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This document provides technical detail and supporting data for the research findings discussed in 'The student journey in VET: the many faces of completion and non-completion'. The analysis in this technical paper explores: (1) an approach to identifying VET subject enrolment activity that serves a compliance or regulatory purpose; (2) variability in completion rates across VET qualifications, and associated differences in patterns of subject enrolments and outcomes; (3) different indicators of student outcomes in VET, including program completion, subject completion, and movement to subsequent VET; (4) student training pathways exploring the extent to which students undertook programs, stand-alone subjects, or a combination of the two, and how this training choice evolved over time; and (5) student training pathways exploring the extent to which students went on to enrol in a program at a higher, lower, or the same level of educations, and how these pathways compared for students who did and did not complete their initial program.

Module A of the OECD Higher Education Policy Survey (HEPS) 2022 elicited information on policies to promote digitalisation of higher education in OECD member and accession countries. In total, 30 jurisdictions responded, providing comparative information on various areas of digitalisation policy, from regulation and governance to financial and human resources. The survey results provide insight into the role of public authorities in guiding, coordinating and resourcing the digital transformation of higher education institutions. The analysis and comparative tables in this working paper provide insights that can support the development of strategic digitalisation policies.

With the widespread onset of the COVID-19 pandemic in 2020, Australian universities anticipated a significant loss of students and revenue and hence forecast the need for significant job reductions. Using Higher Education Statistics (HES) data on student numbers and full-time equivalent (FTE) staff by field of study, we explored changes which occurred between 2019 and 2020, this data only becoming publicly available in 2022. Against expectations, and with the exception of the field of study of Management and Commerce, nationally student numbers did not decline, but increased marginally. Our interest lay in the impact of this on casual academic staff employment in Australia's public universities, noting institutional strategies of having a flexible pool of casual staff to manage fluctuations in student demand. While the HES data does not allow firm conclusions, trends may become clearer with the release of the 2021 data. Nonetheless, it appears that many universities reduced casual academic staff numbers and marginally increased full and part time appointments. Overall, there were fewer academic staff to teach a static or increased number of students. What this exercise suggests is that irrespective of student enrolments, some universities may have used the pandemic as an opportunity for restructures and academic renewal. It also highlights the difficulties that universities may experience in managing their academic workforce.

The OECD Future of Education and Skills 2030 (E2030) project's overall goal is that of looking to the future in terms of how school curricula should evolve given the technological advances and other changes that societies are now facing. Towards that end, the E2030 project centres on the idea that education needs to equip students with the knowledge, skills, attitudes and values they need to become active, responsible and engaged citizens. Mathematics is considered a highly relevant subject for achieving the above stated goals, as such it requires further and more detailed analysis. As a result, it has been chosen as one of the E2030 project's subject-specific analyses. The project has been named the Mathematics Curriculum Document Analysis (MCDA) study as per the request of participating countries. This working paper presents the findings of the MCDA study, which involves participants from 19 countries and jurisdictions.

The National Student Outcomes Survey (SOS) collects information about students who completed their vocational education and training (VET) in the previous calendar year. The gathered information on the surveyed VET students includes their reasons for training, employment outcomes, satisfaction with training, and further study outcomes. The survey covers students who have completed a qualification (graduates) and those who have completed only part of a course and then left the VET system (subject completers). The National Centre for Vocational Education Research (NCVER) has conducted the survey with government-funded VET students annually since 1999. In 2016, the scope of the survey was expanded to report on the outcomes of graduates whose training was Commonwealth--or state-funded as well as fee-for-service graduates. These graduates were referred to as total VET graduates. An explanation of the difference between total VET and government-funded student outcomes can be found in appendix A. The expanded scope was applied to the 2017 survey for graduates (following a successful trial in 2016) and for the first time for subject completers and the series renamed VET student outcomes. At the time of sample selection, insufficient information is available from the National VET Provider Collection to identify 'actual' subject completers. Instead, a sample of potential subject completers is chosen, which includes students who are continuing in the VET system. The status of respondents is determined through the survey responses. As such, respondents to the SOS include a number of students who were sampled as subject completers based on administrative data reported to the National VET Provider Collection, but self-identify in the questionnaire as graduates. For many years these 'self-reported graduates' (SRGs) were categorised as graduates in survey outputs, because the self-report was deemed to be more reliable than the collection data. However, it became apparent that many SRGs were not, in fact, graduates. In response to this issue, in 2012, NCVER created a logistic model that predicted the eligibility of a SRG being an 'actual' graduate based on their personal and training characteristics (Braysher 2012). This model has since been run annually for each SOS to assign group membership to SRGs. Those SRGs that were not predicted by the model to be a graduate were re-assigned to their original subject completer status. One of the conditions of the initial analysis was that the model should be reviewed at least every four years to assess its ongoing validity and to make possible modifications should demographics and administrative data change and alter the predictive power of the model. The model was reviewed by NCVER in 2015 (unpublished). The review found some changes in data quality, but found no evidence that these changes were affecting the estimates. At the time no changes were recommended to the logistic model or graduate reclassification procedure, but it was recommended that the model be reviewed again at a later stage. In relation to data quality, the proportion of subject completers claiming to be self-reported graduates has declined significantly since 2007, particularly from 2015 to 2017, highlighting the improvement in the quality of the National VET Provider Collection data since the need to run the model arose (appendix B). Hence, it was appropriate to review the model again. This report presents the findings of an additional comprehensive review of the model and methodology.

This occasional paper is the first in a series on the National Quality Framework (NQF). This paper offers detailed insights into education and care service quality ratings for Quality Area 1 -- Educational Program and Practice, which focuses on ensuring that educational program and practice is stimulating and engaging, enhances children's learning and development, and meets children's individual learning and development needs. Australian Children's Education and Care Quality Authority (ACECQA) has chosen to focus this first occasional paper on Quality Area 1 because of its vital contribution to child outcomes and because the evidence indicates that services are less likely to meet the National Quality Standard (NQS) in this Area. Additionally, the paper is timely given ACECQA's work in period 2014/15 with Regulatory Authorities and Professional Support Coordinators to deliver national workshops to educators to help them better understand and meet the requirements of Quality Area 1. The paper provides a brief overview of the NQS, its rating system, quality areas and overall ratings to date. It then examines Quality Area 1 looking at differences across jurisdictions, management types, service sub-types, and socioeconomic and remoteness classifications. The paper culminates by examining patterns in the distribution of Quality Area 1 ratings and discusses possible explanations for these variations, as well as implications of the report findings and future directions. The paper is intended to be of interest to people who deliver education and care services, people who provide training and professional development services to the sector, and to officers in the Regulatory Authorities that conduct quality rating. Unless otherwise stated, the paper draws on data from the National Quality Agenda Information Technology System (NQA ITS) as at 31 December 2015.

The topic of more frequent and timely vocational education and training (VET) data has been an issue of interest for a number of years. Since 2015, the National Centre for Vocational Education Research (NCVER) has collected and reported data on government-funded students and courses on a quarterly basis. These quarterly data submissions are cumulative and allow additional data to be reported and corrections made to previously submitted data. The first year of quarterly reporting has provided a useful insight into how training activity is reported by the different jurisdictions over a calendar year. This paper presents the results of some initial analysis of that data using the reporting scope that was in place for 2015 reporting, broadly defined as all activity delivered by government providers and government-funded activity delivered by community education and other registered providers.

Early years are a critical period for skill development. In this sense, the Early Childhood Education and Care (ECEC) programmes have an important role in promoting children's learning during this period. This study aimed to explore the effectiveness of ECEC programmes by analysing the relationship between students' ECEC attendance and their later academic proficiency using PISA 2015 data. PISA results show that across the OECD countries, students who had attended ECEC tend to have higher scores in academic proficiencies at the age of 15. However, these differences in academic proficiencies between those who attended ECEC versus those who did not attend are almost nil when students' socio-economic status (SES) is considered. This relationship reflects differential access to learning opportunities for children from deprived contexts. Furthermore, results show that entering ECEC programmes earlier than the typical time is associated with lower proficiencies at the age of 15. Therefore, earlier entry to ECEC is not necessarily beneficial. Learning benefits of ECEC provision vary considerably across PISA countries illustrating the importance of a country-specific policy context and the quality of their ECEC provision. The analyses of several quality indicators point out that the improved quality of ECEC programmes is associated with higher academic skills at later stages. These results highlight that mere attendance to ECEC programmes is not enough to ensure better academic performance. The quality of the educational provision, especially concerning those students from disadvantaged backgrounds, should be ensured.

This is a support document to the "Longitudinal Surveys of Australian Youth (LSAY) 2009 Cohort User Guide" report. Developed for users of LSAY, the user guide consolidates information about the LSAY 2009 cohort into one document. This support document provides employment information for the guide. [For the main report, "Longitudinal Surveys of Australian Youth (LSAY) 2009 Cohort User Guide. Technical Paper 74," see ED536971. For other supporting documents, see "Longitudinal Surveys of Australian Youth (LSAY) 2009 Cohort User Guide: Data Elements A--Demographics. Technical Paper 74A" (ED536979); "Longitudinal Surveys of Australian Youth (LSAY) 2009 Cohort User Guide: Data Elements B1--Education (School and School Transition). Technical Paper 74B1" (ED536973); "Longitudinal Surveys of Australian Youth (LSAY) 2009 Cohort User Guide: Data Elements B2--Education (Post-School). Technical Paper 74B2" (ED536975); and "Longitudinal Surveys of Australian Youth (LSAY) 2009 Cohort User Guide: Data Elements D--Social. Technical Paper 74D" (ED536972).]

This is a support document to the "Longitudinal Surveys of Australian Youth (LSAY) 2009 Cohort User Guide" report. Developed for users of LSAY, the user guide consolidates information about the LSAY 2009 cohort into one document. This support document provides social information for the guide. [For the main report, "Longitudinal Surveys of Australian Youth (LSAY) 2009 Cohort User Guide. Technical Paper 74," see ED536971. For other supporting documents, see "Longitudinal Surveys of Australian Youth (LSAY) 2009 Cohort User Guide: Data Elements A--Demographics. Technical Paper 74A" (ED536979); "Longitudinal Surveys of Australian Youth (LSAY) 2009 Cohort User Guide: Data Elements B1--Education (School and School Transition). Technical Paper 74B1" (ED536973); "Longitudinal Surveys of Australian Youth (LSAY) 2009 Cohort User Guide: Data Elements B2--Education (Post-School). Technical Paper 74B2" (ED536975); and "Longitudinal Surveys of Australian Youth (LSAY) 2009 Cohort User Guide: Data Elements C--Employment. Technical Paper 74C" (ED536974).]

This is a support document to the "Longitudinal Surveys of Australian Youth (LSAY) 2009 Cohort User Guide" report. Developed for users of LSAY, the user guide consolidates information about the LSAY 2009 cohort into one document. This support document provides post-school information for the guide. [For the main report, "Longitudinal Surveys of Australian Youth (LSAY) 2009 Cohort User Guide. Technical Paper 74," see (ED536971). For other support documents, see "Longitudinal Surveys of Australian Youth (LSAY) 2009 Cohort User Guide: Data Elements A--Demographics. Technical Paper 74A" (ED536979); "Longitudinal Surveys of Australian Youth (LSAY) 2009 Cohort User Guide: Data Elements B1--Education (School and School Transition). Technical Paper 74B1" (ED536973); "Longitudinal Surveys of Australian Youth (LSAY) 2009 Cohort User Guide: Data Elements C--Employment. Technical Paper 74C" (ED536974); and "Longitudinal Surveys of Australian Youth (LSAY) 2009 Cohort User Guide: Data Elements D--Social. Technical Paper 74D" (ED536972).]

This is a support document to the "Longitudinal Surveys of Australian Youth (LSAY) 2009 Cohort User Guide" report. Developed for users of LSAY, the user guide consolidates information about the LSAY 2009 cohort into one document. This support document provides school and school transition information for the guide. [For the main report, "Longitudinal Surveys of Australian Youth (LSAY) 2009 Cohort User Guide. Technical Paper 74," see ED536971. For other supporting documents, see "Longitudinal Surveys of Australian Youth (LSAY) 2009 Cohort User Guide: Data Elements A--Demographics. Technical Paper 74A" (ED536979); "Longitudinal Surveys of Australian Youth (LSAY) 2009 Cohort User Guide: Data Elements B2--Education (Post-School). Technical Paper 74B2" (ED536975); "Longitudinal Surveys of Australian Youth (LSAY) 2009 Cohort User Guide: Data Elements C--Employment. Technical Paper 74C" (ED536974); and "Longitudinal Surveys of Australian Youth (LSAY) 2009 Cohort User Guide: Data Elements D--Social. Technical Paper 74D" (ED536972).]

Differences in teacher quality are commonly cited as a key determinant of the huge international student performance gaps. However, convincing evidence on this relationship is still lacking, in part because it is unclear how to measure teacher quality consistently across countries. We use unique international assessment data to investigate the role of teacher cognitive skills as one main dimension of teacher quality in explaining student outcomes. Our main identification strategy exploits exogenous variation in teacher cognitive skills attributable to international differences in relative wages of nonteacher public sector employees. Using student-level test score data, we find that teacher cognitive skills are an important determinant of international differences in student performance. Results are supported by fixed-effects estimation that uses within-country between-subject variation in teacher skills.

The Student Outcomes Survey is an annual national survey of vocational education and training (VET) students. Since 1995, participants have been asked to rate their satisfaction with different aspects of their training, grouped under three main themes: teaching, assessment, and generic skills and learning experiences. While the composition of the bank of satisfaction questions has remained fairly constant over time and the suitability of the three overarching satisfaction categories has been validated statistically on several occasions, little progress has been made on creating summary measures that encapsulate the three main themes of student satisfaction. Such summary measures would be much more useful to researchers than responses to the bank of 19 satisfaction questions, which are very detailed. This paper compares three methods of creating a composite score and evaluates their statistical veracity. These methods are Rasch analysis, weighted means and simple means. This report finds that all three methods yield similar results and so recommends using the simple means method to create the summary measures. (Contains 7 tables, 2 figures and 2 footnotes.) [Funding for this paper was provided through the Department of Industry, Innovation, Science, Research and Tertiary Education.]

This is a support document to the "Longitudinal Surveys of Australian Youth (LSAY) 2009 Cohort User Guide" report. Developed for users of LSAY, the user guide consolidates information about the LSAY 2009 cohort into one document. This support document provides demographics information for the guide. [For the main report, "Longitudinal Surveys of Australian Youth (LSAY) 2009 Cohort User Guide. Technical Paper 74," see ED536971. For other supporting documents, see "Longitudinal Surveys of Australian Youth (LSAY) 2009 Cohort User Guide: Data Elements B1--Education (School and School Transition). Technical Paper 74B1" (ED536973); "Longitudinal Surveys of Australian Youth (LSAY) 2009 Cohort User Guide: Data Elements B2--Education (Post-School). Technical Paper 74B2" (ED536975); "Longitudinal Surveys of Australian Youth (LSAY) 2009 Cohort User Guide: Data Elements C--Employment. Technical Paper 74C" (ED536974); and "Longitudinal Surveys of Australian Youth (LSAY) 2009 Cohort User Guide: Data Elements D--Social. Technical Paper 74D" (ED536972).]

Developed for users of the Longitudinal Surveys of Australian Youth (LSAY), this user guide consolidates information about the LSAY 2009 cohort into one document. The guide aims to address all aspects of the LSAY data including: how to access the data; data restrictions; variable naming conventions; the structure of the data; documentation; classifications and code frames used; weights; and derived variables. Updates to the Y09 data file are appended. (Contains 14 tables, 9 figures and 6 footnotes.) [For supporting documents, see "Longitudinal Surveys of Australian Youth (LSAY) 2009 Cohort User Guide: Data Elements A--Demographics. Technical Paper 74A" (ED536979); "Longitudinal Surveys of Australian Youth (LSAY) 2009 Cohort User Guide: Data Elements B1--Education (School and School Transition). Technical Paper 74B1" (ED536973); "Longitudinal Surveys of Australian Youth (LSAY) 2009 Cohort User Guide: Data Elements B2--Education (Post-School). Technical Paper 74B2" (ED536975); "Longitudinal Surveys of Australian Youth (LSAY) 2009 Cohort User Guide: Data Elements C--Employment. Technical Paper 74C" (ED536974); and "Longitudinal Surveys of Australian Youth (LSAY) 2009 Cohort User Guide: Data Elements D--Social. Technical Paper 74D" (ED536972).]

Apprentice and trainee data are reported by the State and Territory Training Authorities to NCVER (National Centre for Vocational Education Research) on a quarterly basis, starting at the September quarter of 1994. The set of data submitted that quarter is referred to as Collection 1. The sets of data submitted in subsequent quarters are referred to as Collection 2, Collection 3 and so on. NCVER publishes data on the numbers of contracts of training that commence, complete, cancel/withdraw, re-commence, expire or suspend and the time at which these events occur (referred to as the "date of effect"). From these events, the number of contracts in training at a given time can be calculated. Due to time delays in reporting data on the status of contracts to NCVER, the most recent data are estimated. Further details regarding this methodology are provided in the technical paper produced by NCVER, Estimation of Apprentice and Trainee Statistics, which can be found at http://www.ncver.edu.au/publications/2267.html. The purpose of this technical paper is to document the adjustments that are made to the estimates at each collection, and produce a cumulative document of these adjustments, commencing at Collection 60, June 2009 estimates. (Contains 15 figures.) [For the main report, "Australian Vocational Education and Training Statistics: Apprentices and Trainees. September Quarter, 2010", see ED516870.]

The Longitudinal Surveys of Australian Youth (LSAY) ask participants how satisfied they are with aspects of their lives. Their answers give us a measure of the subjective wellbeing of our youth and can be used to explore the link between education, employment and wellbeing. Yet, wellbeing is broader than satisfaction with life. It also encompasses physical, mental and emotional health, as well as social aspects of life. Therefore, to gain a better understanding of the state of young people's wellbeing, this briefing paper uses national statistics from the Australian Bureau of Statistics (ABS) to examine the major trends that can affect their participation in education and employment. Based on this broader definition of wellbeing, young people are generally disability-free and rate their state of health as "excellent", "very good" or "good". However, there are some concerning trends in their wellbeing over time; for instance, one in four young people suffers from a mental health disorder and over 30% are overweight or obese. This paper also analyses the responses of LSAY participants interviewed between 1995 and 2006 to explore how subjective wellbeing changes during the transition from school to work, and finds evidence of notable changes to the average life satisfaction ratings of the cohort between ages 16 to 25. The period between their late teens and early 20s is a particularly happy time for young people. They are finishing school and embarking on early work experiences or post-school study. The majority of them are still living at home and enjoying their social lives. This is also a time when young people's satisfaction with their future and their level of independence begin to grow. By age 25, young people are less happy with their social life, home life, and career prospects and work. This may be related to unmet expectations or not having a satisfying career. Data from the Household, Income and Labour Dynamics in Australia (HILDA) survey indicate that this downward trend in life satisfaction continues beyond age 25. Previous research on the relationship between education, employment and wellbeing is summarised and we discuss some of the measures of wellbeing, particularly those used in LSAY. This discussion highlights the need for further work on definitions of wellbeing and the development of a consistent framework for measuring this complex construct. (Contains 3 tables, 11 figures and 6 footnotes.)

During the recent economic downturn, media and industry reports of skill shortages in the trades continued to appear. The intent of this paper is to examine the evidence for skill shortages in the trades persisting during the economic downturns over the last 20 years, using various indicators. These include employment growth, vacancy rates, unemployment rates, apprentice completions and occupational mobility. This paper contains the following key messages: (1) There is no evidence of persistent skill shortages during downturns in the construction, automotive and engineering trades, and unconvincing evidence of persistent shortages in the electrotechnology and telecommunications trades, the food trades and hairdressing; (2) Declining numbers of apprenticeship completions account for much of the persistent shortage in the electrotechnology and telecommunications trades during the 1990s and 2000s, but apprenticeship completions (expressed as a proportion of employment) for this trade have now recovered to pre-1992 levels. If recent completion numbers are maintained, it should be possible to avoid future skill shortages; and (3) Very high job churn creates the perception of persistent skill shortages in the food trades and in hairdressing. Many food tradespersons and hairdressers swap employers but remain in their occupation. Two appendices are included. (Contains 22 tables, 21 figures and 4 footnotes.)

Despite significant improvements in the areas of education and employment, the gaps between Indigenous and non-Indigenous youth remain. Across some indicators--for example, university participation--the gap has actually widened. This is mainly because improvements for non-Indigenous young people have matched or surpassed the gains made by Indigenous young people. Governments at both federal and state levels are striving to improve Indigenous people's educational attainment and employment participation. The consistently lower scores in reading and maths assessments achieved by Indigenous youth have meant that improving their performance in literacy and numeracy has become one of the key target areas on the national agenda to assist in closing the gap between Indigenous and non-Indigenous Australians. Using data from the Longitudinal Surveys of Australian Youth (LSAY), this briefing paper explores the impact of literacy and numeracy levels on the educational gap between Indigenous and non-Indigenous youth. The paper focuses on the early post-school outcomes of Indigenous and non-Indigenous young people between 1999 and 2007. Appendices include: (1) Measuring the Gap; and (2) Additional Table. (Contains 11 tables and 3 footnotes.)

Apprentice and trainee data are reported by the state and territory training authorities to the National Centre for Vocational Education and Training (NCVER) on a quarterly basis, starting at the September quarter of 1994. The set of data submitted that quarter is referred to as collection 1. The sets of data submitted in subsequent quarters are referred to as collection 2, collection 3 and so on. At the time of writing, the set of data being submitted is for the June 2009 quarter and is referred to as collection 60. Of particular interest are the numbers of contracts of training that commence, complete, cancel/withdraw, recommence, expire or suspend, and the time at which these events occur (referred to as the "date of effect"). From these events, the number of contracts "in-training" at a given time can be calculated. The purpose of this technical paper is to describe: (1) the way data accumulate over many collections; (2) how items derived from the data change as the data accumulate; (3) the endorsed estimation method (developed from the analysis of the above); (4) the formulae for calculating the required estimates; and (5) potential weaknesses in the method. Supporting data is appended. (Contains 4 tables, 8 figures and 1 footnote.) [This paper is an updated version of the "Estimation of Apprentice and Trainee Statistics. Technical Paper" report. For the original paper, see ED510131.]

To what extent do local governments use vocational education and training as a staff retention strategy? Human resources personnel from a selection of councils around Australia believed that a lack of career development or training opportunities might cause an employee to leave their organisation. They had some reservations about the quality and value of VET, but planned to continue to use it for staff development as it is the most widely available option. This paper is by a novice researcher from the Community of Practice program, which is part of NCVER's Building Researcher Capacity initiatives. The research for this paper was undertaken while the author worked as National Workforce Development Advisor at Government Skills Australia. The paper investigates the extent to which local government councils offer vocational education and training as a strategy to retain their employees. The study comprised interviews with key human resource personnel in 14 councils around Australia, as well as an analysis of council records on staff training and turnover. Appended are: (1) Interview questions; and (2) Turnover data analysis by council. (Contains 9 tables and 10 footnotes.)

There are many factors which might cause a student to drop out of a course of study; some of these are preventable. This paper describes the piloting of a survey tool designed to identify students at risk of not completing. Attendance was found to be the strongest predictor of module completion; low or declining scores on the survey were also predictive of students dropping out. The research for this paper was undertaken by a novice researcher in the Community of Practice Scholarship Program, which is funded through National Centre for Vocational Education Research's (NCVER's) Building Researcher Capacity initiative. Appended are: (1) Defining completion; (2) Surveys; (3) Comments from student surveys; and (4) Correlation values--survey scores (all measures). (Contains 5 tables, 7 figures, and 6 footnotes.)

In the year to February 2002, one in every five of the 9.8 million people who worked in Australia experienced at least one job separation. This paper looks at the determinants of job separation within a stayer/mover framework using individual-level data for Australia. Conditional on job separation the paper also investigates the determinants of job-to-job turnover (differentiated by occupation) and job-to-joblessness turnover (unemployment and exit from the labour force). The results show the importance of the normal demographic variables (age, gender, immigrant status and place of residence) but also qualifications and other labour market variables (hours of work, reason for job separation) for explaining turnover behaviour. Appended are: (1) mathematical description of the logit model and that of calculating the marginal effect; and (2) tables and figures. (Contains 10 tables, 13 figures and 8 footnotes.)

In March 1997, all State, Territory and Commonwealth education ministers agreed on the national goal: that every child leaving primary school should be numerate and able to read, write and spell at an appropriate level. To provide focus for this goal, ministers also agreed to a sub-goal: that every child commencing school from 1998 will achieve a minimum acceptable literacy and numeracy standard within four years. To help support the achievement of these goals, ministers agreed to the implementation of the National Literacy and Numeracy Plan, the essential features of which are: (1) early assessment and intervention for students at risk of not achieving minimum required standards; (2) development of national benchmarks for each of years 3, 5 and 7; (3) assessment of student progress against these benchmarks; (4) national reporting of benchmark data, and (5) professional development for teachers. Education authorities in all States and Territories, assisted by the Commonwealth, have been engaged in implementing these elements of the plan since its formulation. This paper concerns the national reporting of benchmark data for 2007 and follows on from earlier editions of the "National Report on Schooling in Australia," which published data for 1999, 2000, 2001, 2002, 2003, 2004, 2005 and 2006. The publications reflect the continuing development of the benchmark reporting process. This 2007 edition also provides data on the performance of students in metropolitan, provincial, remote and very remote areas. In each State and Territory, students' school locations are categorised using the Ministerial Council on Education, Employment, Training and Youth Affairs (MCEETYA) Geographical Location Classification, and procedures closely related to the approaches of the Australian Bureau of Statistics. From 2005, States and Territories commenced collecting information on student socioeconomic background through school enrolment processes. Preliminary data from this collection approach has indicated there is a relatively low response rate from parents/care-givers. Information about student socioeconomic background will be published in the relevant chapter of the full "National Report on Schooling in Australia." (Contains 36 tables and 12 figures.) [For "National Report on Schooling in Australia, 2006. Preliminary Paper. National Benchmark Results Reading, Writing and Numeracy Years 3, 5 and 7," see ED534692.]

Taking a gap year--a break between high school and university--is becoming increasingly popular with Australian students. In terms of length and purpose, the traditional notion of a gap year being a year off between school and university has expanded considerably over time. For the purposes of the analysis reported in this paper, a person who takes a gap year is defined as "an individual who commenced university one to two years after completing Year 12. This includes those who accept and defer their university placement for one to two years" (Curtis, Mlotkowski & Lumsden 2012). Highlights of this report include: (1) In Australia the incidence of taking a gap year has increased from 10% in the period 1999-2000 to 24% in 2009-10; (2) The top four primary activities undertaken by gap students in 2009-10 were work (51%), full-time study leading to a non-university qualification (10%), other study (6%), and travel (6%); (3) Characteristics of gap-takers include: (a) being academically less inclined than non-gap-takers; (b) living in regional locations when at school; (c) having English speaking backgrounds; (d) being employed when in Year 12 at school; and (e) being less likely to receive Youth Allowance payments while at school; (4) In their first year of university, gap-takers are more likely to study in the areas of education and creative arts; and (5) Those who don't take a gap year are substantially more likely at age 24 to be employed full-time and to work in professional occupations than gap-takers. Much of this difference can be attributed to the fact that, in terms of their careers, gap-takers are a year or two behind those who don't take a gap year. The data do not allow the authors to measure the longer-term outcomes of both groups because the Longitudinal Surveys of Australian Youth (LSAY) stops at age 25. Appended are: (1) Gap year definitions; and (2) LSAY cohorts sample sizes and durations. (Contains 13 tables.) [For "Bridging the Gap: Who Takes a Gap Year and Why? Longitudinal Surveys of Australian Youth. Research Report," see ED533077.]

In March 1997, all State, Territory and Commonwealth education ministers agreed on the national goal: that every child leaving primary school should be numerate and able to read, write and spell at an appropriate level. To provide focus for this goal, ministers agreed to a sub-goal: that every child commencing school from 1998 will achieve a minimum acceptable literacy and numeracy standard within four years. To help support the achievement of these goals, ministers agreed to the implementation of the National Literacy and Numeracy Plan, the essential features of which are: (1) early assessment and intervention for students at risk of not achieving minimum required standards; (2) development of national benchmarks for each of years 3, 5, and 7; (3) assessment of student progress against these benchmarks; (4) national reporting of benchmark data, and (5) professional development for teachers. Education authorities in all States and Territories, assisted by the Commonwealth, have been engaged in implementing these elements of the plan since its formulation. This paper concerns the national reporting of benchmark data for 2006 and follows on from earlier editions of the "National Report on Schooling in Australia," which published data for 1999, 2000, 2001, 2002, 2003 and 2005. The publications reflect the continuing development of the benchmark reporting process. This 2006 edition also provides data on the performance of students in metropolitan, provincial, remote and very remote areas. In each State and Territory, students' school locations are categorised using the Ministerial Council on Education, Employment, Training and Youth Affairs (MCEETYA) Geographical Location Classification, and procedures closely related to the approaches of the Australian Bureau of Statistics. In this 2006 edition, results for the performance of Indigenous students by geolocation are reported for the first time. (Contains 30 tables and 12 figures.) [For "National Report on Schooling in Australia, 2005. Preliminary Paper. National Benchmark Results Reading, Writing and Numeracy Years 3, 5 and 7," see ED534693.]

Following the collapse of the US investment bank Lehmann Brothers in September 2008, the world economy began a downward spiral, with many countries falling into recession. Australia experienced significant stock market losses and unemployment rates began to climb. This briefing paper considers how young people fared in previous downturns and discusses how structural labour market changes over the past 20 years have affected young people this time around. It also looks at the qualitative evidence from respondents in the Longitudinal Surveys of Australian Youth (LSAY), exploring common themes in how they perceived the economic downturn had affected their work and study intentions in 2009. The author finds that, although Australia experienced a relatively mild downturn, young people bore almost the entire weight of the full-time job decline (including apprenticeships), and a disproportionate share of the increase in unemployment. Those unable to find a job or who have been made redundant are at risk of remaining unemployed for a significant time, with potential longer-term scarring effects. Recent structural changes to the labour market, such as rising educational participation, appear to provide some protection for young people. However, full-time work for 15 to 19-year-olds has become even more concentrated in industries more sensitive to economic changes such as building and construction, and retail. Calculation of Impact of Change in Employment is appended. (Contains 8 tables, 16 figures and 2 footnotes.)

This paper was originally developed to help the Training and Skills Commission in South Australia consider the pathways between elements of the vocational education and training (VET) system, how they are working and what improvements can be made. It has been revised to make it national in scope. The authors reveal that quite substantial numbers of VET graduates go on to university level study or further study within VET itself. Significant numbers of university graduates also go on to study in VET. However, not all VET graduates choose to study at a higher level; a substantial proportion of students going on to further study do so at the same or lower level. This suggests that entitlement models need to consider horizontal (skills broadening) as well as vertical (only qualifications at a higher level) in their funding mix. Additional data tables are appended. (Contains 13 tables and 2 footnotes.)

In recent times social capital has received considerable attention because it is seen as having the potential to address many of the problems facing modern society, including the poor educational outcomes of considerable numbers of young people. This paper uses data from the Longitudinal Surveys of Australian Youth (LSAY) to explore the relationship between social capital at age 15 and participation in education and training at age 17. The issue is whether social capital is yet another factor which advantages the already advantaged, or whether social capital operates separately from family background. Findings reveal that social capital influences educational participation "over and above" the effects of background characteristics such as parents' education levels, parental occupation, geographic location, cultural background, school sector and academic achievement. For both males and females, participation in a diverse range of activities has the greatest influence on participation in education and training, followed by the strength of the relationship students have with their teachers. Increasing rates of participation in sport also increase educational participation for females. The authors note that, if anything, the findings underestimate the net effects of social capital because the results cannot fully account for the accumulation of social capital prior to the age of 15. The finding that social capital matters for school education is a very positive one. It implies that activities that promote and encourage engagement at school can go some way to redressing economic and social disadvantage. Appended are: (1) Factor analysis; (2) Distribution of social capital; (3) Logistic regression (1); (4) Logistic regression (2); and (5) Distribution of social capital by academic orientation. (Contains 10 tables, 12 figures and 6 footnotes.)

Migration patterns to and from Australia are becoming complex with migration programmes increasingly targeted towards meeting the needs of the labour market and regional development. This paper provides an analysis of the permanent and temporary movements of people to and from Australia in the last three years and their impact on the skilled labour supply in Australia. The paper also provides an analysis of occupational mobility of permanent immigrants. The results are consistent with previously published results of initial downward occupational mobility among immigrants. The consequence of this is wastage of skills which the country can least afford in times of reported skills shortages. Skills wastage can be minimised by making available to newly arrived immigrants appropriate programmes for recognising previously acquired qualifications and occupational licenses; updating occupation-specific skills; and providing up-to-date information on the labour market and its operation. In this respect, the TAFE (Technical and Further Education) system in Australia is uniquely placed to play a key role. (Contains 7 footnotes, 1 figure, and 21 tables.)

In March 1997, all State, Territory and Commonwealth education ministers agreed on the national goal: that every child leaving primary school should be numerate and able to read, write and spell at an appropriate level. To provide focus for this goal, ministers agreed to a sub-goal: that every child commencing school from 1998 will achieve a minimum acceptable literacy and numeracy standard within four years. To help support the achievement of these goals, ministers agreed to the implementation of the National Literacy and Numeracy Plan, the essential features of which are: (1) early assessment and intervention for students at risk of not achieving minimum required standards; (2) development of national benchmarks for each of years 3, 5, and 7; (3) assessment of student progress against these benchmarks; (4) national reporting of benchmark data, and (5) professional development for teachers. Education authorities in all States and Territories, assisted by the Commonwealth, have been engaged in implementing these elements of the plan since its formulation. This paper concerns the national reporting of benchmark data for 2005 and follows on from earlier editions of the "National Report on Schooling in Australia," which published data for 1999, 2000, 2001, 2002, 2003 and 2004. The publications reflect the continuing development of the benchmark reporting process. This 2005 edition also provides data on the performance of students in metropolitan, provincial, remote and very remote areas. In each State and Territory, students' school locations are categorised using the Ministerial Council on Education, Employment, Training and Youth Affairs (MCEETYA) Geographical Location Classification, and procedures closely related to the approaches of the Australian Bureau of Statistics. (Contains 30 tables and 12 figures.) [For "National Report on Schooling in Australia, 2004. Preliminary Paper. National Benchmark Results Reading, Writing and Numeracy Years 3, 5 and 7," see ED534694.]

Apprentice and trainee data are reported by the State and Territory Training Authorities to the National Centre for Vocational Education Research (NCVER) on a quarterly basis, starting at the September quarter of 1994. The set of data submitted that quarter is referred to as Collection 1. The sets of data submitted in subsequent quarters are referred to as Collection 2, Collection 3 and so on. NCVER publishes data on the numbers of contracts of training that commence, complete, cancel/withdraw, re-commence, expire or suspend and the time at which these events occur (referred to as the "date of effect"). From these events, the number of contracts in training at a given time can be calculated. Due to time delays in reporting data on the status of contracts to NCVER, the most recent data are estimated. The purpose of this technical paper is to document the adjustments that are made to the estimates at each collection, and produce a cumulative document of these adjustments, commencing at Collection 60, June 2009 estimates. (Contains 12 figures.) [For the accompanying report, "Australian Vocational Education and Training Statistics: Apprentices and Trainees. Annual, 2009", see ED510873.]

Apprentice and trainee data are reported by the State and Territory Training Authorities to NCVER (National Centre for Vocational Education Research) on a quarterly basis, starting at the September quarter of 1994. The set of data submitted that quarter is referred to as Collection 1. The sets of data submitted in subsequent quarters are referred to as Collection 2, Collection 3 and so on. At the time of writing, the set of data being submitted is for the June 2009 quarter and is referred to as Collection 60. Of particular interest is the numbers of contracts of training that commence, complete, cancel/withdraw, re-commence, expire or suspend and the time at which these events occur (referred to as the "date of effect"). From these events, the number of contracts in training at a given time can be calculated. The purpose of this technical paper is to describe: (1) the way data accumulate over many collections; (2) how items derived from the data change as the data accumulates; (3) the endorsed estimation method (developed from the analysis of the above); (4) the formulae for calculating the required estimates; and (5) potential weaknesses in the method. Throughout the main text of this document data for New South Wales commencements and expired contracts are used as examples to illustrate the concepts being discussed. Supporting data is appended. A glossary is included. (Contains 4 tables and 8 figures.) [For the accompanying report, "Apprentices and Trainees: December Quarter, 2009", see ED510135.]

Apprentice and trainee data are reported by the State and Territory Training Authorities to the National Centre for Vocational Education Research (NCVER) on a quarterly basis, starting at the September quarter of 1994. The set of data submitted that quarter is referred to as Collection 1. The sets of data submitted in subsequent quarters are referred to as Collection 2, Collection 3 and so on. NCVER publishes data on the numbers of contracts of training that commence, complete, cancel/withdraw, re-commence, expire or suspend and the time at which these events occur (referred to as the "date of effect"). From these events, the number of contracts in training at a given time can be calculated. Due to time delays in reporting data on the status of contracts to NCVER, the most recent data are estimated. The purpose of this technical paper is to document the adjustments that are made to the estimates at each collection, and produce a cumulative document of these adjustments, commencing at Collection 60, June 2009 estimates. (Contains 6 figures.) [For the accompanying report, "Apprentices and Trainees: September Quarter 2009," see ED508817.]

This paper investigates change in employer satisfaction with vocational education and training (VET) between the years 2005 and 2009. Employer satisfaction was measured using the Survey of Employer Use and Views of the VET System, conducted biennially since 2005. Key measures from the survey are employer satisfaction with: vocational qualifications as a job requirement; apprentices and trainees; and nationally recognised training. To determine whether the distribution of responding employers accounts for the large differences in survey estimates, employer satisfaction is modelled taking into account the size and industry of responding employers. Appended are: (1) Differences in the survey estimates; and (2) Regression results. (Contains 11 tables and 3 figures.)

This technical paper examines some large and unusual movements for data in the 2007 VET (Vocational Education Training) Provider Collection by comparison with 2006. Changes in the patterns of courses undertaken explain most of the divergence between students, enrolments and hours. Appendices include: (1) Derivation of the decomposition; (2) Tables of enrolment growth and its effects--2006-2007; and (3) Reporting hours and enrolments for common, new and ceased modules by state. (Contains 48 tables and 1 footnote.) [This work has been produced by the National Centre for Vocational Education Research (NCVER) on behalf of the Australian Government and state and territory governments with funding provided through the Australian Department of Education, Employment and Workplace Relation.]

In 2015, for the first time in its history, PISA (the Programme for International Student Assessment) asked teachers to describe the various aspects of their working environment and teaching practices. This paper examines how teacher, student, and school characteristics are related to science teachers' satisfaction in 19 PISA-participating countries and economies. The findings show that the most satisfied science teachers tend to be those who are initially motivated to become teachers. The results also highlight the positive relationship between science teachers' satisfaction and teacher collaboration, good disciplinary climate in science classes, availability of school resources, and the opportunity to participate in professional-development activities.

This paper investigates large differences in employer satisfaction with vocational education and training (VET) between 2005 and 2007. Employer satisfaction was measured using the Survey of Employer Use and Views of the VET System, which was first conducted in 2005 and repeated in 2007. It measures employer satisfaction with vocational qualifications as a job requirement, apprentices and trainees, and nationally recognised training. Differences in weighted estimates of employer satisfaction were examined in light of sample sizes and the distribution of employers' responses to the survey. A model-based approach to estimation was used, which accounted for the relationship between satisfaction and the size and industry of the employer. Key findings included: (1) In three out of five cases, the large differences in employer satisfaction between years were found to be real and not as a result of the structure of the sample; (2) In the remaining two cases, the differences in employer satisfaction were found not to be significant. This suggested that the structure of the sample had the potential to reveal differences that did not hold up under closer scrutiny; and (3) Survey estimates of large differences between years need to be treated with some caution and a model-based approach to estimation provides a tool to give assurance that large differences are real and not a result of peculiarities in the sample. An appendix, comprising the majority of the report, provides the regression results. (Contains 7 tables.) [This work has been produced by the National Centre for Vocational Education Research (NCVER) as a joint initiative of the Australian Government and state and territory governments, with funding provided through the Australian Department of Education, Employment and Workplace Relations.]

Lower-level qualifications (certificate I and II programs) provide little or no immediate return to the individual in terms of increased wages. However, lower-level qualifications are intended to prepare students who would otherwise not be capable of enrolling in and completing a higher-level qualification or making a successful transition into the workplace, because of their ability, social circumstances, or previous educational experiences. The aim of this report is to test whether lower-level qualifications serve a broader purpose by functioning as a "stepping stone" to further study or into the labour market. The critical part of the methodology is the selection of the comparison group. Using data from the Longitudinal Surveys of Australian Youth (LSAY), the research matches certificate I and II graduates to other young people who share similar characteristics but who have neither completed nor are undertaking study or training at a higher level. The report compares their further study, training, employment and overall wellbeing outcomes two years after graduation and at age 26. The findings do not relate to certificate I or II qualifications completed as part of an apprenticeship or traineeship. Appended are: (1) Characteristics of certificate I and II students; and (2) Statistical methodology. (Contains 19 tables.)

This report reviews the use of loans for learning in 33 European countries and analyses the schemes in eight selected Member States: France, Hungary, the Netherlands, Austria, Poland, Finland, Sweden and the UK. The analysis shows that loan schemes vary considerably across Europe in terms of types and levels of learning covered, conditions of access, repayment and governance. Some loans aim to increase participation in learning in general, while others are designed to promote equity. The report attempts to assess the selected loans and discusses their strengths and weaknesses and determinants of performance, while considering if a given scheme operates on a large scale or targets niche groups. The evaluation results provide a basis for identifying good practice principles for designing and implementing loans. Policy recommendations are formulated based on these findings. Annexed are: (1) Methodology; (2) Key terms and definitions; (3) Information on countries/schemes selected for in-depth analysis; (4) Proposed typologies of VET loan schemes; (5) Tables and figures; (6) Tosmana truth tables; (7) Questionnaires; (8) Basic characteristics of non-European loan schemes. (Contains 37 tables, 5 figures, 20 boxes and 33 footnotes.)

This research used a survey to investigate the attitudes of people with a disability towards undertaking training. The findings show very positive attitudes towards training by participants and, although the ability to generalise to the wider population is limited, one thing is clear: generally, people with a disability are willing to undertake vocational education and training (VET) and consider it a good option in helping them find employment. Some factors affected attitudes more than others, including level of school-based education; highest qualification level completed; whether people had single or multiple disabilities; and, to some extent, gender. (Contains 10 tables and 1 footnote.)

Apprentice and trainee data are reported by the State and Territory Training Authorities to National Centre for Vocational Education Research (NCVER) on a quarterly basis, starting at the September quarter of 1994. The set of data submitted that quarter is referred to as Collection 1. The sets of data submitted in subsequent quarters are referred to as Collection 2, Collection 3 and so on. NCVER publishes data on the numbers of contracts of training that commence, complete, cancel/withdraw, re-commence, expire or suspend and the time at which these events occur (referred to as the "date of effect"). From these events, the number of contracts in training at a given time can be calculated. Due to time delays in reporting data on the status of contracts to NCVER, the most recent data are estimated. This technical note provides a cumulative record of the adjustment notes relevant for the estimation of apprentice and trainee figures at each collection. This document commences with the adjustment note for Collection 64 (June 2010 estimates used to produce the March quarter 2010 publication). (Contains 15 figures.) [This is a support document for "Australian Vocational Education and Training Statistics: Apprentices and Trainees, March Quarter 2010"]

This paper provides an analysis of revenue for and expenditure on Australian education institutions. It includes a review of funding from public and private sources and from overseas. Analyses are made for education as a whole and for the major sectors: schools, vocational education and training (VET) and higher education. Estimates are considered in current and constant prices. Analysis is made of changes in expenditure per student or hour of training. Consideration is given to non-institutional expenditures including student assistance and employer expenditures. In the last few years expenditures on educational institutions have grown in real terms by about 2 per cent per annum. Private expenditure and expenditure by overseas students have grown faster than public expenditure, though part of the expansion of private expenditures has been financed by government, such as grants to non-government institutions and advances to support the Higher Education Contribution Scheme (HECS). Most of the additional resources for education have gone to schooling. On average, both government and non-government schools have experienced continuing substantial growth in real expenditure per student. The total real resources in VET in 2001 were about the same as in 1997 but hours of training had increased by about 4 per cent per annum. There are various ways in which efficiencies have been pursued to offset the effects of the apparent reduction in resources per hour. An increased proportion of expenditure in this period went to non-TAFE (Technical and Further Education) providers and, as with universities, there was a reduction in the share of expenditure on personnel. In higher education there has been little growth in publicly funded Australian student numbers in recent years and a small decline in real public funding per student. The most notable changes are the continued growth in the proportion of the public expenditures funded through HECS and the expansion in fee paying overseas students and Australian students in postgraduate courses. The decline in staffing ratios in higher education is significantly larger than the decline in funding per student. The gap is a matter for further analysis. An appendix, The Nature of the VET Financial Data, is included. (Contains 9 footnotes and 32 tables.)

This project, conducted by the Centre for the Economics of Education and Training (CEET) during 2003, set out to investigate the relationship between innovation and the provision of appropriate education and training in regional Australia. The project was designed as a pilot study with two main purposes: (1) To test whether and how the issues could be investigated, with the aim of using the findings as a basis for larger and more comprehensive studies in the future; and (2) To collect and analyse information about innovation and the provision of relevant education and training in some specific regions that would advance understanding of the major concerns and issues, both within the particular area and more generally in regional Australia. The Gannawarra Shire of northern Victoria was chosen for this pilot study because contacts made in the Shire indicated considerable support for investigating the issues and offered opportunities for access to local government, enterprises and training providers. Preliminary discussions and examination of published material also indicated substantial innovation in the region. The project comprised a search for sources of information about the Gannawarra region including geography, population, industries and employment; analysis of this material to gain an understanding of the major characteristics of the region; consultations with relevant people and organisations within and outside the region; and a survey of individuals and enterprises on the Gannawarra Business Register. Opportunities for presenting the preliminary and final survey results within the Shire to local enterprises and training providers enabled the findings to be discussed and contributed to ongoing refinement of the conclusions. Key findings include: (1) Considerable innovation is occurring in the industries and enterprises of Gannawarra, contributing to changes in the types of training being sought; (2) A balance of formal and informal provision of education and training in Gannawarra, although further investigation is recommended to determine that the balance is optimal to needs; and (3) Establishment of Local Learning and Employment Networks (LLENs) by the Victorian Government has been successful in strengthening relationships between educational providers, communities and industry in Gannawarra. Two attachments are included: (1) Regional Development, Skill Needs and Training Questionnaire; and (2) Initiatives of the LLENs in Gannawarra Shire. (Contains 10 figures and 40 tables.)

The Career Interest Test (third edition) is a 63-item forced choice and individually administered instrument of 7 vocational interest categories: Outdoor, Practical, Scientific, Creative, Business, Office, and People Contact. The test is designed for use in vocational contexts as a practical guide to educational and vocational planning. The item content has been revised from the 1988 edition and subsequent revisions. The Career Interest Test is now made freely available. Descriptive data on some 900 Australian high school students and occupational data are available together with information relating to the reliability and concurrent validity of the results. This manual replaces the earlier version. (Contains 12 tables, 6 figures, and 16 references.) (Author/SLD)

This study used Australian Bureau of Statistics (ABS) survey data to assess changes in child poverty in Australia between 1982 and 1995-96. The findings suggest a dramatic one-third drop in before-housing child poverty during this period, largely as a result of the very substantial increases in government cash payments to low-income families with children. However, while there have been sharp falls in poverty among dependent children, poverty rates among 15- to 18-year-olds who have left the parental home or who are still living at home but not in full-time study have increased very sharply. In addition, the after-housing poverty rate has changed little, apparently due to a compositional shift in the types of family in after-housing poverty. (Author)

An exploratory study was the first part of an extensive study of retention in vocational education and training (VET) modules in Australia. These four major categorical variables were used to explore patterns in the withdrawal rate: year, gender, state/territory, and area of study/discipline. Withdrawal rates declined significantly from 1995-97. The rate at which males and females failed to complete modules differed by slightly less than 1 percent. Differences among states and territories were quite marked--from a withdrawal rate of just over 4 percent in South Australia to more than 21 percent in the Australian Capital Territory. Area of study also greatly affected withdrawal. Differences varied from a low 8.3 percent in Built Environment to a high 18.1 percent for Humanities. Data showed a significant inverse relationship between withdrawal rates for males and females across disciplines. Females had withdrawal rates higher than males in states where withdrawal rates were relatively low; this reversed in states where withdrawal rates are relatively high. A range of methods were explored to understand the interactions among these four variables: hierarchical breakdown analyses; additive analyses (analysis of variance, logit analysis, iterative fits); and weighted net percentage difference analyses. It was found that gender played a role in withdrawal rates only through its mediation by other variables, and that discipline had an important role. (Contains 16 references, 14 tables, and 9 figures.) (YLB)