Session Information
Contribution
The dropout rate is one of the key performance criteria for educational institutions at all levels of education. It has been widely studied for the undergraduate student, many theoretical frameworks were developed and a lot of quantitative studies based on big datasets were conducted. It can be caused by two main reasons. The first is that this level of education includes the highest number of people and the problem of undergraduate attrition is conceptualized as a problem of unequal access to tertiary education and as an aspect of social inequality. The second possible reason is the vast amount of available data. Unfortunately, we lack such statistical data on doctoral students. That is why most of the studies of doctoral dropout rate are either qualitative or case studies. The second limitation is that the majority of doctoral attrition studies has organizational and applied nature and do not contain any theoretical framework (Tinto 1995).
Studies of dropout factors usually focus on the following groups of attrition determinants:
- Individual: socio-demographic (Wright & Cochrane, 2000) or psychological characteristics (Litalien et al 2015);
- Organizational: characteristics of department and field of study (Baird 1990), integration into academic and social environment (Tinto 1995);
- Institutional: reforms of doctoral education (Geven, Skopek, Triventi, 2017).
This research focuses on institutional factors of doctoral student attrition. The aim is to examine the effect of the reform that was implemented in the HSE doctoral programs at 2010 (“The Full-time Advanced Doctoral Program”) on Ph.D. attrition.
The Full-time Advanced Doctoral Program aimed to support HSE doctoral students financially (monthly stipend is 10 times higher than average), to train them better (the Program implies more structured obligatory educational part), to adjust doctoral students to the academic environment (full-time job at HSE departments or research centers related to the thesis topic, obligatory one semester internship abroad).
Method
I will use a regression analysis to predict two events: the dropout or defense. The model will include such variables as gender, the field of study, characteristics of previous degrees, age, characteristics of scientific adviser and institutional factors. I use a data set on graduate students who studied at the Higher School of Economics (HSE, Russia) in the period from 2000 to 2017 and completed training with different results (anonymized data from administrative records were obtained from the HSE in December 2017 and comprise data for 4048 Ph.D. students).
Expected Outcomes
Right now I check the dataset and expect to get the final model and the results during next two months.
References
Baird L.(1990) Disciplines and Doctorates: The Relationships Between Program Characteristics and the Duration of Doctoral Study. Research in Higher Education, Vol. 31, No. 4 Geven, K., Skopek, J., & Triventi, M. (2017). How to Increase PhD Completion Rates? An Impact Evaluation of Two Reforms in a Selective Graduate School, 1976–2012. Research in Higher Education. https://doi.org/10.1007/s11162-017-9481-z Litalien, D., & Guay, F. (2015). Dropout intentions in PhD studies: A comprehensive model based on interpersonal relationships and motivational resources. Contemporary Educational Psychology, 41, 218–231. https://doi.org/10.1016/j.cedpsych.2015.03.004 Tinto, V. (1975). Dropout from Higher Education: A Theoretical Synthesis of Recent Research. Review of Educational Research, 45(1), 89. https://doi.org/10.2307/1170024 Wright, T., & Cochrane, R. (2000). Factors Influencing Successful Submission of PhD Theses. Studies in Higher Education, 25(2), 181–195. https://doi.org/10.1080/713696139
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