implications, Paris-Jourdan Sciences Economiques, Working Paper No: 2006-24, 1-35. Retrieved from https://halshs.archives-ouvertes.fr/halshs-00590436