Predicting departure from British education: Identifying those most at risk through discrete time hazard modelling
Predicting departure from British education: Identifying those most at risk through discrete time hazard modelling
Key takeaways
Bibliography: Alcott, B., 2013. Predicting departure from British education: Identifying those most at risk through discrete time hazard modelling. wide particip lifelong learn 15, 46–64. https://doi.org/10.5456/WPLL.15.4.46
Authors:: Ben Alcott
Collections:: UCL BCS Dump
First-page: 46
This study’s principal aim is to identify factors associated with student departure from full-time education in the United Kingdom. Utilising a discrete time hazard model, it conceptualises educational access in terms of number of completed years of education, both compulsory and non-compulsory. Using a longitudinal dataset whose participants completed education in the early 1990s, it confirms the importance of many of the key explanatory factors identified in previous research. However, it also indicates that type of state schooling may not be a significant predictor of departure after controlling for economic, identity and social class characteristics. The model also indicates that the accuracy of certain explanatory variables as predictors of dropout vary across the educational stages. Models such as this can help to improve the efficacy of access policies in Britain by identifying the students most likely to leave education at different points in schooling and higher education.
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Reading notes
Imported on 2024-05-07 21:31
⭐ Important
- & However, it also indicates that type of state schooling may not be a significant predictor of departure after controlling for economic, identity and social class characteristics. (p. 46)
- & n 2009 the most disadvantaged quintile of students were around six times less likely to participate in university than the most advantaged quintile (Vignoles and Powdthavee, 2009). (p. 46)
- important point when get to modern cohorts:
- & whilst the BCS cohort would have paid no fees at any university, on average this year English students will mostly be charged in excess of £8,000 per annum (Chowdry, Dearden, Hin and Lloyd, 2012) (p. 47)
- & Michael Gove’s (2012) assertion that a homogeneous comprehensive school sector fails students could be examined by comparing (p. 47)
- & the trajectories of students at these schools to those at grammar and religious schools. (p. 48)
- & Gibbons and Vignoles (2012) argue that the considerable socioeconomic gap in participation in higher education is rooted predominantly in poorer students achieving lower grades in academic tests throughout schooling (p. 50)
- & Chowdry et al. (2013) analysed administrative data on all students at English state schools who completed Key Stage 4 in 2002 and 2003; their results demonstrate that, prior attainment explained 60% of the raw difference in university participation rates between the top and bottom socioeconomic quintiles, even after controlling for school and individual characteristics (p. 50)
- & The authors do acknowledge though that confidence and aspirations may still be the root cause of this relationship, since disadvantaged students may not achieve academically in compulsory education because they do not believe themselves capable of studying at higher education. Nonetheless, when considering the argument of Gorard et al. that the ‘qualified age participation rate is near 100 per cent’ (2007: 124), it might seem that academic achievement prior to the higher education level should be the key focus of higher education access efforts. (p. 50)