Sinan Gemici

Development Patterns of Occupational Aspirations in Adolescents with High-Incidence Disabilities:

This study analyzed the longitudinal development of occupational aspiration prestige scores over a 12-year period (Grade 8 to 8 years postsecondary) to better understand this aspect of career choice from adolescence into adulthood for people with high-incidence disabilities. A curvilinear trajectory was detected where aspirations increased during high school, but decreased after school completion. The only covariate positively associated with the intercept factor was academic achievement. Higher socioeconomic status was associated with a positive change in the slope of aspirations across the 3 time points before school completion. In adulthood, disability status was the only significant factor associated with aspiration change. Findings are considered with regard to the potential influence of special education services and disability on career development and choice.

Senior secondary workplace learning and transition success in Australia

Purpose – The purpose of this paper is to examine the effectiveness of participation in workplace learning among senior secondary students in Australia. Work placements are deemed to be effective if they meet policy objectives of improving student transitions by (a) enhancing Year 12 completion rates and (b) increasing the engagement of participants in post‐school work or study. Engagement is defined as full‐time study, full‐time work, some full‐time/part‐time combination, or two simultaneous part‐time engagements (e.g. part‐time work and part‐time study).Design/methodology/approach – Propensity score matching is used to address selection bias into work placements. After controlling for numerous student background characteristics and creating equivalent comparison groups, we estimate the influence of participation in work placements on Year 12 completion and post‐school engagement.Findings – It is found that participation in work placements during Year 11 is associated with a 5.2 percent increase in Year ...

Socioeconomic status and the allocation of government resources in Australia: How well do geographic measures perform?

Purpose - The aim of this paper is to compare the performance of area-based vs individual-level measures of socioeconomic status (SES). Design/methodology/approach - Using data from the longitudinal surveys of Australian youth (LSAY), a multidimensional measure of individual SES is created. This individual measure is used to benchmark the relative usefulness of socio-economic indexes for areas (SEIFA), a geographic set of measures often used in Australia to assess the SES of individuals. Both measures are compared in terms of classification bias. The effects of using the different SES measures on participation in post-compulsory education are examined. Findings - SEIFA measures perform satisfactorily with regard to the aggregate measurement of SES. However, they perform poorly when their use is aimed at channelling resources toward disadvantaged individuals. It is at the individual level that the analysis reveals the shortcomings of area-based SES measures. Research limitations/implications - While region based measures are relatively easy to collect and utilise, we suggest that they hide significant SES heterogeneity within regional districts. Hence, the misclassification resulting from the use of regional measures to direct support for low SES groups creates a risk for resource misallocations. Originality/value - The finding that region-based measures are subject to significant misclassification has important research and policy implications. Given the increasing availability of individual-level administrative data, the paper suggests that such data be used as a substitute for geographic SES measures in categorising the SES of individuals.

A Primer for Handling Missing Values in the Analysis of Education and Training Data.

Abstract Quantitative research in vocational education and training (VET) is routinely affected by missing or incomplete information. However, the handling of missing data in published VET research is often sub-optimal, leading to a real risk of generating results that can range from being slightly biased to being plain wrong. Given that the growing availability of data from large-scale surveys and administrative collections offers exciting new opportunities for quantitative VET research, it is important that researchers follow best-practice approaches when using such data in their own work. Against this backdrop, we: (1) provide a primer on the use of appropriate missing data methods for quantitative VET research; and (2) illustrate the detrimental effects of inefficient methods on research results via a simulation study using real-world education and training data from the Longitudinal Surveys of Australian Youth (LSAY).

Use of propensity score matching for training research with observational data

Abstract Evaluations of vocational education and training (VET) programs play a key role in informing training policy in Australia and elsewhere. Increasingly, such evaluations use observational data from surveys or administrative collections to assess the effectiveness of VET programs and interventions. The difficulty associated with using observational data is that they are inherently prone to selection bias, which results from individuals self-selecting into a given VET program based on differences in background characteristics or other external factors. The effects of the VET program on outcomes of interest are thus confounded with the effects of pre-existing systematic differences between program participants and non-participants. Propensity score matching (PSM) can mitigate selection bias in evaluation studies with observational data by statistically balancing program participants and non-participants post hoc on observed background characteristics. This article seeks to offer a general introduction to PSM and to provide interested VET researchers with an initial stepping stone for using the method in their own work.