Matthias Kubler’s research while affiliated with The University of Queensland and other places

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Publications (8)


Predicted probability of attending university by SES and school performance (mean of standardised Maths and English NAPLAN scores)
Marginal effect high SES vs. low SES (probability of attending university by SES and school performance (see footnote 5)
Differences in predicted probabilities of attending university by parental education and occupation
Predicted probability of attending university by SEB and school performance (quantiles of standardised NAPLAN scores). Note: 2014 School and Student data linked with 2018 Next Step survey data. Results from the multilevel logistic regression model presented as predicted probabilities
Socio-economic status, school performance, and university participation: evidence from linked administrative and survey data from Australia
  • Article
  • Full-text available

June 2024

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151 Reads

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5 Citations

Wojtek Tomaszewski

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Matthias Kubler

Despite being a target of various policy interventions across developed countries, disparities in higher education participation among students from different socio-economic backgrounds remain persistent. While previous literature has outlined the processes through which parental resources can shape students’ educational decisions and pathways, the evidence remains scarce on how the effects of social origin on the participation in higher education vary along the academic performance distribution. Utilising multilevel models applied to large-scale linked administrative and survey data from Australia, this study explores how the participation in higher education varies along the students’ performance distribution by their social origins. Our results show that the effects of social origins on university participation are most pronounced in the middle of the academic performance distribution and taper off towards either end. Consideration is also given to exploring different ways to capture socio-economic status (SES) (i.e. through parental education and occupation) as an indicator of social origins. The results show that parental education serves as a better predictor of students’ university participation than does parental occupation. The paper discusses the implications of these findings for educational policies aimed at increasing university participation among individuals from low-SES backgrounds.

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Differences in Higher Education Access, Participation and Outcomes by Socioeconomic Background: A Life Course Perspective

October 2022

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257 Reads

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12 Citations

The intergenerational transmission of socio-economic status is driven to a significant extent through parents with higher socio-economic status providing advantages to their children as they move through the education system. At the same time, attainment of higher education credentials constitutes an important pathway for upwards social mobility among individuals from low socio-economic family backgrounds. Given the critical importance of higher education for socio-economic outcomes of children, this chapter focuses on young people’s journeys into and out of university. Drawing on the life course approach and opportunity pluralism theory, we present a conceptual model of the university student life cycle that splits individuals’ higher education trajectories into three distinct stages: access, participation and post-participation. Using this model as a guiding framework, we present a body of recent Australian evidence on differences in pathways through the higher education system among individuals from low and high socio-economic status (SES) backgrounds. In doing so, we pay attention to factors such as family material circumstances, students’ school experiences and post-school plans, and parental education and expectations—all of which constitute important barriers to access, participation and successful transitions out of higher education for low SES students. Overall, our results indicate that socio-economic background plays a significant role in shaping outcomes at various points of individual’s educational trajectories. This is manifested by lower chances amongst low-SES individuals to access and participate in higher education, and to find satisfying and secure employment post-graduation. Our findings bear important implications for educational and social policy.


Predicted probabilities from random-effect logistic regression models of studying towards an Australian qualification and studying towards a degree. BNLA, waves 1–5 (2013–2017). Based on results from the model presented in columns (1) and (2) in Table 2. For discrete variables (e.g. marital status), we present predicted probabilities for each of the variable’s categories. For continuous variables (e.g., age), we selected representative values of the variable’s distribution and presented predicted probabilities for those values. Orange and green colouring is used to visually separate results for different, adjacent variables. Bars without filling denote discrete variables in which none of the categories was statistically significant relative to the reference category or continuous variables that were not statistically significant
Predicted probabilities from random-effect logistic regression models of the odds of being a student, by gender and time in Australia, employment status and marital status. BNLA, waves 1–5 (2013–2017). Based on results from the model presented in Table 7
Sample means for outcome variables, by survey wave
Understanding access to higher education amongst humanitarian migrants: an analysis of Australian longitudinal survey data

August 2022

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151 Reads

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5 Citations

Francisco Perales

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Wojtek Tomaszewski

Humanitarian migrants are amongst the most marginalised population groups in countries within the Global North, including Australia. An important channel for these migrants to successfully settle into the host society and improve their socio-economic outcomes is participation in the local education system, particularly in higher-education options. However, we know surprisingly little about the socio-demographic factors that structure inequalities in humanitarian migrants’ access to (higher) education, with evidence from robust quantitative studies being particularly scarce. The present study fills this important gap in knowledge by analysing Australian longitudinal survey data (Building a New Life in Australia; n = 2109 migrants and 8668 person-year observations) by means of random-effect panel regression models. Key results indicated that higher English-language proficiency and pre-arrival education levels are core factors fostering greater engagement with the Australian higher-education system amongst humanitarian migrants. Humanitarian-migrant women in our sample exhibited a greater adjusted likelihood of being a student than humanitarian-migrant men. Altogether, our findings confirmed inequalities in accessing the Australian higher-education system amongst humanitarian migrants, and that policy attention is required to redress this situation. However, they also stress that a ‘one size fits all’ policy strategy may be neither sufficient nor appropriate to boost their education prospects.


Towards the point of return: Maximising students' uptake of university places following deferral and leave

May 2022

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655 Reads

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1 Citation

Deferral and leave-taking behaviour substantially affects enrolment and retention rates across Australian universities. Almost ten per cent of commencing students defer their university offer every year, while over 20 per cent of continuing students take leave from their university within three years of commencing a Bachelor degree. Our research confirms that around one third of deferring students do not return to the university sector. Many more return to the sector but enrol in a different course or university from which they deferred. More worryingly, less than a third of continuing students who take leave subsequently return to study within the next two years. Universities have become more flexible in enabling students to leave, but arguably not as flexible and motivated to accommodate their return.


Descriptive statistics of ACLD data. ACLD 2011-2016, unweighted data extracted using TableBuilder
Marginal effects from growth-curve models. HILDA Survey (2001–2016). Based on results from growth-curve models presented in Table 5. Covariates held at their means and random effects at zero. Whiskers denote 90% confidence intervals
Beyond Graduation: Socio-economic Background and Post-university Outcomes of Australian Graduates

February 2021

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257 Reads

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18 Citations

Research in Higher Education

Research consistently shows that higher-education participation has positive impacts on individual outcomes. However, few studies explicitly consider differences in these impacts by socio-economic background (SEB), and those which do fail to examine graduate trajectories over the long run, non-labor outcomes and relative returns. We address these knowledge gaps by investigating the short- and long-term socio-economic trajectories of Australian university graduates from advantaged and disadvantaged backgrounds across multiple domains. We use high-quality longitudinal data from two sources: the Australian Longitudinal Census Dataset and the Household, Income and Labour Dynamics in Australia Survey. Low-SEB graduates experienced short-term post-graduation disadvantage in employment and occupational status, but not wages. They also experienced lower job and financial security up to 5 years post-graduation. Despite this, low-SEB graduates benefited more from higher education in relative terms—that is, university education improves the situation of low-SEB individuals to a greater extent than it does for high-SEB individuals.




Making Every Day Count: Effective strategies to improve student attendance in Queensland state schools

June 2017

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23 Reads

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3 Citations

This project was commissioned by the Queensland Department of Education and Training (DET) to determine what strategies are being used within Queensland government (state) schools to improve student attendance. In 2008, the Department’s Every Day Counts initiative sought to improve student attendance at school through a shared commitment by students, parents, caregivers, schools and the community. Data from DET indicate that on any given day, nine per cent of Queensland state school students are absent from school. Through the Every Day Counts website, the initiative provides resources for schools, parents and the community to promote and support student attendance at school, every school day.

Citations (5)


... Yet, although increasing numbers of relatively disadvantaged young people participate in higher education, a socioeconomic attainment gap remains (H.-P. Blossfeld et al., 2015;Bukodi & Goldthorpe, 2013;Pensiero & Schoon, 2019), even among those with similar levels of cognitive ability (Bukodi et al., 2014;Tomaszewski et al., 2024). ...

Reference:

Socio‐Economic and Gender Differences in Post‐Secondary Pathways in the UK, Germany, and Australia
Socio-economic status, school performance, and university participation: evidence from linked administrative and survey data from Australia

... In Australia, there have been numerous policy strategies, such as the Queensland government's Every Day Counts initiative (DoE, 2018), which explicitly addresses one element of this problem-attendance. This issue has been well-researched (e.g., Birioukov, 2016;Kearney & Graczyk, 2014;Ladwig & Luke, 2013;Mills et al., 2018) and involves a range of evidence-based practices for increasing student attendance. The second part is generally regarded as a problem of retention, which has also drawn interest from researchers and policy makers (e.g., Allen et al., 2018;Lamb et al., 2004;te Riele, 2007). ...

Making Every Day Count: Effective strategies to improve student attendance in Queensland state schools
  • Citing Technical Report
  • June 2017

... While global efforts have been made to achieve gender parity in education, these challenges remain entrenched in numerous regions. Extensive literature has highlighted significant disparities in educational enrolment across economic strata, with many studies relying on enrolment and attendance ratios due to their availability and ease of measurement (Blanden, Doepke & Stuhler, 2023;Tomaszewski, Perales, Xiang & Kubler, 2022;Entrich, 2020). However, such metrics fail to fully capture the complexities of educational attainment, as they do not account for students who drop out before completing their education. ...

Differences in Higher Education Access, Participation and Outcomes by Socioeconomic Background: A Life Course Perspective

... Being open access, enabling programs attract superdiverse student cohorts, and refugee students make up a significant proportion of enrolments. The number of refugee students in Australian universities is difficult to ascertain since official data counts them as 'domestic students' if they hold permanent visas (Stevenson & Baker, 2018) and because they are not recognised as an equity group, universities are not required to collect and report on (former) refugee status (Perales et al., 2022). The only data available for UniSA College is for the number of Humanitarian Visa (HV) holders, with data available from 2012 onwards; from 2012 to the start of 2024, there were 330 to 340 HV holders enrolled. ...

Understanding access to higher education amongst humanitarian migrants: an analysis of Australian longitudinal survey data

... In addition, some empirical literature examines the influence of specific graduate characteristics on different labour market outcomes, such as the probability of finding a job, wage level, and job quality, defined in terms of stability, working hours, or the risk of over-education (Lauder & Mayhew, 2020). The characteristics analysed include different fields of study (Xu, 2013;García-Aracil, 2008), participation in employability programmes (Bolli et al., 2021;Scandurra et al., 2023), study abroad (Croce & Ghignoni, 2024), socioeconomic background (Tomaszewski et al., 2021), as well as age and gender (Bellas, 2021), among others. Unfortunately, we have not identified any articles that examine the impact of multiple academic characteristics on the risk of being affected by digitalization in a comprehensive way. ...

Beyond Graduation: Socio-economic Background and Post-university Outcomes of Australian Graduates

Research in Higher Education