Technical report: How do we get our chronically absent students back to school

In Term 2 this year, over 80,000 students missed more than three weeks of school.  These students who are chronically absent are often struggling, are at high risk of poor education outcomes, and have poor lifetime outcomes. 

This technical report describes what we did to look at how good the system and supports are for chronic absence in Aotearoa New Zealand. It sets out how we explored the reasons for chronic student absence, and the outcomes for students who miss significant portions of their schooling.

Download the PDF to read the technical report. 

We are grateful for the extensive support from the Ministry of Education and Social Investment Agency in this work throughout the project. We also appreciate the support from an Expert Advisory Group, made up of experts and practitioners in the education and attendance fields. We acknowledge support from members of the Steering Group who provided overall guidance and support for the project. 

This chapter discusses how we designed the evaluation, including:  

1. what we looked at  
2. who we worked with  
3. how we decided what we would do  
4. the overall approach  
5. caveats  
6. terminology  
7. report structure.   

1. What we looks at

Purpose of the evaluation

The Associate Minister of Education commissioned this evaluation to better understand the students who are chronically absent (70 percent or less attendance in a term) and to assess the effectiveness of Attendance Services in bringing those students back to school.  

Evaluation questions  

This evaluation looks at the effectiveness and value for money of interventions aimed at getting chronically absent students back to school and keeping them there. We answer five key questions.   

1. Who are the students who are chronically absent from school?  
2. Why are they absent?  
3. What are the outcomes for students who are chronically absent from school and what are the costs of those outcomes?  
4. How effective are the supports and interventions for students who are chronically absent at getting students back into school and keeping them in school? Are different models more or less effective?  
5. What needs to change so that the supports and interventions for students who are chronically absent from school achieve better results and are cost-effective?  

This report looks at students who are chronically absent, which means they miss three weeks or more a term (attending school for 70 percent of the time or less).  

2. Who we worked with

The Education Review Office (ERO) worked with the Social Investment Agency (SIA) and the Ministry of Education (the Ministry) to produce this report. It looks at how well the education system identifies the students who are chronically absent or not enrolled, and how well it works with them and their parents and whānau to get them attending school regularly.  

• The Education Review Office is responsible for reviewing and reporting on the performance of early learning services, kura, and schools. As part of this role, ERO looks at how the education system supports young people’s outcomes.  

• The Social Investment Agency is responsible for leading the implementation of social investment and providing cross-sector insights to decision makers.  

• The Ministry of Education is responsible for managing policy and performance for the education system, and delivering services and support locally, regionally, and nationally. It does this to ‘shape an education system that delivers excellent and equitable outcomes.’ 

We also worked closely with an Expert Advisory Group with a range of proficiencies, including academics, school leaders, Attendance Service staff, and staff from agencies that work to improve student attendance.  

3. How we decide what we would do

We engaged an Expert Advisory Group to provide specialist expertise and evidence-based perspectives to inform, critique, and support this evaluation. We also drew on the experience of methodology experts at SIA and within ERO to determine which areas to focus our evaluation on.  

This evaluation used a mixed-methods approach to ensure that our data is robust and that we are hearing the experiences of students, school leaders, Attendance Service staff, and parents and whānau.  

4. The overall approach

Mixed-methods

ERO used a mixed-methods approach, drawing on a wide range of administrative data, site visits, surveys, and interviews. This report draws on the voices of students, school leaders, Attendance Services, parents and whānau, and experts to understand chronic absence and its implications on the students in the long term.  

The Ministry provided data on attendance rates in schools, and attendance rates by different demographics and subgroups.   

The SIA provided analysis on the outcomes of students who were chronically absent, and those who were referred to Attendance Services. The SIA also provided data on the monetary cost associated with chronically absent students.  

Data that informed the evaluation  

The table below describes the data we used to inform each question.  

Ethics

All participants were informed of the purpose of the evaluation before they agreed to participate in an interview. Participants were informed that:   

• participation was voluntary and could be withdrawn at any time   

• their words may be included in reporting, but no identifying details would be shared   

• permission to use their information could be withdrawn at any time   

• interviews were not an evaluation of their school, and their school or provider would not be identified in the resulting national report   

• their information was confidential and would be kept securely subject to the provisions of the Official Information Act 1982, Privacy Act 1993, and the Public Records Act 2005 on the release and retention of information.   

Interviewees consented to take part in an interview via email, or by submitting a written consent form to ERO. Their verbal consent was also sought to record their online interviews. Participants were given opportunities to query the evaluation team if they needed further information about the consent process.  

Data collected from interviews, surveys, and administrative data will be stored digitally for a period of six months after the full completion of the evaluation. During this time, all data will be password-protected and have limited accessibility.  

Quality assurance

The data in this report was subjected to a rigorous internal review process for both quantitative and qualitative data, which was carried out at multiple stages across the evaluation process. External data provided by the Ministry and SIA was reviewed by them.  

5. The caveats for this report

Administrative attendance data  

Administrative attendance records are comprehensive. They contain information on the attendance of students who are enrolled at schools in Aotearoa New Zealand.   

The latest data on attendance used in this report is from Term 2, 2024.  

Surveys  

The surveys were focused on students who have been chronically absent and their parents and whānau. Responses are representative of chronically absent Māori and Pacific students, but are over representative of chronically absent Pākehā students (respondents were able to select multiple ethnicities). To ensure robustness, the survey results are complemented with administrative data, including Integrated Data Infrastructure (IDI) analysis, to draw conclusions.   

Integrated Data Infrastructure   

Data from the IDI is comprehensive. It contains information on attendance of students who are enrolled in Aotearoa New Zealand schools from 2011 onwards. However, the voices of young people who are not enrolled in school or do not attend school regularly are difficult to access. While we have captured some of their voices, the majority of students in our sample either attend school some of the time or have been successfully returned to education.

IDI data disclaimers  

These results are not official statistics. They have been created for research purposes from the Integrated Data Infrastructure (IDI) which is carefully managed by Stats NZ. For more information about the IDI please visit: https://www.stats.govt.nz/integrated-data/.  

The results are based in part on tax data supplied by Inland Revenue to Stats NZ under the Tax Administration Act 1994 for statistical purposes. Any discussion of data limitations or weaknesses is in the context of using IDI for statistical purposes, and is not related to the data’s ability to support Inland Revenue’s core operational requirements.  

6. Terminology

What is chronic absence?  

There are four different categories of attendance, depending on how many half-days a student attends in a school term. These are set out below.   

• Regular attendance: attend 90 percent or more of a term (missing up to five days of a 10-week term).  

• Irregular absence: attend 80 to 90 percent of a term (missing five to 10 days of a 10-week term).  

• Moderate absence: attend 70 to 80 percent of a term (missing 10 to 15 days of a 10-week term).  

• Chronic absence: attend less than 70 percent of a term (missing 15 days or more of a 10-week term). This report focuses on this group of students.  

What counts as ‘going to school’?  

Students are present at school when they are in class. They are also considered present when they are:  

• late to class (but within school policy for lateness)  

• on the school site, doing things like:  
  - unsupervised study  
  - sitting an exam  
  - having an appointment at school (e.g., with a dean, sports coach, or nurse)  
  - waiting in the sickbay  
  - in-school isolation (e.g., removed to a different class or in the administration corridor)  
• away from school, but doing a school-based activity, like
  - a sports trip or cultural presentation
  - camp
• learning somewhere else, as agreed with the school, like: 
  - Alternative Education, Secondary Tertiary Programme (including Trades Academies), or Activity Centre
  - Teen Parent Unit, Health Camp, or Regional Health School  
  - a course or work experience  
• at a medical or dental appointment, or attending to Justice Court proceedings.  

Different types of absences  

Table 1: Justified and unjustified absences  

Abbreviations  

• IDI: The Integrated Data Infrastructure is a large research database maintained by Stats NZ. It holds de-identified microdata about people and households.

• ERO: Education Review Office  

• The Ministry: Ministry of Education  

• SIA: Social Investment Agency  

• UE: Un-enrolled students  

• UA: Unjustified absence  

• N: Number of responses  

7. Report structure

This report has 10 chapters.  

• Chapter 1: Evaluation design  

• Chapter 2: Analytical tools – Data and Methodology  

• Chapter 3: How well attendance is going in Aotearoa New Zealand  

• Chapter 4: What is driving chronic absence from school  

• Chapter 5: The outcomes for students who are chronically absent  

• Chapter 6: How effective the Aotearoa New Zealand model is against that evidence  

• Chapter 7: How effective Attendance Services are  

• Chapter 8: How effective schools are at addressing chronic absence  

• Chapter 9: Our key findings and the areas for action to drive improvement in student attendance  

• Chapter 10: Limitations of this research  

Conclusion  

ERO was commissioned to look at students who are chronically absent and the effectiveness of Attendance Services in bringing those students back to school. We used a mixed-methods approach, drawing on a wide range of administrative data, site visits, surveys, and interviews.   

The next chapter describes the tools and analysis methods we used.  

This evaluation draws on a variety of data collected, using a mixed-methods approach to answer the evaluation questions. Sources of information include the Integrated Data Infrastructure, administrative data on attendance, analysis of chronically absent students, and survey responses from students, school leaders, Attendance Service staff, and parents and whānau.  

This chapter sets out information about the tools used to collect this data, and how we brought together the multiple sources of information to assess the quality of the system that works to reduce chronic student absence in Aotearoa New Zealand schools.  

This chapter describes our data collection methods, and the analytical techniques used in answering our evaluation questions presented in the previous chapter.  

This chapter sets out our:  

1. overview of the approach  
2. data collection methods  
3. analysis methods.  

1.Overview of the approach  

We used a mixed-methods approach to collect the data to draw our findings. To make sense of our findings and recommendations, we drew on the knowledge of subject matter experts.  

a) Mixed-methods approach to data collection  

ERO used a mixed-methods approach, drawing on a wide range of administrative data, site visits, surveys, and interviews. This report draws on the voices of students, school leaders, Attendance Services, parents and whānau, and experts to understand chronic absence and its implications on the students in long term.  

Our mixed-methods approach integrated quantitative data (IDI, administrative data, and surveys) and qualitative data (surveys, focus groups, and interviews) - triangulating the evidence across these different data sources. We used the triangulation process to test and refine our findings statements, allowing the weight of this collective data to form the conclusions. The rigour of the data and validity of these findings were further tested through iterative sense-making sessions with key stakeholders.  

To ensure breadth in providing judgement on the key evaluation questions we used:  

To ensure depth in understanding of what works and what needs to improve we used:   

b) Sense-making through expert group discussions  

Following analysis of the administrative data, surveys, and interviews, we conducted sense-making discussions to test interpretation of the results, findings, and areas for action with:   

• ERO specialists in reviewing school practice   

• the project’s Expert Advisory Group, made up of sector experts   

• the project’s Steering Group, made up of ERO, the Ministry, and SIA representatives.   

All three groups included Māori representation.  

We then tested and refined the findings and lessons with the following groups to ensure they were useful and practical.  

• Representatives from the Ministry and Social Investment Agency  

• The project Steering Group  

2. Data collection methods  

We used data from existing and new data sources including:  

• IDI  

• surveys  

• administrative attendance data  

• interviews and focus groups  

• international literature.   

a) Use of Integrated Data Infrastructure 

We worked with the SIA on this report. The SIA used the data in IDI to analyse:  

• characteristics, predictors, and drivers of students who were chronically absent in 2019  

• longer-term outcomes of students who are referred to the Attendance Service, compared to a group of similar students  

• longer-term outcomes for a group of students with low attendance  

• longer-term costs to the Government of students with low attendance.  

b. Surveys   

For the evaluation of the Attendance Service system, we administered surveys of:  

• school leaders  

• Attendance Service staff  

• students who are chronically absent or have a history of chronic absence  

• parents and whānau of chronically absent students.  

Survey links for school leaders, students, and parents and whānau, were sent via email to schools to distribute. Survey links for Attendance Service staff, students, and parents and whānau were sent via email to Attendance Service providers to distribute.  

Surveys were in the field from mid-June to early August 2024. All surveys were carried out using SurveyMonkey. The parent and whānau survey (with minor adaptions) was also distributed through Dynata.  

Full surveys can be found in the appendices (Appendix 2).  

Table 2: Sample size  

Number of usable, complete responses received and used in our analysis. 

Student surveys  

Participants were selected if they were chronically absent or had a history of chronic absence.  

Links were sent in two tranches.   

• Tranche 1: sent to 500 state schools across all regions – 150 secondary and composite, and 350 primary and intermediate. Sent to all Attendance Services.  

• Tranche 2: sent to 300 additional schools to ensure there was good representation across characteristics (e.g., size, type, location etc.).   

ERO also shared the survey links with the Ministry to share on their networks and through regional hubs, Te Aho o te Kura Pounamu (formerly The Correspondence School), alternative education providers, and other student support organisations. Participants who completed the parent and whānau survey were also invited to pass the survey link on to their children if they had not already completed one.  

Attendance Services surveys  

Participants for the Attendance Services survey are:   

• staff who worked at Attendance Services (including advisors and officers)  

• leaders/managers of Attendance Services.  

School leader surveys  

Participants were selected on the following criteria:   

• school leaders and/or staff who dealt with attendance, in schools who had made at least one referral to their Attendance Service (Tranche 1)  

• school leaders and/or staff in schools who dealt with attendance, who may or may not have referred students to their Attendance Service (Tranche 2).  

We sent links to schools in two tranches.  

• Tranche 1: sent to 500 state schools across all regions – 150 secondary and composite, and 350 primary and intermediate.  

• Tranche 2: sent to 300 additional schools to ensure there was good representation across characteristics (e.g., size, type, location etc.).  

ERO sent information and survey links to schools via email. After one week, ERO identified schools with no responses and re-engaged these schools via email.  

Parent and whānau survey   

Participants were selected if their child was currently chronically absent or had a history of chronic absence.  

ERO sent links to 800 schools and all Attendance Services for them to share with parents and whānau of chronically absent students who they had been working with to increase their attendance.  

c) Administrative attendance records data 

The Ministry publishes data on student attendance on their website (Education Counts).2 In this report, we used the latest available data from Term 2, 2024. We analysed attendance patterns and trends of chronic absence from 2011 to 2024. A snapshot of this data can be found in Appendix 1. More detail can be found on the Ministry’s Education Counts website.  

d) Site visits, interviews, and focus groups 

The interviews and focus groups were conducted for students, school leaders, Attendance Service providers, and parents and whānau from April to May 2024. Most interviews were conducted during site visits. Some interviews were conducted online to better suit participants.  

All interviews were carried out by members of the project team, which included evaluation partners who work directly with schools. Interviews were semi-structured, developed from domains and indicators developed from international and national literature, and refined through discussions with experts. Most interviews had two project team members. We conducted interviews with:  

• twenty-one chronically absent young people who were nominated by schools and Attendance Services  

• twenty-six parents and whānau who were nominated by schools and Attendance Services  

• seventy-seven Attendance Service staff.  

Site visits  

We visited 28 schools and 19 Attendance Services, most of whom were selected in partnership with the Ministry from a list of 20 Attendance Services and 84 schools who had made a referral to Attendance Services in each region.  

We made clear in all communication that:   

• participation was voluntary   

• consent is sought and anonymity is assured   

• interviews and focus groups with students were undertaken with their agreement and parental consent (if under 16 years)   

• interviews/focus groups could happen either online, over the phone, or in person.  

e) International literature 

We drew on international evidence to understand if the increasing trend in chronic absence is a global phenomenon, after Covid-19. International evidence has also been key in accessing how different other countries address chronic absence in schools, interventions, practices, and systems they have in place to support schools and students to attain high level of attendance.  

Key sources of information were from research centres focused on attendance (e.g., Attendance Works, United States of America), and Department of Education resources in New South Wales, Australia, and the United Kingdom.   

We also used meta-analyses and reviews of attendance research (e.g., Education Endowment Fund) to develop an understanding of trends, effectiveness of approaches, interventions, and practices.  

3. Analysis methods  

This chapter sets out how we analysed the data from:  

• the IDI  

• surveys  

• administrative attendance data  

• interviews and focus groups  

• international literature.   

a) Integrated Data Infrastructure Data analysis 

We worked with the SIA to determine:  

• the characteristics, predictors, and drivers of students who were chronically absent in 2019  

• the longer-term outcomes of students who are referred to the Attendance Service, compared to a group of similar students   

• longer-term outcomes for a group of students with low attendance  

• longer-term costs to the Government of students with low attendance.  

The characteristics, predictors, and the drivers of chronically absent students  

The analysis looks at the characteristics of students who were chronically absent in Term 2, 2019. The sample included students who had attendance data in both Term 2 2018 and Term 2 2019, and were of compulsory school age (aged 5-15) in 2019. 

Characteristics

The characteristics considered in the analysis include:   

• whether student had chronic absence in 2018 

• student has a record of recent offending of any crime in 2019  

• student has a record of being a victim of crime in 2019  

• mother/father (measured separately) having custodial or community sentences in 2019student living in social or emergency housing in 2019  

• student received mental health and addiction services in 2019  

• mother/father (measured separately) received mental health and addiction services in 2019 

• student had a diagnosis of Intellectual Disability, Autism Spectrum Disorder, or had evidence (not necessarily diagnosis) of functional impairment 

• mother’s highest qualification as of 2019 

• student was admitted to the emergency department in 2019  

• student had a record of participating in early childhood education in the past 

• student was subject of an Oranga Tamariki investigation in 2019  

• equivalised income in the household of the student in 2019 

• size of the student’s household in 2019 

• NZ Deprivation Index associated with the student’s address in 2019. 

• The modelling also adjusted for demographic characteristics (gender, ethnicity and whether the student lived in Auckland). 

Regression  

Logistic regression analyses were used to statistically compare which characteristics are more likely for students with chronic absence, after adjusting for the effects of the other characteristics. 

The snapshot of chronically absent students in 2019 in the sample is as shown in Table 3.  

Table 3: Number and percentage of students by attendance categories in 2019  

Note that students who did not have attendance records in 2018 and a small number of students who could not be matched to the IDI were not included in this analysis. This means these numbers will differ from the statistics officially reported by the Ministry of Education. 

For all tests, results were treated as significant if the p-value was equal to or less than 0.05. All results presented in the report are unweighted.  

The regression outputs are in Appendix 3.  

The findings from this analysis can be found in Chapter 4.  

The outcomes for students with chronic absence  

SIA analysed IDI data to identify students with chronic absence in Term 2 2019, born between 1990 and 2015. All students with attendance rates of 70 percent or less, irrespective of their enrollment status, are classified as chronically absent in this analysis. The analysis looks at the outcomes of chronically absent students in 2022.  

Longer-term outcomes of students who are referred to the Attendance Service 

SIA looked at the population of people born between 1990 and 2015, and identified which of these people ever had a record of being referred to the Attendance Service (for chronic absence), and were aged 17 or older in 2022. These referred students were then paired with a comparison group (using Propensity Score Matching – more detail below) of otherwise similar students. Outcomes of both groups were then analysed, up to age 25.  

The findings from this analysis can be found in Chapter 7. 

Outcomes  

In this report, the outcomes are reported by age. The following outcomes were included for each age: 

• education (highest school attainment)  

• employment (whether IR recorded wage or salary income for the person) 

• income (total income, including benefit income, recorded by IR) 

• Government benefits received (whether IR recorded government benefit income) 

• living in emergency housing (any spell during the year) 

• rates of offending (Police proceeding in year) 

• victims of a crime (reported victimisation to Police) 

• corrections outcomes (any community or custodial sentence served during the year).  

The analysis compares outcomes for chronically absent students and the total population for 17- to 25-year-olds. For example, we compared the proportion of 20-year-olds who were chronically absent who attained University Entrance to the proportion of 20-year-olds in the total population who attained University Entrance in 2022. The attendance data was not collected prior to 2011, therefore SIA could only follow young adults with a history of chronic absence through to age 25.  

Comparison group and matching process 

To carry out a comparative outcome analysis of chronically absent students who are not referred to the Attendance Services, SIA identified a comparative group using propensity score matching. The comparative group had similar circumstances and characteristics as chronically absent young people, but have never been referred to Attendance Services (see Appendix 4).   

In total, 98 variables were used for matching, including age, ethnicity, stand-downs and suspensions, interactions with Oranga Tamariki and Youth Justice, and prior attendance history (see Appendix 4 for the full list of matching variables). The matching method was 1:1 nearest neighbour matching with replacement, using calipers for the overall propensity score as well as for justified and unjustified absence history. Referred students were exact matched on birth year and age and year of referral. 

The matching process resulted in some referred students (for whom there was not a suitable non-referred counterpart) being dropped from the sample. Of the 62,154 students in the sample that were referred to the Attendance Service for chronic absence, 47,769 were included in the analysis. SIA undertook statistical tests comparing outcomes between the groups. All differences discussed in the report were statistically significant at the 5% level of significance. 

To ensure robustness in our conclusions, SIA also performed the same comparisons (between outcomes across the referred students and their matched comparison groups) for subsets of students of different genders, ethnicities, school deciles, referral ages, prior attendance, and of students attending different providers. There was no subset for which the Attendance Service group had detectably better outcomes than their matched comparison group (see figure 4C in Appendix 4). 

There were a few unobserved factors which we could not control for in our analysis (e.g., bullying).   

Longer-term outcomes for students with low attendance  

For this analysis, SIA grouped the students who were referred to the Attendance Service due to chronic absence with the comparison group of students who were matched to these students. See the description of the previous analysis for more information on the sample used. These two groups combined are likely to represent a subset of the students who are chronically absent in any particular year.  

Outcomes for this combined group of students with low attendance were compared with outcomes for the whole student population (matched using birth year but otherwise not adjusted for any other characteristic). No statistical tests were performed in this analysis. 

The outcomes described in this section are the same as the outcomes used in the Attendance Service analysis.  

The findings from this analysis can be found in Chapter 4.  

Costs to the Government for students with chronic absence   

Using the same cohort as the previous analysis (the students who were referred to the Attendance Service due to chronic absence, combined with their counterparts in the matched comparison group), SIA examined the costs incurred through a subset of government services. Because cost data tends to be lagged in the IDI, this analysis tracked students from age 17 to age 23 (instead of age 25 as in the previous analysis).  

The total Government expenditure includes expenditure on Ministry of Social Development benefits, costs associated with corrections (custodial and community sentences), public hospital admissions, pharmaceuticals costs, and disability support services expenses. The average Government expenditure was calculated for students with chronic absence by age, for 17- to 23-year-olds.  

For comparison with the total population, average Government expenditure was calculated for all students by age 17 to 23 in 2022. The results from the analysis are discussed in Chapter 4: What are the outcomes for chronically absent students? in the section: What is the cost of these outcomes?.

b) Survey analysis  

Surveys were given to students who were currently chronically absent and who had a history of chronic absence. The student dataset was used to identify the key reasons why students who are chronically absent miss school. We also used it to understand how students worked with schools and attendance services.  Open ended questions were reviewed to see if there were reasons for chronic absence not included in the short answer questions.   

Students  

From the surveys we identified students who were chronically absent the week before.  We used the two groups of students – those who were chronically absent last week and those with a history of chronic absence to look at the key drivers of the students who are currently chronically absent.  We reported on the reasons for absence for the students who are currently chronically absent. To ensure our findings reflected current, rather than historical issues.  

Parents  

Like the students, surveys were given to parents of students who were currently chronically absent and who had a history of chronic absence.  The parents dataset was used to identify the key reasons why their child misses school. We also used it to understand how parents worked with schools and attendance services.  Open ended questions were reviewed to see if there were reasons for chronic absence not included in the short answer questions.   

From the surveys we identified parents of students who were chronically absent the week before. We reported on the reasons for absence for the parents whose students who are currently chronically absent to ensure our findings reflect current, rather than historic issues.  

The survey questions were designed to understand:  

• why students are absent   

• how effective the supports and interventions are for chronically absent students at getting them back to school and keeping them in school  

• which model is more effective  

• what needs to change so that the supports and interventions for chronically absent students achieve better results while being cost-effective.  

Three analytical techniques were employed to analyse survey data:   

1. descriptive statistics  
2. regression analysis  
3. long answer analysis.  

The quantitative data from surveys presented in this report is largely descriptive, but two regression analyses were run which assessed:  

• what are the most likely reasons for the students to be chronically absent  

• how different practices in schools impact levels of chronic absence.  

Descriptive statistics  

We completed quantitative survey data analysis to identify the key drivers/reasons for chronic absence from the viewpoint of students, school leaders, Attendance Service staff, and parents and whānau. We grouped main drivers into three categories: school factors, family factors, and student factors. We have reported on the proportion of respondents who have identified reasons in those categories as the key drivers for chronic absence.   

Table 4: School factors   

Table 5: Family factors   

 Table 6: Student factors  

The findings from this analysis are discussed in Chapter 4: What is driving chronic absence?   

Regression analysis  

We ran two regression analyses looking at reasons chronically absent students do not attend school and effective approaches to reduce chronic absence.  

Regression: Reasons for chronic absence  

In the first regression analysis, we looked at the most likely reasons for chronically absent students not to attend school when we controlled for the impact of various demographic factors.   

Sample  

A logistic regression was run using survey data of 624 students.  

The outcome variable of interest was the student who had been away from school more than two days in the last two weeks of Term 2.  

There were 256 students who had been away for more than two days compared to 279 students who had been away for zero or one day. One hundred and fifty students were excluded from the regression analysis because they did not know or did not answer the question.  

Variables  

Predictor variables included in the model were:  

• demographics: gender, ethnicity, disability, and if they are in the care of Oranga Tamariki  

• school classification: whether they attended a primary or secondary school, the size of the school, Equity Index Score of schools, whether the school is in Auckland, the rest of the North Island, or the South Island, and the proportion of their school roll that has Māori or Pacific students  
• behaviour and attitudes related survey questions: what school supports the student feel helped them get to school, reasons why they have not gone to school this year, and how important they feel school is for their future  
• survey questions: the statements from the student survey on:
  - Question 34: “what has helped you go to school more”  
  - Questions 24-29: “so far this year you did not go to school because…”. 

The regression output can be found in appendix 3A.  

Regression: Effective practices to reduced chronic absence  

In the second regression analysis we looked at the key frameworks/approaches schools use to address chronic absence and the likelihood of those approaches to be successful in reducing chronic absence when we control for the impact of various demographic and socio-economic factors.  

Sample  

A logistic regression was run on the survey data of 255 school leaders.  

The outcome variable of interest was the schools with less than 5 percent of students chronically absent.  

In our sample, 142 schools had more than 5 percent of chronic absence and the remaining 113 schools had less than 5 percent of students chronically absent.   

Variables  

A number of predictor variables were included in the model.  

• School classification: Primary or secondary school, the size of the school, Equity Index Score of schools, the proportion of their school roll that had Māori or Pacific students, and isolation index.  

• Behaviour and attitudes related questions: How schools work with Attendance Services staff, how schools work with others to address attendance issues, the actions schools take to manage absence, the experience of schools with Attendance Services.  

• Survey questions: From the school leader survey, the following questions:  
  
  • Question 17: “How do you work with Attendance Services staff”  
  • Question 32: “How much you agree with the statements, thinking about how you work with others to address attendance issues….”  
  • Question 33: “How often the school staff do the actions below….”  
  • Question 38: “How much do you agree with the questions, thinking about the attendance environment and the staff working in it….”    
  • Question 39: “How often the staff working to support attendance do the actions below….”.
  
  
  

Detail on the regression can be found in appendix 3B.  

Long answer questions  

We used the open-ended responses from our surveys to understand the effectiveness of Attendance Services, and to find out which approaches are effective in successfully returning chronically absent students to school.   

The open-ended questions used in our surveys are outlined below.   

For students:   

• What has helped you go to school more?  

• What did teachers, school leaders and Attendance Service workers/officers do that got in the way of helping you attend school more? Why didn’t it help?  
• What would help you go to school more?

For parents and whānau:  

• What has helped your child go to school more?  

• What did not work well when working with school and Attendance Service staff to help your child go to school more?  

• What would help your child go to school more?  

For Attendance Service staff:  

• In your experience, what does work to increase attendance? Why do you think this does work?  

• In your experience, what does not work to increase attendance? Why do you think this does not work?  

• Do you have any more comments about student attendance/lack of attendance in NZ schools?  

For school leaders:  

• What has helped students come to school more?  

• In your experience, what does work to increase attendance? Why do you think this does work?  

• In your experience, what does not work to increase attendance? Why do you think this does not work?  

• Do you have any more comments about student attendance/lack of attendance in NZ schools?  

c) Administrative attendance data analysis 

The Ministry publishes data on attendance of students for each term (Education Counts). 3 In this report, the latest available data from Term 2, 2024 is used. We looked at attendance patterns and the trend of chronic absence from 2011. We used this data to analyse our evaluation question, “Who are the students who are chronically absent from school?”.   

We analysed demographic cuts like gender, ethnicities, region, year-level, and school type. We also used attendance data from the Ministry to look at the patterns of attendance by schools.  

The quantitative data presented in this report, using administrative attendance records, is largely descriptive statistics.   

d) Site visits, interviews, and focus groups analysis 

The interviews were guided using semi-structured questions that were developed from domains and indicators on good practice in schools and Attendance Services. Based on analysis of key documents and interviews with key staff, the evaluation team assessed the quality of provision against the domains set out in Chapter 6. This assessment led to a description of how the Attendance Service and school was performing on each domain and indicator. This helped the evaluation team identify examples of good practice and to understand what the key contributing factors were. Similarly, the team was able to identify examples of issues and challenges that Attendance Services and schools were facing and understand the main contributing factors.  

Questions we asked:  

For students:   

• Do you think coming to school is important?    

• What are some good things about coming to school?    

• What are some of the reasons you might not come to school?    

• What might help you attend school more often?   

• Talk to us through what happened when you did not attend school   

• What worked well?  What did not?  

For parents and whānau:  

• Please tell me a bit about yourself.   

• Do you think attending school is important?    

• What are some of the reasons your child might not come to school?   

• What could help your child attend school more often?   

• Talk to us through how your child got support when they did not attend school   

• What worked well?   

For school leaders and staff with attendance responsibilities:  

• Talk to us about what your role involves.    

• Tell us about attendance patterns or issues at your school.    

• How does your school deal with any attendance challenges?    

• Considering the last year, what would you say is the percentage of students who:   
  
  • returned to school?   
  • increased their attendance?   
  • stayed at school?   

• Have you accessed the Regional Response Fund (RRF)?    

• What could make a difference in helping you to address chronic absence?   

 For Attendance Services managers/leaders:  

• Talk to us about what your role involves .   

• Are there any patterns or trends in attendance across the cluster?   

• How do you work with students and their families? How do you work with schools?    

• Have you been involved with a project resourced from the Regional Response Fund (RRF)?    Considering the last year, what would you say is the percentage of students who:   
  
  • returned to school?   
  • increased their attendance?   
  • stayed at school?    
• What could make a difference in helping you to address chronic absence?   

Analysis  

Data was analysed in two main ways.  

1. A semi-inductive approach was initially taken, whereby the interviewer notation was coded into previously established themes, which were organised within the key evaluation questions. Cross-interview themes were established during workshops comprising the qualitative analysis team.  
2. Following substantive analysis of both the qualitative and quantitative data, a deductive approach was taken to establish exemplars that illustrated those analyses with real-world experiences.  

The research team held workshops to discuss the survey data and the interview results to identify cross-cutting themes. This also ensured that members of the research team were analysing and interpreting the data consistently, and additional investigation could be undertaken to address gaps or inconsistencies.  

We used information from interviews and focus groups to answer our evaluation questions:   

• Why are students absent?  

• How effective are the supports and interventions for students who are chronically absent at getting students back into school and keeping them in school?  

• Are different models more or less effective?  

• What needs to change so that the supports and interventions for students who are chronically absent from school achieve better results and are cost-effective?  

All quotes were gathered from verbatim records and open-ended survey responses.  

Conclusion  

This evaluation developed numerous data collection tools and methods of analysis to answer key evaluation questions about chronically absent students and the system of support available to them.   

In the next chapter, we describe how we looked at the extent of the problem of chronic absence in Aotearoa New Zealand.  

Aotearoa New Zealand is experiencing a crisis of chronic absence. Chronic absence has doubled since 2015 and is now at 10 percent. This means one in 10 students are missing three weeks or more a term.  

In this chapter, we set out how we analysed how many students are attending school, and how chronic absence varies for different students and schools.  

What we did   

We used administrative data to understand how big the problem of chronic absence is, and who the students who are chronically absent are.  

In this chapter, we use the administrative attendance records of students available publicly on the Ministry’s Education Counts website. This chapter reports on the prevalence of chronic attendance by different schools, using customised data provided by the Ministry. The latest statistics on attendance reported in this chapter are from Term 2, 2024.   

Data sources used in this chapter  

In this chapter, we use the administrative attendance records of students available publicly on Ministry’s Education Counts website. This chapter reports on the prevalence of chronic absence by different schools, using customised data provided by MOE. The latest statistics on attendance reported in this chapter are from Term 2, 2024

This chapter sets out what we found out about:  

1. how many students are not attending school  
2. how chronic absence is different for different students  
3. how attendance varies by school.   

What we found: an overview  

Chronic absence has doubled since 2015.  

One in 10 students (10 percent, N = 80,569 students) were chronically absent in Term 2, 2024. In Term 2 last year, over 80,000 students are attending school less than 70 percent of the term.  

Senior secondary school students are most likely to be chronically absent.  

Nearly one in five (15 percent, N = 23,712 students) senior secondary school students (Years 11-13) were chronically absent in Term 2, 2024.  

Chronic absence rates are higher in low socio-economic areas.  

Students from schools in low socio-economic areas are six times as likely to be chronically absent (18 percent compared to 3 percent, N = 10,072 compared to 4,885 students).

1. How many students are chronically absent from school? 

Source: Ministry of Education, attendance data  

Chronic absence is currently at 10 percent.  

In Term 2 this year (2024), 80,569 students (10 percent of all students) were recorded as chronically absent, missing more than three weeks of a school term.   

Figure 1: Percentage of students by the proportion of absence in Term 2 2024  

Data Source: Ministry of Education  

Chronic absence is on the rise and has doubled since 2015.  

Five percent of students (N = 29,355 students) were chronically absent in Term 2 in 2015. Chronic absence started to increase in 2016, and in Term 2 2024, 10 percent of students (N = 80,569 students) were chronically absent. 

Figure 2: Percentage of chronic absence in 2015 and 2024 Term 2  

Data Source: Ministry of Education 

2. How is chronic absence different for different students? 

Source: Ministry of Education, attendance data  

Most chronically absent students are away for three weeks in a term, but some miss a whole term.  

In Term 2 of 2024, just under half of chronically absent students were away for four weeks. But there were over 1 percent of chronically absent students (N = 2,234 students) who missed the whole term (nine or more weeks).

Māori and Pacific students are more at risk of chronic absence.  

In Term 2 of 2024, 18 percent of Māori students (N = 34,973 students) and 17 percent of Pacific students (N = 18,453 students) were chronically absent. This is compared to 8 percent of NZ European/Pākehā students (N = 36,272 students) and 6 percent of Asian students (N = 9,167 students).4 Concerningly, the gap in the rate of chronic absence between NZ European/Pākehā students and Māori and Pacific students has increased from pre-Covid-19 levels. The gap for Māori students has increased from 8 percentage points in 2019 to 10 percentage points in 2024. Whereas for Pacific students, the gap has increased from 7 percentage points in 2019 to 9 percentage points in 2024. (In 2019: Māori 13 percent, Pacific 12 percent, and NZ European/Pākehā 5 percent. In 2024: Māori 18 percent, Pacific 17 percent, and NZ European/Pākehā 8 percent).  

Figure 3: Percentage of chronically absent students by ethnicity in Term 2 2024  

 Data Source: Ministry of Education  

There is no difference in chronic absence for gender.   

Boys and girls are equally likely to be chronically absent. In Term 2 of 2024, 10 percent of both girls (N = 39,703 students) and boys (N = 40,682 students) had chronic absence.  

Chronic absence rates are higher for older students.  

Chronic absence is a problem in both primary and secondary school. Senior secondary school students have higher rates of chronic absence compared to primary school students. In primary school (Years 1-8) chronic absence is 10 percent (N = 40,297), in secondary school (Years 9-10) it is 13 percent (N = 16,538), and in senior secondary school (Years 11-13) it is 15 percent (N = 23,712).   

Figure 4: Chronic absence rates across different year levels in Term 2 2024  

Data Source: Ministry of Education 

3. How is chronic absence different for different schools? 

Source: Ministry of Education, attendance data  

More students are becoming chronically absent at younger ages.  

Chronic absence rates have doubled in secondary schools and nearly tripled in primary schools since 2015. Rates of chronic absence in secondary schools started to increase in 2015. In primary schools, rates of chronic absence started to increase in 2016. Chronic absence rates have improved since the peak of the pandemic (2022), but they remain higher than before the pandemic.  

Figure 5: Rates of chronic absence in primary and secondary schools   

Data Source: Ministry of Education  

Source: SIA, IDI data analysis - regression  

Attendance in primary school matters. Students who do not have a history of regular attendance are more likely to continue being chronically absent.  

We found from our analysis that, for students who have a history of regular attendance, their likelihood of attending school regularly increases by 221 percent. ERO’s previous work also tells us that there is a greater impact on learning the more days of school students miss. Having healthy attendance patterns in primary school helps students maintain attendance habits in secondary school.

Source: Ministry of Education, attendance data  

Chronic absence rates are higher in schools in low socio-economic communities, and in the Northland Te Tai Tokerau region.  

Students from schools in low socio-economic communities5 are six times as likely to be chronically absent from school (18 percent, N=10,072) than students in schools in high socio-economic communities (3 percent, N=4,885).  

Figure 6: Percentage of chronic absence by schools in socio-economic areas in 2024 Term 2   

Data Source: Ministry of Education  

Despite absence rates being higher in schools in low socio-economic areas, there are schools in low socio-economic communities that have low chronic absence rates and schools in high socio-economic communities that have high chronic absence rates (more about this can be found in Chapter 8).  

Regionally, Northland | Te Tai Tokerau (15 percent, N=4,663) and Southwest Auckland | Tāmaki Herenga Waka South (15 percent, N=11,924) has the highest percentage of chronically absent students in Aotearoa New Zealand, followed by Hawkes Bay | Tairāwhiti (N=4,602), Waikato (N=8,620) and Bay of Plenty | Waiariki (N=7,286) (12 percent).

Figure 7: Percentage of chronic absence by regions in Term 2 2024  

 Data Source: Ministry of Education  

Conclusion  

Chronic absence in Aotearoa New Zealand has reached crisis levels, doubling since 2015. over 80,000 students (10 percent) were chronically absent in Term 2, 2024. This has serious impacts for students. Senior secondary school students, Māori students, Pacific students, and students in schools in low socio-economic areas are at a greater risk of chronic absence.   

The next chapter looks at how we assessed drivers for students’ absence from school, and the reasons for Aotearoa New Zealand’s high rates of chronic absence.  

Improving school attendance is crucial to raising educational outcomes for students across Aotearoa New Zealand. To address this, we first need to have a detailed understanding of the reasons behind chronic absence.   

In this chapter, we set out how we analysed the risk factors for chronic absence, then explore students’ reasons for chronic absence.  

What we did  

1. Understanding the reasons behind chronic absence can help us reduce it. We wanted to understand the role student, family, and school, factors play in chronic absence. To understand the biggest predictors of chronic absence we used statistical modelling to identify the risk factors for students being chronically absent.  

This chapter sets out:  

1. the key predictive risk factors for chronic absence  
2. the main reasons for chronic absence.  

What we found: an overview  

There are a range of risk factors that make it more likely a student will be chronically absent. The most predictive factors are previous poor attendance, offending, and being in social or emergency housing.  

Twenty-five percent of students who are chronically absent were chronically absent a year ago (N = 10,494).  Four percent of students who are chronically absent have a recent history of offending (compared to less than 1 percent of all students). Just over one in 10 (12 percent, N = 5,532 students) of chronically absent students live in social housing, compared to 3 percent of all students (N = 12,123 students).  

Students’ attitudes to school and challenges they face are drivers of chronic absence. Wanting to leave school, physical health issues, finding it hard to get up in the morning, and mental health issues, are key drivers.  

Nearly a quarter of students who are chronically absent report wanting to leave school as a reason for being chronically absent. Over half (55 percent, N = 142) identified mental health and a quarter (27 percent, N = 69) identified physical health as reasons for being chronically absent.  

Our findings are set out in more detail below. 

1. What are the predictive risk factors for chronic absence? 

To investigate the key predictive socio-economic risk factors for chronic absence, SIA used data from IDI. They looked at the prevalence of low socio-economic factors in students with chronic absence and with regular absence, in 2019.  

 The socio-economic factors considered are: 

• offending 

• social and emergency housing 

• mental health and addiction 

• emergency department admissions 

• attendance history 

• victim of crime 

• Oranga Tamariki investigation.   

SIA also ran regression analysis to find out the likelihood of socio-economic factors in chronically absent students when we control for demographic factors like, ethnicity, gender, and region. This time-period was chosen as it was latest available period unaffected by impacts of Covid-19 related lockdowns. The details on the data and methodology is explained in chapter 2.

This chapter sets out what predictive risk factors are associated with chronic absence. We categorise these into:  

• community factors  

• family factors  

• student factors.  

The predictive risk factors for chronic absence are set out in the table below. 

Community factors  

Source: SIA, IDI data analysis  

Students from lower socio-economic communities are more likely to be chronically absent.  

We saw in Chapter 3 that students from schools in low socio-economic communities are six times more likely to be chronically absent than students from schools in high socio-economic communities.  After controlling for family factors and student factors, students living in low socio-economic communities are still 1.8 times more likely to be chronically absent.   

Source: ERO site visits, interviews, and focus groups and surveys  

Community factors that impact attendance are wide ranging and include geographic remoteness, access to transport, and community responsibilities. Parents of students who have a history of chronic absence told us that the availability of affordable transport was often a barrier to attendance.  

We heard that getting children back to school was more difficult in areas hit by natural events such as flooding. Attendance Service providers told us about roads being washed out making getting to school difficult. Parents and students who have experienced trauma related to natural disasters are anxious about being able to contact or reach each other during an event and were reluctant to be separated in case this happened again.

Family factors  

Source: SIA, IDI data analysis - regression  

Students experiencing unstable housing and complex family lives are more likely to be chronically absent.  

The family factors that are most predictive of chronic absence are living in social housing (1.4 times more likely to be chronically absent) and living in emergency housing (1.5 times more likely to be chronically absent). Other predictive family factors are linked to family dysfunction or conflict, including parental drug and alcohol addiction (1.1 times more likely to be chronically absent) and involvement of Oranga Tamariki (1.3 times more likely to be chronically absent).   

Source: ERO site visits, interviews, focus groups and surveys  

We heard how complex home lives, where families are struggling with drug and alcohol addiction or other mental health needs, means school attendance is not prioritised. Some parents discussed being victims of domestic violence, and how it made it difficult to prioritise their children going to school.  

In many of these families there is an inter-generational disengagement from school – where parents did not go themselves, and their children do not go to school now. 

“Non-attendance at school is a symptom of complex family challenges, often including significant trauma which may be long-term and inter-generational.” (Attendance Service provider)  

We also heard how financial hardship can cause chronic absence. Parents and students told us that students having to look after younger children while parents work and a lack of school supplies, including uniforms, contributed to chronic absence. Attendance Service staff and schools told us that transience and poor housing conditions both lead to increased absence from school.  

Student factors  

Source: SIA, IDI data analysis - regression  

Students with histories of offending and a history of chronic absence are most likely to be chronically absent.   

The student factors that are most predictive of chronic absence are being a recent offender (4.2 times more likely to be chronically absent) and having a recent history of chronic absence (five times more likely to be chronically absent). Accessing mental health services and hospital emergency admissions, which are indicators of mental health and physical health issues, are also predictive of chronic absence (1.8 and 1.5 times more likely to be chronically absent).

Source: ERO site visits, and interviews and focus groups  

Building and maintaining a habit of attendance can protect against becoming chronically absent, but periods of chronic absence can lead to further chronic absence. We heard from our interviews that the more students miss school, the harder it is for them to return – creating a cycle of increased chronic absence.  

Parents and students also told us that there were mental and physical health reasons for students not regularly attending, particularly anxiety and persistent winter illnesses.  

2. What are the main reasons students report for current chronic absence? 

Source: ERO site visits, interviews / focus groups and survey data analysis   

We asked students, their parents and whānau, school leaders, and Attendance Services, about what kept students from attending school in the last year. This chapter sets out what the main drivers of chronic absence are from students’ perspectives. We categorise these drivers into:  

• school factors – challenges with the school  

• family factors – challenges with the family circumstances, or parenting  

• student factors – challenges with individual health.  

Together, these challenges can create real barriers to students going to school every day. Many students who are chronically absent are struggling with other issues in their lives.   

Source: ERO student survey logistic regression analysis  

To understand the main drivers / reasons of chronic absence we analysed our survey data. We analysed the proportions of responses mentioning school, family, and student related factors as a reason for the chronic absence. We ran logistic regression analysis to identify the most likely reason for students to be chronically absent after controlling for other demographic factors that has an association with the rate of attendance like gender and ethnicity. The detail on the regression can be found in chapter 2.  

School factors  

Source: ERO survey data analysis   

Students who feel isolated or not supported by their school are more likely to be chronically absent.  

The school factors most likely to be identified by chronically absent students are:  

• not getting enough support for what they need at school (42 percent of students, N = 108)  

• not feeling like they belong (35 percent of students, N = 89)  

• not wanting to do some school activities (34 percent of students, N = 86).   

 Source: ERO student survey logistic regression analysis  

As per the logit regression run on data from student survey, students who want to leave school are 3.2 times more likely to have a recent history of chronic absence, compared to other chronically absent students.    

 Source: ERO survey data analysis   

Parents also rated students not wanting to do some school activities as one of the top three reasons students were not likely to go to school (30 percent of parents, N = 93). Attendance Service staff and school leaders did not identify school factors in their top three reasons for chronic absence.

Figure 8: School factors that students report as reasons for chronic absence   

Source: ERO site visits, interviews, focus groups and surveys  

In our interviews students were most likely to identify schooling factors as a barrier to attendance. They reported:  

• feeling socially isolated and having a lack of friends or poor relationships with teachers   

• having learning needs that the school is unable to accommodate – for example, parents also report restricting attendance of neurodiverse students to manage their triggers  

• feeling physically unsafe due to schools not addressing bullying  

• schools not offering courses of study that are relevant to their career goals.  

Parents also told us that bullying and poor relationships with teaching staff were factors in their child not attending school.  

“I was bullied and threatened at school the school didn’t respond in a way to keep me safe so had no choice but leave school.” (Student)  

“I couldn’t keep up or understand what they wanted me to do… But turned out I have ADHD and find it hard to focus in class.” (Student)  

“I'm unsettled when my friends or teacher aren't at school and I often come home during the day. I get bored. Sometimes I prefer to do what I like and am good at instead of what I don't like and struggle with.” (Student)  

“[I want to learn] more life skills and stuff we need as adults and less irrelevant stuff.” (Student)  

Family factors   

Source: ERO survey data analysis   

Chronically absent students report a wide range of family factors that impacted on their attendance, staying up late was the most common issue.  

Two out of five students (41 percent of students, N = N = 105) reported finding it hard to get up in the morning as a reason they do not attend, which make students 1.8 times (odds ratio from regression) more likely to be chronically absent. Attendance Service staff (90 percent, N =124) and school leaders (75 percent, N= 180) agreed, both rating finding it hard to get up in the morning after staying up late as one of the top three reasons why students are chronically absent from school. Attendance providers also identified moving between family homes in their top three (85 percent, N = 117).  

Figure 9: Family factors that students report as reasons for chronic absence   

Source: ERO site visits, interviews, focus groups and surveys  

We heard that students are late getting to school, or stay at home due to a:  

• lack of organisation in the household  

• lack of vigilance over bedtime routines which meant students engage in late night activities and don’t have sufficient sleep.   

In our interviews, students were most likely to tell us about financial barriers to school attendance, and particularly the cost of transport and uniforms. We heard that some students need to help out their family with caregiving when parents can’t, or work at after-school jobs to contribute to family expenses, and are unable to attend school the next morning.  

“[I go to school more] when I don’t have to help Mum look after the babies and Dad in the shearing shed.” (Student)  

“Sometimes we run out of uniform because it costs a lot of money, and I break it or it is in the washing machine. [The school] is now changing the uniform and [making], it cost more and my Mum says I can only have one of each clothing.” (Student)  

Attendance Service providers and school leaders told us that family factors were often a driver of poor school attendance, including parental anxiety about sending their child to school and distrust of the education system.   

“I watch my mum struggle every week to get us to school… I watch her have less… knowing it will come at an extra cost.” (Student)  

Student factors   

Source: ERO survey data analysis and logistics regression analysis of student survey   

Chronically absent students report their mental health as a key reason for their chronic absence.  

Across all factors, mental health was the top reason students were chronically absent (55 percent of students, N = 142). Students who have physical or mental health barriers are 2.4 and 1.7 times more likely to have a recent history of chronic absence (odds ratio from regression). This is consistent with the finding from the IDI that students who access mental health and addiction services are 1.8 times more likely to be chronically absent.  

Parents (33 percent, N = 103), Attendance Service staff (94 percent, N = 130), and school leaders (70 percent, N = 168) agreed - all report mental health in the top three reasons why students did not attend school.   

Figure 10: Student factors that students report as reasons for chronic absence   

Source: ERO site visits, interviews, focus groups and surveys  

In nearly all interviews, anxiety was discussed as a crucial driver for chronic absence. Students told us about being too anxious to leave their home to go to school.    

“I found it overwhelming as I have social anxiety.” (Student)  

Students, and parents and whānau report that long-term health conditions, as well as winter illness, led to chronic absence. For students with chronic conditions, the students didn’t have energy to sustain their attendance over a day or a week.  

“When you have multiple physical and mental health issues, it’s hard for people who haven’t experienced those things to really understand.” (Student)  

Conclusion  

School, parent and whānau, student, and community factors, all impact on students’ likelihood to be chronically absent. The most predictive risk factors are having a recent history of chronic absence, having recently offended, or living in social or emergency housing. The largest drivers of recently having been chronically absent are wanting to leave school, physical health, finding it hard to get up in the morning, and mental health. Addressing these key factors can reduce chronic absence. In the next chapter, we explain how we analysed the impacts of chronic absence on student outcomes.  

Attendance is critical for life outcomes. Students with chronic absence have worse outcomes. They are significantly more likely to leave school without qualifications, be charged with an offence, or live in emergency housing. Chronically absent students also cost more to the Government due to increased spending on benefits, corrections, and health services.  

This chapter describes how we analysed chronically absent young people’s long-term outcomes, compared to the wider Aotearoa New Zealand population.  

What we did   

To understand what the outcomes are for students who were chronically absent, we draw on:  

• SIA’s analysis of IDI data from 2019 onwards  

• interviews with chronically absent students, and their parents and whānau  
• interviews with school leaders and Attendance Service staff.  

This chapter looks at the outcomes for students who have been chronically absent or not enrolled in any school. It sets out:  

1. what their education outcomes are  
2. what their employment and income outcomes are  
3. what their housing outcomes are  
4. what their justice outcomes are  
5. what the cost is of these outcomes.  

The data does not control for other childhood and family factors which might be contributing to these poor outcomes.  

What we found: an overview  

Students who were chronically absent are significantly more likely to leave school without qualifications.   

At age 20, over half (55 percent) have not achieved NCEA Level 2, and almost all (92 percent) have not achieved University Entrance. This leads to having significantly lower rates of employment and income. At age 25, nearly half are not earning any wages or salary (42 percent).  

Young adults who were chronically absent are more likely to be charged with an offence or live in social or emergency housing. They are more likely to visit the emergency department.  

Reflecting their lower incomes, at age 25, 12 percent of young adults who were chronically absent are in social housing, compared to 4 percent of the total population. In the year they turned 25, 6 percent of young adults who were chronically absent had been charged with an offence, compared to 3 percent of the total population. They have 1.3 times more emergency admissions.  

Chronically absent young people cost the Government nearly three times as much.   

At age 23, young adults who were chronically absent cost $4,000 more than other young people. They are particularly costly in corrections, hospital admissions, and receiving benefits.  

Our findings are set out in more detail below. 

1. What are their education outcomes? 

Source: SIA, IDI data analysis  

We looked at three education outcomes:   

• NCEA Level 2  

• University Entrance  

• enrolment in tertiary education.  

At age 20, students who have been chronically absent are two times less likely to achieve NCEA Level 2 and five times less likely to achieve University Entrance than the general population.   

Attendance matters for education. Students who are chronically absent have consistently worse education outcomes.  

• NCEA Level 2 is the minimum pre-requisite for higher education and training, and many entry level jobs. At age 20, over half of students who have been chronically absent do not achieve NCEA Level 2 (55 percent), compared to just under one in five of the total population (19 percent).  

• Students who have been chronically absent are more than five times more likely to leave school without University Entrance. At age 20, 8 percent of students who have been chronically absent have University Entrance, compared to just over two in five of the total population (42 percent).  

• At age 20, young people who were chronically absent are less likely to be attending tertiary education (20 percent of chronically absent young people, compared to 42 percent of young people in the total population).  

Figure 11: Chronically absent young adults’ education outcomes at age 20, compared to the total population  

Data Source: Social Investment Agency  

Concerningly, students who are chronically absent from school often experience cumulative effects on their learning. The longer the period away from school, the greater the effort required to re-engage them, which leads to increased impact on learning progress and achievement.  

Source: ERO site visits, interviews, focus groups and surveys  

We heard from students, parents and whānau, schools, and Attendance Services, that periods of absence impacted their ability to keep track of and understand their learning and make progress in their learning.  

“They've had one or two days off and they feel like they can't catch up. They feel like they're behind already.” (Attendance Service)  

Students know that school is important for their future, but they do not always see the potential impact of their chronic absence. Students reported that what they learn will not help them for their future.   

“I don’t see the point in learning about things that I won’t use.” (Student)  

“The curriculum is irrelevant and the ideology won't help me with my future and career.” (Student)  

2. What are their income outcomes? 

Source: SIA, IDI data analysis   

We looked at three employment and income outcomes:   

• total income  

• income from wages  

• benefit receipt.  

At age 25, young adults who were chronically absent from school earn $40,000 less than what other 25-year-olds earn.   

Chronically absent young adults earn the same as the total population at 17 years old. However, over time their income becomes significantly less than the total population. At age 25, young adults who were chronically absent from school earn $16,667 compared to $59,235 for other 25-year-olds.  

Figure 12: Chronically absent young adults’ wages, compared to the total population  

Data Source: Social Investment Agency  

The lower income rates are because young people who were chronically absent are less likely to be earning wages and more likely to be receiving a benefit.  

Leaving school with fewer qualifications means young adults who were chronically absent at school are less likely to be employed. At age 25, just under three in five young adults who have been chronically absent from school have a wage or salary income (58 percent), compared to more than two-thirds of the total population (69 percent).   

Worryingly, from age 17 to 26, young adults who were chronically absent are more likely to be receiving a benefit. At age 25, almost half of young adults who were chronically absent are receiving a benefit (46 percent), compared to one in five of the total population (20 percent). From age 17 to 26, chronically absent young adults earn more income from benefits compared to the total population. At age 25, they receive $1,500 more in benefit than the total population.  

3. What are their housing outcomes? 

Source: SIA, IDI data analysis   

Young adults who have been chronically absent from school are three times more likely to live in social housing compared to the total population at age 25.  

From age 17 to 26, young adults who were chronically absent are more likely to be in social and emergency housing. At age 25, 12 percent of young adults who were chronically absent are in social housing, compared to 4 percent of the total population. Two percent are in emergency housing, compared to 1 percent of the total population.  

The higher rates of social housing and emergency housing of young adults who were chronically absent from school reflect housing affordability issues for people with lower incomes.  

Figure 13: Chronically absent young adults in social housing across ages, compared to the total population  

Data Source: Social Investment Agency  

4. What are their health outcomes? 

Source: SIA, IDI data analysis   

We looked at three health outcomes:  

• enrolment with a GP  

• visits to a GP  

• emergency admissions to hospital. 

Young adults who have been chronically absent from school are just as likely to visit a doctor but more likely to visit the emergency department  

Encouragingly, young adults who are chronically absent are just as like to be enrolled at, and visit, a GP as the total population.  At age 20:  

• eighty-eight percent of young adults who were chronically absent from school were enrolled in a GP compared to 83 percent of the total population  

• young adults who were chronically absent from school had 2.6 visits a year to their GP compared to 2.8 visits for the total population.  

However, young adults who have been chronically absent from school have 1.3 times more emergency admissions. In the year that they turned 20, young people who were chronically absent had 0.4 emergency admissions compared to 0.3 for the total population.  

5. What are their justice outcomes? 

Source: SIA, IDI data analysis   

We looked at three justice outcomes:  

• charged with an offence  

• custodial and community sentences  

• victim of an offence.  

Young adults who have been chronically absent from school are two times more likely to be charged with any offence.   

Young people who are chronically absent have consistently higher rates of offending, particularly violent offences. In the year they turned 25, just 6 percent of young adults who were chronically absent had been charged with an offence, compared to 3 percent of the total population. In the year they turned 25, 1 percent of young adults who were chronically absent had been charged with a violent offence, which occurs at double the rate in the total population (6 percent).  

The higher rates of offending likely reflect the higher rates of offending while still in school.  It also likely reflects the higher prevalence of family dysfunction when the young people were school aged.  

Young adults who have been chronically absent from school are three times more likely to be in the corrections system.   

The increased offending rates and increased violent offending rates mean that students with a history of chronic absence have higher rates of custodial and community sentences. Young adults who were chronically absent from school are significantly more likely to have:  

• served a community sentence - in the year they turned 25, 6 percent have served a community sentence, compared to 2 percent of the total population  

• served a custodial sentence - in the year they turned 25, 2 percent have served a custodial sentence, compared to 1 percent of the total population.   

Figure 14: Chronically absent young adults in the corrections system at age 25, compared to the total population  

Data Source: Social Investment Agency  

Young adults who have been chronically absent from school are nearly two times as likely to be a victim of any type of crime, and nearly three times more likely to be a victim of a violent crime.  

Sadly, significantly more young people who are chronically absent have been a victim of a crime. At age 25, 6 percent of young people who were chronically absent had been a victim of any crime, compared to 4 percent of the total population.  

Figure 15: Chronically absent young adults who have been victims of crime across ages, compared to the total population  

Data Source: Social Investment Agency  

They are also significantly more likely to be victims of violent crimes. At age 25, 4 percent of young people who were chronically absent had been a victim of a violent crime, compared to 2 percent of the total population. 

6. What is the cost of these outcomes? 

Source: SIA, IDI data analysis   

We know that being chronically absent has large individual costs in terms of income, health, and social outcomes. The poor social outcomes of young adults who were chronically absent from school also pose a sizeable cost to the Government.  

At age 20, young adults who were chronically absent cost the Government nearly three times as much as other 20-year-olds.   

The poor social outcomes of young adults who were chronically absent consistently cost more to the Government throughout their lives. At age 23, chronically absent young adults cost the Government $7,389 on average. This is about $4,000 more than other young people.  

Costs to the Government are much higher for chronically absent young people in corrections, hospital admissions, and benefits.  

Figure 16: Chronically absent young adults’ total expenditure per person per year, compared to the total population  

Data Source: Social Investment Agency  

Table 7: Comparison of the cost to the Government related to benefits, corrections, and hospital admissions for chronically absent students (20-year-olds)  

Conclusion  

The outcome of a lost education on students who have been chronically absent is clear. Students who were chronically absent have lower rates of educational attainment. This leads to lower incomes and higher rates of benefit receipt. Cycles of offending are not broken, and access to affordable housing is limited to what the state provides.   

The cost to the Government and Aotearoa New Zealand taxpayers is also high, with young adults who have been chronically absent costing nearly three times as much as other 20-year-olds. They are particularly costly in corrections, hospital admissions, and benefits. It is critical we reverse the trend of increasing absence.   

In the next chapter, we set out how we analysed how effective the Aotearoa New Zealand model is at supporting chronically absent students.  

ERO’s review has found weaknesses in each element of the education system intended to address chronic absence. Identification and action are too slow, and targeted support is not working well. Improvements are not sustained and funding for support is inadequate.  

This chapter sets out how we analysed each of the components of an effective response to chronic absence and ERO’s assessment of its effectiveness. 

What we did  

To understand how effective the model for attendance in Aotearoa New Zealand is, we compared the current practice against the indicators of effective practice.  

This chapter sets out:  

1. how effective the system is overall  

1. how effective each of the components are within the system.  

What we found: an overview  

Schools are setting expectations for attendance, but parents and whānau do not understand the implications of non-attendance.   

When students and parents and whānau do not understand the implications of absence, chronic absence rates increase from 7 percent to 9 percent.   

Action is too slow, and students fall through the gaps.   

Schools have tools in place to identify when students are chronically absent, but often wait too long to intervene. Only 43 percent (N = 132) of parents and whānau with a child who is chronically absent have met with school staff about their child’s attendance. One in five school leaders (18 percent, N = 33) only refer students after more than 21 days consecutive days absent. Just over two-thirds of Attendance Service staff report schools never, or only sometimes, refer students at the right time (68 percent, N = 86). Approximately half of schools do not make referrals to Attendance Services. 

Finding students who are not attending is inefficient and time consuming.   

There is inadequate information sharing between different agencies, schools, and Attendance Services. Attendance Services have to spend too much time trying to find students. Almost half of Attendance Services (52 percent, N = 65) report information is only sometimes, or never shared across agencies, schools, and Attendance Services.  

Schools and Attendance Services are planning responses to attendance barriers, but are not always identifying the correct barriers.  

Most school leaders and Attendance Service staff report they always plan how they work with students and parents and whānau using what they know about students and what works. However, there is a mismatch between what schools and Attendance Services identify, and what students and parents and whānau see as the barriers.  

Schools and Attendance Services are not well set up to enforce attendance.  

Just over half of school leaders (54 percent, N = 119) and just over three in five Attendance Service staff (62 percent, N = 67) do not think there are good options to enforce attendance and hold people accountable. Schools that have tried to prosecute have found the process complex and costly.  

Students are not set up to succeed on return to school.  

The quality of plans for returning students to school is variable, and students are not set up to succeed on return to school. While many schools welcome students back to school, there is not a sufficient focus on working with the students to help them ‘catch up’ and reintegrate.    

Improvements in school attendance are often short-lived as barriers remain. The education offered often does not meet students’ interests or needs, leading to them not sustaining attendance when they return to school.  

Although nearly four in five chronically absent students (79 percent, N = 203) finding learning a barrier to attendance, under half (44 percent, N = 105) of school leaders report they have changed schoolwork to better suit learners on their return. Over half of school leaders (59 percent, N = 129) and Attendance Services (58 percent, N = 63) report there are not opportunities for young people to learn in other settings.   

Accountability in the system is weak.  

There is a lack of clarity around where roles and responsibilities begin and end, and the accountability in the system is weak. Just over one in five school leaders (21 percent, N = 45) and two in five Attendance Service providers (40 percent, N = 47) want more clarity about the roles and responsibilities.  

Resourcing is inequitably distributed and does not match the level of need.  

Funding has not increased to match the increase in demand. Caseloads for advisers in the Attendance Services that ERO visited vary from 30 to more than 500 cases. Funding does not reflect need. Contracts vary in size (from around $20,000 to $1.4m) and in how much funding is allocated per eligible student – from $61 to $1,160 per eligible student Our findings are set out in more detail below.  

1.Overall, how effective is the system? 

ERO’s review found weakness in each element of the attendance system.   

The Aotearoa New Zealand system is not effectively tackling chronic truancy. The table summarises the ratings of each element of effectiveness.    

Table 8: Ratings of effectiveness for each element of the attendance systems  

2. How effective are each of the elements of the system? 

In this chapter, we describe each of the elements of the attendance system set out in Table 8 (above). For each, we look at what is and isn’t working well.  

a) Expectations for attendance 

What is working?  

Source: ERO site visits, interviews / focus groups and survey data analysis   

Schools are setting expectations for attendance.   

Nearly all school leaders (98 percent, N = 237) agree their school has clear and high expectations for attendance. Schools, parents and whānau, and students, told us that students are expected to attend school regularly. Parents and whānau receive frequent reminders from the school about the importance of attending school regularly.  

What doesn’t work?  

Source: ERO survey data analysis, site visits and interviews / focus groups  

Students and parents and whānau do not understand that reduced attendance is a key predictor of chronic absence.  

Rates of chronic absence are higher in schools where students and parents and whānau do not understand the implications of absence (7 percent in schools where students and parents and whānau do understand, 9 percent in schools where students and parents and whānau do not understand). Over one third of school leaders (33 percent, N = 80) report that parents do not understand the implications of not attending school.   

“[Parents] don't understand the long-term consequences for tamariki who do not attend school regularly, and how this can impact negatively on their job prospects, the type of jobs, high paying versus low paying.” (Attendance Service staff)  

Schools’ time is spent with parents and whānau focusing on whether an absence is justified or not, and less on whether the amount of absence is impacting students’ education.  

Attendance related activity and discussions do not always focus on whether a student’s absence is contributing to a pattern of chronic non-attendance and the impact that it is having on their education. Schools spoke to us about how much of their time is spent talking to parents and whānau about why an absence was classified as ‘unjustified’.  

Parents and whānau talked to us about confusion over their school’s expectations for attendance or how to manage sickness, anxiety, or when there is limited teacher aide support for students with high needs. There is also a lack of clarity between schools and parents and whānau about whether students who work from home through digital portals are meeting attendance expectations.  

b) Identifying students with poor attendance 

What is working?  

Source: ERO site visits, interviews / focus groups and survey data analysis   

Schools do well at monitoring and analysing attendance, supported by a nominated person responsible for this.  

Schools typically have a nominated person responsible for monitoring and analysing attendance, which helps them have oversight of what is happening.  

Nearly all (97 percent, N = 235) school leaders agree that teachers and leaders use data to monitor attendance patterns. In the schools we visited there is a focus on gathering and monitoring attendance data for individuals in the system.   

Who monitors and analyses attendance in schools?  

Principal: 71 percent  

Deputy or Assistant Principal: 66 percent  

Senior Leader: 28 percent  

Teacher: 36 percent  

Administrative staff: 54 percent  

School-based attendance or whānau officer: 18 percent  

Learning support staff: 13 percent  

Teacher aide: 3 percent  

Where effective, schools have differentiated roles regarding attendance. Teachers and leaders record and track attendance of individuals and groups of students. Senior leaders analyse and report patterns of attendance.   

There are expectations for schools to record and report on attendance, and most schools do report to the Ministry on attendance.    

Schools are expected to record and report all absences to the Ministry. Attendance is usually recorded with the use of codes through electronic attendance registers, which connect through schools’ management systems. This data is published each term and trends are tracked over time.   

Each school has their own policy to identify when a student is chronically absent.  

Nearly all schools (97 percent, N = 230) have a policy or procedure that guides the schools’ response to students’ non-attendance. These typically contain expectations for regular attendance, why attendance is important, and how to report absence.   

What doesn’t work?  

Source: ERO survey data analysis, site visits and interviews   

The lack of clarity around which attendance codes to use under what circumstances means that quality of this data is inconsistent.  

Schools told us that assigning attendance codes and monitoring attendance is time consuming. Schools are also not linking the codes to their responses to chronic absence. Attendance Officers in Attendance Services are funded to help schools with data analysis, but only 15 percent (N = 32) of school leaders receive help from Attendance Services to do this.  

Assigning attendance codes  

Schools are expected to record attendance daily, using a Ministry supplied system and 26 codes which identify the reason for absence (both Justified and Unjustified). Schools express their frustration with assigning codes, noting that it is time-consuming, complex and requires interpretation. They also talk about how they needed to spend time with parents and whānau to help them understand what these codes represent, and why an absence counts as ‘Unjustified’, even though an explanation had been given. Currently the Ministry is reviewing the use of the Attendance Codes to simplify their use to improve the consistency of data recording and reporting.  

There is no nationally consistent policy for when absence is a problem.   

Although there are guidelines for recording and expectations for how to classify attendance patterns, it is less clear about when to identify if absence is a problem. Schools are expected to develop their own attendance policies. Schools we visited have a range of practices for when and how to address chronic absence and there is variation in how they identify when attendance becomes a problem or when to escalate an issue.   

There is no clear guidance on when schools should escalate cases. According to Attendance Service Application guidance, absence referrals from schools to Attendance Services should occur when a student is unjustifiably absent, and the school has been unable to return them. Most school leaders refer students after 11 to 20 days of unjustified absences (25 percent, N = 45), and 35 percent (N = 63) do so after less than 10 days. However, one in five school leaders (18 percent, N = 33) only refer students after more than 21 consecutive days absent.  

Schools find it hard to identify and act when students are not enrolled in a school.  

The processes to identify non-enrolled students are making it hard to act, for example:   

• the system for schools notifying non-enrolled students is not used consistently well   

• investigations are often stalled through a lack of information about location or status   

• there is no clear way to escalate cases for students who are missing or not responding to attendance support.  

Schools do not escalate their response to absence early enough.  

Patterns of absence may go unnoticed or are not investigated, and these patterns become normalised. Only 43 percent (N = 132) of parents and whānau with a child who is chronically absent have met with school staff about their child’s attendance.   

Students and parents and whānau report how schools did not approach them to find out why their attendance patterns had changed, when an earlier conversation would have helped them get to school.     

Schools refer students too late, and it makes it harder for them to get students back to school.  

The Attendance Services consistently report that schools refer students too late, making it difficult for them to fix the issue. Over two thirds of Attendance Service staff report schools never, or only sometimes, refer students at the right time (68 percent, N = 86).   

c) Finding and engaging students with chronic absence and their parents and whānau

What is working?  

Source: ERO site visits, interviews / focus groups and survey data analysis  

Attendance staff develop good rapport and trust with parents and whānau, as a foundation to understanding the underlying challenges with student attendance.  

Staff in Attendance Services are usually passionate and care about the parents and whānau and students they work with. Staff focus on building trust with families to develop their confidence to share their struggles. This means they can better match them to the support needed to help get their child to school. Sixty-two percent (N = 72) of Attendance Service staff reported that they have safe and positive relationships with students all the time, and 38 percent (N = 44) most of the time.  

What doesn’t work?  

Source: ERO survey data analysis, site visits and interviews  

Finding students who are not attending is inefficient and time consuming and causes significant delays in engaging with them.   

Over half (52 percent, N = 65) of Attendance Service staff report that information is only ‘sometimes’ or ‘never’ shared across agencies, schools, and Attendance Services. Only 17 percent (N = 21) report it happens ‘all of the time'.   

In Attendance Services ERO visited, we found that there is insufficient information from schools about attendance patterns and pastoral care for individual students, including barriers to attendance or strategies that had been used previously to encourage attendance. This can lead to Attendance Services trying forms of support that schools had already attempted.   

Attendance Services also told us that there were government agencies, like Work and Income, who were in regular contact with the families but would not share contact information or help facilitate contact due to privacy concerns.    

Attendance Services also reported that the Attendance Service Application used for referring students to Attendance Services is difficult to use and does not retain all the information needed reliably. Many Attendance Services run a supplementary data collection system.  

Safety can be a significant barrier to initial engagement.  

Many Attendance Service staff have to work in pairs when making initial engagements with students and their parents and whānau, as safety cannot always be guaranteed. Some staff discussed negative experiences, where they did not feel safe to enter properties and engage with parents or whānau.   

d) Working with students, parents and whānau, and others to plan a response  

What is working?  

Source: ERO survey data analysis  

Schools and Attendance Services are planning responses to address students’ barriers to attendance.   

Sixty-seven percent (N = 82) of Attendance Service staff plan how they work with students and parents and whānau using what they know about students and what works all of the time. Eighty-seven percent (N = 207) of school leaders do the same - in schools, support is planned and managed to ensure students can maintain attendance all (39 percent, N = 94), or most (47 percent, N = 113) of the time.   

What doesn’t work?  

Source: ERO survey data analysis, site visits and interviews  

Schools and Attendance Services identify different drivers to students and parents and whānau.     

Fifty-six percent (N = 69) of Attendance Service staff report they always identify the causes of students missing school. School leaders also think they can identify drivers of absence. Ninety-three percent (N = 168) of school leaders are confident that their school knows students’ current barriers to attendance.   

However, there is a mismatch between what schools and Attendance Services identify, and what students and parents and whānau see as the barriers.   

• Students report school drivers as the main drivers of absence.    

• School leaders report family factors as the main drivers of absence.  

• Parents and whānau report student factors as the main drivers of absence.  

• Attendance Service staff report family, student and school factors equally.   

This mismatch matters as it can mean support is not effective and improving attendance.  

“Behind every attendance issue lies a larger issue, so do a needs assessment about what the whole whānau need, to be able to get the end result of the young person returning back to regular schooling.” (Attendance Service staff)  

Whilst planning happens, Attendance Service staff and school leaders do not always have the ability to develop a good plan.     

In Attendance Services, staff come from a variety of backgrounds, including youth or social work, but do not receive any specific training for their roles. This means plans and strategies are often based on individual personal experience, and rarely on evidence-based practice. There is a lack of guidance on what effective plans look like.  

School leaders are not well supported to make effective plans. Less than half of school leaders receive help from Attendance Services to developing plans and strategies (39 percent, N = 85).  

e) Removing barriers to attendance and enforcing compliance 

What doesn’t work?  

Source: ERO survey data analysis, site visits and interviews  

School and Attendance Service staff often struggle to access the community and social supports needed to effectively remove barriers – especially when the young person is not currently enrolled in a school.   

Community and social supports are not working effectively with schools or Attendance Services to remove barriers to student attendance – especially when the young person is not currently enrolled in a school. Nearly half of Attendance Services (52 percent, N = 59) and over half of schools (67 percent, N = 148) are only sometimes, or never able to access appropriate community supports in a timely way.   

Often, Attendance Services found that other agencies and support organisations did not have school attendance as a priority, and were reluctant to promote this in their work, or assist Attendance Services. There is often a time lag and waitlist of available services and agency support. Access depends on established relationships.   

Attendance Services and schools are reluctant to use legislative levers for fear of damaging their relationship with students and parents and whānau.  

Sixty-two percent (N = 67) of Attendance Services and 54 percent (N = 119) of schools report that they do not have good options to enforce attendance, holding students, parents and whānau, schools and Attendance Services accountable.  

There are some options for schools to enforce attendance expectations through messaging and excluding student privileges or detentions. Although there are options for fining parents, this is rarely used. We heard that some schools have tried to use legislation to prosecute parents and found the process overly complex and costly. Others talked about the lack of a positive outcome – it did not increase the student’s attendance and the process damaged any positive relationships that had been built, meaning parents and whānau became more alienated and antagonistic towards schools and services. 

f) Returning students to school and/or increasing their attendance  

What doesn’t work?  

Source: ERO survey data analysis, site visits and interviews   

There is a lack of clarity around roles, responsibilities, and what is allowed or expected when returning students to school.  

It is not clear when Attendance Services stop having responsibility for a student who has returned to school, and what the role is of the schools in ensuring students’ transition is positive and sets them up well for ongoing improved attendance. While some Attendance Services collaborate regularly with schools and share information about the students they are working with, others do not. Two in five Attendance Service staff (40 percent, N = 47) identify clarity in roles and responsibilities as something that would help increase attendance in schools.  

The quality of handover as students are returned to school and their attendance support is phased out, is highly variable.   

Almost half of Attendance Services staff (48 percent, N = 60) report they do not always wait to close a case until a student is able to sustain attendance. Most Attendance Services have little engagement with students once their cases were closed, unless they were re-referred.   

We heard that Attendance Service staff were not always confident that students were attending school regularly when they closed a case, and that sometimes they continued to check up on the progress of students on an informal basis. Other staff talked about the expectation that they close a case as soon as they could so that they could move on to other cases. Attendance Services are expected to meet KPIs that can lead to cases being closed before there is sufficient evidence of increased attendance and engagement. This means Attendance Services are not able to know if their interventions are effective in the longer term.   

Source: ERO site visits, interviews / focus groups and surveysSource: ERO site visits, interviews, focus groups and surveys  

School leaders reported that sometimes case closures are not discussed with the school, and some are closed by Attendance Services as soon as children come back to school.   

“High caseloads prevent us from being able to monitor ongoing attendance. In the case of non-enrolled students, once they are enrolled, case is closed straight away. There are more new cases to replace them.” (Attendance Service staff)  

Schools do not welcome all students back to school.   

Two-thirds of schools (67 percent, N = 160) report absent students are welcomed back to school all of the time but Attendance Service staff talked to us about schools who did not welcome some students back who had been stood down before, or had behavioural incidents or a negative history at the school.  

Students discussed the way in which teachers or senior leaders in the school did not make them feel welcome and they felt they didn’t belong at the school. In some cases, their return to school made them feel more disconnected and isolated from others, and catching up was an impossible task.   

Source: ERO site visits, interviews / focus groups and surveysSource: ERO site visits, interviews, focus groups and surveys  

Schools cannot always access the additional support some students need on their return to school.  

Schools report being unable to access enough or specialised support to help students reintegrate into school, especially for traumatised or high needs students. Not getting this support means students may be unable to navigate school systems, and they may feel confused and unable to connect with learning. Schools also talked about how they did not always have the capacity to spend a prolonged period of time with returning students to ensure they continued to improve their attendance.   

“If I could somehow find some other students like me and get the teachers to help me do this – I can't do it by myself.” (Student)  

“In our area, we have a high number of students with anxiety and mental health and there aren't enough health providers to support. These students won't, or most likely won't, return to mainstream school and we need to be getting in earlier with these students to help the problem.” (Attendance Service staff) 

g) Sustaining good attendance and engagement in education 

 What is working?  

Source: ERO site visits, and interviews, focus groups  

Schools are trying different approaches to support students to sustain their attendance.   

Schools are committed to improving attendance and trying approaches, including:  

• reward systems for attendance goals to help motivate some students and develop a sense of agency and belonging  

• adapting timetables in consultation with individual students to help them reintegrate successfully, and to fit around their learning interests or home circumstances  

• offering alternative programmes or courses within the school that interest the student, including connecting students to their local environment or their cultural identity.  

In some cases, these programmes are helping to attract students to the school environment and bridge the gap in learning caused by their absence from school.  

What doesn’t work?  

Source: ERO survey data analysis, site visits and interviews   

More support is needed to prevent problem attendance reoccurring.  

Seventy-six percent (N = 97) of Attendance Services report that support is not always put in place so students continue to attend once they have re-engaged.    

Although nearly four in five students (79 percent, N = 203) identify learning at school as a driver for their attendance issues, under half (44 percent, N = 105) of school leaders report they have changed schoolwork to better suit learners on their return.  

There are a lack of tailored, alternative, and vocational education offers that keep students engaged and motivated.  

Students do not attend when they do not see the point in what they are learning as it is not relevant to their aspirations, or it is not at the right level for them. Seventy-nine percent (N = 203) of students identify their learning as a barrier to attendance.   

We found that for many students, the courses offered did not fit their interests or learning abilities, which meant they were less interested in attending school. For some there was a mismatch in the level of learning offered (too easy or too hard) which meant they were reluctant to attend class.  

There are not enough options for students to learn things that matter to them, in ways that work for them.  

There are limited options available for re-engaging students in learning that fits them. Access to alternative pathways or vocational courses is limited through wait lists, and in some cases only accessible to students with a positive attendance record. Vocational courses are sometimes available through exemptions at 15.5 years old. Over half of schools (59 percent, N = 129) and Attendance Services (58 percent, N = 63) report there are not opportunities for young people to learn in other settings.  

Source: ERO site visits, interviews, focus groups and surveys  

Secondary school teachers told us about the frustration in trying to enroll students in Alternative Education or exempted courses due to isolation, travel costs, or wait lists.  

“[We need to] provide quality education options to students for whom mainstream school is not the best option, and different education options for neurodiverse and disabled learners where appropriate.” (Attendance Service provider)  

h) Roles, accountability and funding 

What doesn’t work?  

Source: Ministry of Education  

Resourcing does not match the level of need.  

There is variation in the size of contracts and funding (from around $20,000 to $1.4m) and in how much funding is allocated per eligible student – from $61 to $1,160 per eligible student.    

Funding allocation has not increased to match the increase in chronic absence, which has doubled since 2015.  

Source: ERO survey data analysis 

There is inequitable distribution of attendance caseloads. There are services we visited with a typical caseload of over 500 and others with a caseload of less than 40.   

Most Attendance Services are facing high and increasing caseloads, and often do not have the capacity to work effectively to resolve attendance issues. Many Attendance Services work with a high number of schools. From our survey, Attendance Services work with an average of 37 schools, this ranges from two to more than 200.   

Source: ERO site visits, interviews / focus groups and surveysSource: ERO site visits, interviews, focus groups and surveys  

The volumes of cases managed by providers varies from four cases to 1,743 (providers supporting all types of referrals) and 4,397 cases for one provider supporting non-enrolled cases only.   

“My colleagues and I would be much more effective if our team was doubled or tripled – we usually know what would work, and have the skills to carry out successful interventions, but simply don’t have enough time to provide effective help to everyone on our caseloads.  We also know that there are many more students we could help, but schools don’t refer them because they know we are already well over our capacity to respond.” (Attendance Service staff)  

Schools are not able to access the attendance support they need.  

Over half of school leaders (60 percent, N = 134) report that there are not enough Attendance Services in their area.   

Schools are finding it difficult to give sufficient time and resources to attendance matters – monitoring and analysing, engaging with families, planning and implementing strategies and support for students, and ensuring re-engagement is appropriately supported.  

Who is responsible for what is unclear. School leaders and Attendance Services say they know their roles and what they are responsible for, but interpret their roles differently and make up their own roles and systems.   

Most school leaders (86 percent, N = 190) and Attendance Service staff (84 percent, N = 92) say they know what their roles are when resolving attendance issues, but what they told us they were expected to do did not match. Two in five Attendance Service staff (40 percent, N = 47) and a fifth of school leaders (21 percent, N = 45) report the need for more clarity about the roles and responsibilities.  

There is variation between schools on what they consider meets the legislatively required ‘reasonable steps’ they take to address barriers to attendance and get students to school. There is also variation in understanding when it was appropriate to refer a student to Attendance Services. We found there was confusion about the role and responsibilities of support services (such as Resource Teachers Learning and Behaviour, Social Workers in Schools, Learning Support Co-ordinators) to support attendance.    

People are not sure who is supposed to do what if they are unable to get a chronically absent student back to school.  

Both Attendance Services and schools were unsure what to do if they are unable to get students back to school. This was particularly so if they couldn’t contact a family or access a property to investigate the causes of absence.    

Schools and Attendance Services are both unsure about who took responsibility to work with students who become unenrolled or disappear from the system.  

Accountability is weak.  

Schools are legally responsible for making sure students attend school, and they must keep daily records and submit their attendance data to the Ministry each term. There is not an agreed operating model, how schools choose to improve attendance is up to them and while ERO can identify that schools need to improve attendance, there are limited mechanisms in place to hold schools to account if they fail to do so.   

Attendance Services have contractual obligations to the Ministry, including reporting against key performance indicators (KPIs). The only levers to address non-performance are contractual. 

3. What models and provisions do other countries have to manage attendance? 

Source: International literature review  

The expectations for enrolment and attendance in Aotearoa New Zealand are comparable to the expectations in England, New South Wales (NSW, Australia), and Singapore. However, the way these expectations are managed in those countries is different in several critical areas like:  

• what counts as ‘chronic absence’  

• autonomy  

• guidance  

• accountability  

• escalation pathways.  

What counts as ‘chronic absence’?  

Aotearoa New Zealand has a focus on chronic absence. Out of the countries we looked at, Aotearoa New Zealand is the only one with a distinct category to capture chronic absence (<70 percent attendance). England capture ‘severe absence’, but this is classified as under 50 percent attendance.  

Aotearoa New Zealand has a high level of autonomy.  

Aotearoa New Zealand was unique in the level of autonomy held at the school level. Expectations allow boards and Attendance Services to design their own solutions to poor attendance. This is different from Australia, where there is a tiered framework of support and intervention and tailored to the school community. It is also different from Singapore and England who have a more centralised education system.  

Aotearoa New Zealand has limited guidance.  

In Aotearoa New Zealand, there is limited guidance for schools on what reasonable steps they should take in practice to lift attendance before referrals to Attendance Services are made. This is different from England, where schools must follow detailed statutory guidance on improving attendance. There are also a range of additional guidance and resources available, including specific support for schools through ‘attendance hubs’.  

Aotearoa New Zealand has weaker accountability.  

Aotearoa New Zealand schools face fewer ramifications for poor attendance than schools in England and New South Wales, Australia (NSW). ERO looks at school attendance at a system level, or when schools see it as a priority, but there are no clear ramifications for poor attendance in Aotearoa New Zealand schools. This is different from England, where attendance is considered as part of Ofsted inspections, and schools may face serious consequences if attendance is unacceptably low. In NSW, attendance rates are a performance indicator within the National Education Agreement and a key performance measure in the Measurement Framework for Schooling in Australia.    

Aotearoa New Zealand has weaker enforcement.  

Escalation pathways in Aotearoa New Zealand are less clear and not as consistently applied as other countries. Parents can be fined, and schools or Attendance Services can request a Family Group Conference, but these are not regularly used in practice. In England, there are a variety of options and steps available. Fines are regularly issued, and councils can apply for an Education Supervision or School Attendance Order, before prosecuting parents as a last resort.   

Conclusion

Effectively returning students to school and increasing their attendance requires a coherent approach with eight key components. We found most of these are not working effectively across the system for supporting attendance.   

The system in Aotearoa New Zealand does not perform well across the components of good practice. In particular, the system does not perform well at removing barriers to attendance and enforcing compliance, returning students to school, and/or increasing their attendance, and planning for sustained attendance and sustaining good attendance. There are some enabling conditions that also require improvement.  

The next chapter of this report looks at how we analysed the impact of the Attendance Services and other initiatives to support attendance.