Low completion rates for apprentices and trainees have received considerable attention recently and it has been argued that NCVER seriously understates completion rates. In this paper Tom Karmel uses NCVER data on recommencements to estimate individual-based completion rates. It is estimated that around one-quarter of trade apprentices swap employers during their apprenticeship. Taking this into account, Karmel estimates completion rates for individuals, ranging from 39.2% for the food trades to 64.2% for electrotechnology and telecommunications trades workers. He notes that employer churn is an issue, with the worst occupations being hairdressing and the food trades.
This paper was prepared for the Australian Government's National Resources Sector Employment Taskforce, which was created to investigate the extent to which skill shortages might impact on the development of the resources sector. It applies historical apprenticeship commencement rates to population projections to provide an estimate of the number of tradespeople likely to be working in the resources sector between 2010 20 at a detailed level and by region.
Using a 'life tables' approach for recently commencing apprentices and trainees, this technical paper provides information on the methodology used to estimate completion and attrition rates .
Information on the divergence between student numbers and delivery hours for the period 2002 to 2007 is provided in this technical paper. The change in hours from one year to the next is decomposed into three effects, one of which is 'hours inflation', whereby nominal hours increase over time for the same unit of competency or module. Here we show that the 'hours inflation' explains relatively little of the divergence between students and hours. However, another form of hours creep, whereby new modules have higher average hours than ceased modules, was of some significance at the start of the period in question.
This technical paper examines some large and unusual movements for data in the 2007 VET Provider Collection by comparison with 2006. Changes in the patterns of courses undertaken explain most of the divergence between students, enrolments and hours.