[Screen reads: AEDC Symposium August 2022.]
[Screen reads: Dr Yasmin Harman-Smith, Telethon Kids Institute.]
Hi. Yasmin Harman-Smith here from the Telethon Kids Institute on Kaurna Country in South Australia.
I'm the head of the Earlier Systems Evidence Team and we provide support to the Australian Government and states and territories for the AEDC, the Australian Early Development Census Program.
I'd like to pay my respects to Kaurna elders past and present and acknowledge the continuing importance of culture and country for Kaurna people today.
I'm here to give you a welcome to the AEDC New South Wales 2022 Research Symposium on Demand. It will be live on the 11th of August and you'll be able to access it on the New South Wales Department of Education's official website.
The On Demand Symposium will consist of six outstanding presentations and a session on research and action. You'll see how schools and services have used AEDC data to develop targeted initiatives.
It's intended to provide you an opportunity to explore the various ways you might engage with the AEDC data and provide you with resources and connect you to knowledge from those who have successfully engaged with the AEDC for policy, practice and research.
The team in the New South Wales Department of Education have pulled together some really great examples of how others have used the AEDC and we hope this will inspire your own work in connecting evidence to planning children’s learning and wellbeing.
AEDC data is incredibly valuable. It gives you a snapshot of children's development, what families need and what communities can do to support them. I'm sure you'll be inspired by school leaders such as Teagan Sawyer, early childhood education service leaders Niccole McDowell, Narelle Myers and researchers Keisi Chung, David Gummersall, Elise Harvard and Georgina Chambers.
The Research in Action section will include stories from Queensland, Western Australia and Tasmania. There's an attendee pack and it'll support you to reflect and engage with these presentations. It has prompts to guide your thinking and help you to consider what you've seen that's relevant to your context.
You'll also be connected to a range of other helpful resources alongside the symposium videos, including the New South Wales AEDC Professional Learning and Podcast Series. These provide great tips and guidance and the value of the AEDC data and support educators to think about how they can integrate the data into their planning practices.
All these resources are free and available on demand, so you can engage with them at your own pace and return to them whenever you want to.
I hope you enjoy this On Demand symposium.
[Video concludes by displaying the NSW Government logo.]
[End of transcript.]
In this section, researchers explain how they have drawn from the AEDC data to inform their research to new insights and knowledge development.
Watch 'Investigating the impact of prenatal medicine exposure on childhood neurodevelopment' (22:25)
[Screen reads, ‘AEDC Symposium, August 2022’. Screen shows Alys Havard superimposed in a small box on a title slide that introduces the two speakers and their roles.]
Hi, my name is Alys Havard. I'm a researcher at the National Drug & Alcohol Research Centre and the School of Population Health at UNSW Sydney. It's my pleasure to be giving this presentation today alongside my colleague, Claudia Bruno, who is a PhD candidate at the School of Population Health at UNSW. And we are both part of the Centre for Research Excellence in Medicines Intelligence.
In our presentation today, I'll be telling you about our planned research on the impact of medicine use during pregnancy on childhood neurodevelopment. This work forms part of a broader program of research on the safety of medicines when used during pregnancy, and in this program, we'll be examining a range of important safety outcomes, including and beyond neurodevelopmental outcomes among children.
I'll be telling you about the research plans that are still under development, which means I won't be sharing any results today, but this is where Claudia comes in. She has been leading some very similar research using data from the Nordic countries, and we thought it would be nice to tell you about that and give you a taste for what we plan to do with the local data when we receive them.
[Screen reads, ‘Evidence gaps in medicine safety during pregnancy.’ Alys provides further explanation of the data.]
I'd like to start with some background on why we are conducting research on the safety of medicines when used during pregnancy. First, medicine use during pregnancy is common. So the proportion of pregnant women using at least one prescription medicine varies from 27% to 93% across developed countries. Yet the use of some medicines during pregnancy may not be safe. The theoretical risks of any chemical exposure during pregnancy include disruptions to placental function, foetal growth, organ development, and neurodevelopment, and disruptions to these processes could lead to severe adverse events for the mother or child, including preeclampsia, poor foetal growth, preterm birth, stillbirth, congenital anomalies, and poor neurodevelopment, which might manifest as neurodevelopmental disorders such as autism or ADHD, through poor academic performance, or as a developmental vulnerability that may not reach clinical levels, but is still limiting for the child.
Unfortunately, for most medicines, there is inadequate evidence on the risk of these outcomes and whether they're safe to use during pregnancy. This is partly because pregnant women are routinely excluded from clinical trials due to ethical and medico-legal concerns. So in these circumstances, we need to rely on evidence from observational studies, but robust evidence from such studies is not yet available. To be able to produce robust evidence, these studies need to be based on really large cohorts of pregnant women and children, because this is required to obtain reliable measurement of these safety endpoints, many of which are really quite rare. And in order to measure child neurodevelopment, it's important that these studies incorporate a long period of follow up so that outcomes can be measured at key time points during childhood.
[Screen reads, ‘The UNSW Early Life Course data platform’. Below this, screen shows an image of three blue boxes, connected by a double-headed arrow that reads, ‘Early Life Course Platform’. From left to right the boxes read, ‘Medicines in pregnancy’, ‘Perinatal health and exposures’ and ‘Child health, development and wellbeing’.]
And this is exactly what we intend to do, using data from the UNSW Early Life Course data platform. So the Early Life Course platform is a large linked dataset that our team at UNSW are building. It has been designed to support research falling under three themes. That's medicines in pregnancy, perinatal health and exposures, and child health, development, and wellbeing. In this presentation, Claudia and I will be focusing on planned research in the medicines in pregnancy theme.
Before moving on, I'd like to acknowledge our colleagues listed here, or pictured here, all of whom were involved in building this data resource and in leading research under these three themes.
[Screen shows head-shot images of ‘Alys Havard’, ‘Georgina Chambers’, ‘Helga Zoega’ and Bronwyn Brew Haasdyk’.]
Here's a high level overview of the data collections we're linking for the Early Life Course platform.
[Screen shows an image of a mind map. The focus of the mind map reads, ‘All pregnancies resulting in birth in NSW between 2001-2019 = 1.7 million’. Branching off from this are, ‘Pharmaceutical dispensing’, ‘Other health service use’, ‘Registries’, ‘Education’ and ‘Death’.]
The span of the cohort for this linkage comprises all pregnancies resulting in birth in New South Wales in the 19 years from 2001 to 2019. So records of these pregnancies are being linked to 17 different data collections. And from those collections, we are obtaining records belonging to the mother as well as the child. A key data collection that we are linking is the pharmaceutical benefit scheme data, which includes a record for every prescription medicine dispensed that is eligible for subsidy by the Australian government. This will give us information on medicines used during pregnancy.
We'll be obtaining data on a range of other health service use. Data from registries, data collected in the school setting, and then death records.
And here is a more detailed list of the data collections we are obtaining, as well as an indicator for which life stage the data will cover.
[Screen shows a table listing different data collections within the categories, ‘Births, Health Service, Registries, Education and Deaths’ and shows where the collections contain data from certain life stages, ‘Pre-pregnancy’, ‘Pregnancy and birth’, ‘First 2000 days’, ‘School entry’ and ‘Childhood’. Alys provides further explanation of the data.]
So at the top of the list, we've got records relating to births, which include birth registrations and the perinatal data collection. So it's from these records that we construct the spine for the linked data set, which, as I mentioned, comprises all pregnancies resulting in a birth in New South Wales between 2001 and 2019. These perinatal records also provide information about the pregnancy, the birth, and then the neonate, and all of that information is collected by the midwife at the time of birth.
Then we have various data collections that relate to health service use, including medical services funded through Medicare. Also the Pharmaceutical Benefits Scheme data. And we have admissions to the Neonatal ICU, hospital admissions, emergency department presentations, outpatient mental healthcare, and immunisations. We are linking in registries, which cover cancer diagnoses and treatments, as well as congenital anomalies. Then we have three different data sources covering data collected of the children in the education sector. So these include records of school enrolment, the NAPLAN records, and then, of course, records from the Australian Early Development Census. And finally, we have records of deaths that occur among the women and children in our cohort.
Now, we haven't yet received the data for the Early Life Course platform, but we've done very similar research in the past, so we have a really good idea of how we'll conduct these studies of medicine safety and how we will measure each of the key variables.
And here, I want to tell you about how we will identify prenatal exposure to medicines.
[Screen reads, ‘Prenatal exposure to medicines.’ Screen shows an image that summarises Alys’s explanation of how they will gather data.]
So we'll be using the perinatal record in combination with the Pharmaceutical Benefits Scheme records to identify medicines dispensed during pregnancy. So we will estimate the period of pregnancy by subtracting the baby's gestational age from their date of birth, and these pieces of information are both available in the perinatal data collection.
Then, using the linked PBS records, we will be able to identify instances where the date of supply of a medicine falls in that period of pregnancy that we've identified.
In each study, we'll be focusing on a specific set of medicines, and we're planning to start with a study of quit smoking medicines, which you may know include nicotine replacement therapy, varenicline, and bupropion. And we're starting here because fortunately, we have an NHMRC grant to support that work.
We're also planning studies on the safety of opioid analgesics during pregnancy, and we have a PhD student and a post-doctoral fellow planning that work. But as I mentioned earlier, there's insufficient evidence on a really wide range of medicines when used during pregnancy, so we're hoping to use the Early Life Course data to investigate as many of these medicines as possible, given... Or within the resources available.
So I mentioned earlier that there are a number of mechanisms through which medicine exposure prenatally can contribute to adverse outcomes for the mother and for the child. And so it's really important to obtain evidence on a comprehensive range of safety outpoints.
So here are some examples of the outcomes that we'll be measuring in our planned work.
[Screen reads, ‘Safety outcomes’. Alys provides an explanation of the safety outcomes.]
We've got pregnancy complications, including preeclampsia, postpartum haemorrhage, emergency caesarean, et cetera. These are all things that are recorded in the perinatal record.
We also have adverse neonatal outcomes including stillbirth, preterm birth, low birth weight, admission to the Neonatal ICU, and these are also in the perinatal record, although for some of them, we'll be using hospital admission records among the neonates to supplement the measurement of these outcomes.
We also have major congenital malformations, which we'll measure mostly with hospital admission records, because the major malformations generally require surgery, but we also have registry data on congenital anomalies, which we'll explore, but we do know that it is limited.
And then, of course, we have the neurodevelopmental outcomes, which will come from... Well, we'll come at this from different angles. We'll be looking at diagnosed neurodevelopmental disorders like autism and ADHD, and we plan to measure these using records of relevant Medicare funded treatments and prescription medicines which are used in the treatment of ADHD. We'll be using children's NAPLAN scores to measure their academic performance. And then we'll also be using the AEDC data to measure developmental vulnerability that may not reach clinical levels, but is still potentially limiting for the child.
Now, because we haven't yet conducted this research, we don't have the data in house yet, we don't have results from Australian data to share, but Claudia's related research using data from the Nordic countries should provide a good illustration of the kind of evidence we're aiming to generate, and how we'll do that. So I'm going to hand over to you now, Claudia.
[Screen reads, ‘Antipsychotic medication use during pregnancy and cognitive impairment in children. A Nordic population-based register study’. Screen shows Claudia Bruno superimposed in a small box.]
Thank you, Alys. As Alys mentioned, the purpose of my presentation today is to demonstrate how administrative data sets similar to the AEDC can be used. I'll be describing an ongoing study examining the association between antipsychotic medication use during pregnancy and cognitive impairment in children. This project is part of a larger collaboration known as INPRESS, an international pregnancy and safety consortium, which has, and will continue to use, observational data from different countries to examine the safety of medication use during pregnancy.
Before I begin, I would like to acknowledge the work of my co-authors in INPRESS, particularly the team at the Norwegian National Institute of Public Health, where I'm conducting this research as part of my PhD project, and my supervisory team at the School of Population Health, UNSW. Please note that this work is ongoing and that these results are preliminary.
[Screen is titled, ‘Background’. Where it reads, ‘Pregnant women are increasingly exposed to antipsychotics’ it refers to a footnote that reads, ‘Reutfors J, Cesta CE, Cohen JM, et al. Antipsychotic drug use in pregnancy: A multinational study from ten countries. Schizophr Res 2020; 220: 106-115.’ Where it reads, ‘Recent data from US suggest potential developmental disorders, were limited by numbers and requires replication for individual medicine signals’ it refers to a footnote that reads, ‘Straub L. Hernandez-Diaz S, Bateman BT, et al. Association of Antipsychotic Drug Exposure in Pregnancy With Risk of Neurodevelopmental Disorders: A National Birth Cohort Study, JAMA Intern Med. 2022; 182(5):522-533.’ Claudia provides further explanation of the background.]
We are looking at antipsychotic medication during pregnancy because pregnant women are increasingly exposed to antipsychotics. These medicines are primarily indicated for the treatment of schizophrenia and bipolar disorder, however, are increasingly being used to treat other conditions such as depression, anxiety, insomnia, and substance abuse.
As Alys mentioned, theoretically, there are increased risks due to exposure to any medication. And for antipsychotics, these medications are known to cross the placenta, with animal data suggesting that they may affect memory and learning in offspring. Observational data has shown no clear risk of neurodevelopmental disorders such as ADHD and autism. However, there is fewer data on other developmental disorders and academic performance as indicators of cognitive developmental impairment.
[Description not needed: The visuals in this part of the video only support what is spoken; the visuals do not provide additional information.]
Our aims were to examine whether children exposed to antipsychotics in utero are at increased risk of cognitive impairments compared to children unexposed to antipsychotics in utero. Specifically, we looked at developmental disorders, including intellectual, learning, speech and language developmental disorders. We also looked at poor academic performance in mathematics and language arts.
Similarly to NAPLAN in Australia, Nordic countries require standardised testing throughout schooling for all children. Fortunately, we were able to leverage national population and health registries of Nordic countries, and these contain information for all persons living in Denmark, Finland, Iceland, Norway, and Sweden born between 2000 and 2020. This figure shows national registries with the kind of data that they collect.
[Screen shows a diagram with a box in the middle titled, ‘Common data model’. Inside the box are a set of words. Circles surround the box with arrows pointing to words inside the box. Clockwise from the top: Circle reads, ‘Cause of death registers’ with an arrow pointing to the word ‘Death’ inside the box. Circle reads, ‘National patient registers + primary care’ with an arrow pointing to the words ‘Hospitalisations’, ‘Procedures’ and ‘Diagnoses’ inside the box. Circle reads, ‘Medical birth registers’ with an arrow pointing to the words ‘Perinatal data’, ‘Pregnancy’ and ‘Child’ inside the box. Circle reads, ‘Prescribed drug registers’ with an arrow pointing to the word ‘Prescriptions’ inside the box. Circle reads, ‘National Statistics and Social Insurance agencies’ with an arrow pointing to the words ‘Residence’, ‘Socioeconomic’, ‘Sick leave’ and ‘Academic (child)’ inside the box. Footer reads, ‘Cohen, J.M. ., Cesta, C.E. ., Kjerpeseth, L. ., Leinonen, M.K. ., Hálfdánarson, Óskar, Karlstad, Øystein ., Karlsson, P. ., Anderson, M. ., Furu, K., & Hjellvik, V. (2021). A common data model for harmonization in the Nordic Pregnancy Drug Safety Studies (NorPress). Norsk Epidemiologi, 29(1-2). https://doi.org/10.5324/nje.v29i1-2.4053.]
We have used both prescription registries and medical birth registries to ascertain exposure of medication during pregnancy. We also use patient registries to identify children with developmental disorders, and whether their mother had a psychiatric condition recorded prior to pregnancy. School performance is also routinely collected, and for this outcome, we included all children born between 2000 and 2010, excluding Finland, where this information was not made available. Note that not all countries have data from 2000 to 2020, and the years that they contribute depend on when their registries began in the individual countries and when they were last updated.
[Screen reads, ‘Measures, Exposure to antipsychotics: (ATC: N05A) – At least one prescription fill for any antipsychotic medicine during pregnancy defined as last menstrual period (LMP) to birth.’ Below this is a table that represents exposure periods as Pregnancy trimester one to 3, trimester 2 to 3, trimester one and trimester 2 and/or trimester 3, and those unexposed pre-pregnancy or pregnancy.]
We classify children as exposed to antipsychotics prenatally if their mother had at least one prescription fill for any antipsychotic, excluding lithium, between the last menstrual period and delivery. Children were deemed unexposed if their mother did not have a prescription from 90 days prior to their last menstrual period and until birth. We also included a range of other exposure definitions. However, I'll only be presenting exposure to pregnancy anytime.
[Description not needed: The visuals in this part of the video only support what is spoken; the visuals do not provide additional information.]
To identify outcomes for developmental disorders, we require that children have a diagnosis of child developmental disorders from the age of three, and we model these using Cox proportional hazards.
For poor academic performance in mathematics and language arts, we define poor performance if their score was in the lowest 25th percentile for their year and grade level. In Sweden, we used whether the child had a fail grade recorded, due to the availability of data provided.
We restricted to women with psychiatric disorders in the year prior to birth. This was to eliminate confounding by indication and to ensure that the risks identified were due to medication exposure and not the underlying psychiatric condition.
We also adjusted for several indicators of maternal health and social behaviours, as those listed here.
[Screen reads: Adjusted for covariates:
Maternal level of education, maternal country of birth, smoking during pregnancy, parity
Birth year and country of birth, sex of child.]
Having data from all five Nordic countries, we first included over 4 million singleton children born between the years 2000 and 2020. When restricting the cohort to women with psychiatric disorders, we included over 200,000 children. To estimate the risk of developmental disorders, further, we restricted the cohort to children with a school test in the academic cohort, and this included around 400,000 children. For today, though, I will be only showing results from Norway, Iceland, and Sweden, and these numbers are shown here.
[Screen reads: Results:
All singleton, live births: 4,394,109 children
Restricting to women with psychiatric disorder: 222,981 children
Academic cohort: 43,772.]
Our future... Shortly, we'll be adding Denmark and Finland to these results.
We found that women who are exposed to antipsychotics who have a psychiatric condition were more likely to be older, have lower education, have higher BMI, and smoke during early pregnancy. They were also more likely to use other medications during pregnancy. This table here shows the risk of developmental disorders for children who were exposed anytime during pregnancy to antipsychotic medications, compared to children who were unexposed among women with psychiatric conditions in Sweden, Norway, and Iceland.
[Screen shows a table with results for developmental disorders, for the categories: any, intellectual disorders, learning disorders and speech and language disorders. For each category, results are shown for both ‘unexposed’ and ‘exposed at any time’. The columns show the number of participants, and two models that Claudia explains. This data gives HZ: hazard ratio and CI: confidence interval. Footer reads, ‘Results only include children born in Sweden, Norway and Iceland’.]
We show both the minimally adjusted models, adjusting for mother's age, parity, sex of child, source country, and birth year, with the fully adjusted model, which adjusts for a wider range of covariates.
[Screen reads: Model 1 adjusted for mother’s age, parity, sex of child, source country and birth year. Model 2 adjusted for mother’s age, parity, sex of child, source country, birth year, maternal education, cohabitation, mother country of birth, BMI and smoking at early pregnancy, use of known/suspected teratogens, other medications during pregnancy, maternal comorbidity.]
We see here that for having any developmental disorder that the risks are no longer significant when fully adjusting for the model.
[Screen shows a red box appear around the results in the minimal adjusted column. For ‘Any: Exposed any time’ the results are 1.37 HZ (1.13 – 1.66 CI).]
Minimally adjusted results show higher risks of developmental disorders, individual developmental disorders.
[Screen shows a green box appear around the results in the fully adjusted column. For ‘Any: Exposed any time’ the results are 1.12 HZ (0.92 – 1.36 CI).]
However, when fully adjusting the models, these risks are attenuated and non-significant for learning and speech and language disorders.
Similarly, we show here, in this table, the risk of poor academic performance when restricting the cohort to women with psychiatric conditions in Sweden, Norway, and Iceland.
[Screen shows a table with results for poor academic performance, under the categories: any, intellectual disorders, learning disorders and speech and language disorders. For each category, results are shown for both ‘unexposed’ and ‘exposed at any time’. The columns show the number of participants, and two models that Claudia explains. This data gives RR: Risk Ratio and CI: Confidence Interval. Footer reads, ‘Results only include children born in Sweden, Norway and Iceland’.]
The minimally adjusted results for math and language show an increased risk of poor academic performance in these subjects.
[Screen shows a red box appear around the results in the minimal adjusted column. For ‘Math: Exposed any time’ the results are 1.11 RR (1.00 – 1.22 CI).]
However, when fully adjusting for covariates, including maternal education, a strong predictor of child academic performance, we see that there is no increased risk of poor academic performance in these subjects for women with psychiatric conditions and children who were exposed to antipsychotic medications during pregnancy.
[Screen shows a green box appear around the results in the fully adjusted column. For ‘Math: Exposed any time’ the results are 0.94 HZ (0.81 – 1.10 CI).]
To summarise our findings, we found limited or no clear association between antipsychotic use and cognitive impairment in offspring among women with psychiatric disorders, noting that these will be updated with more data from Denmark and Finland. This study is important, as women with psychiatric conditions, including schizophrenia and bipolar, can use the available evidence to weigh the risks and benefits of treatment with antipsychotics during their pregnancy. As we can see, these national data sets have allowed us to examine long-term outcomes associated with rare exposures. They provide a large population sample size to draw from, and having the data linked to a variety of information can help adjust for confounding inherent to observational research. There are, however, limitations, most notably that not all children with impairments or developmental vulnerabilities that affect growth and development will be captured with a clinical diagnosis or participate in school testing.
Their AEDC data may overcome this limitation, as it captures a wide range of developmental vulnerabilities not otherwise captured in the data sources we use today.
[Screen reads, ‘How can AEDC data be used?’. Below this shows a blue triangle cut with horizontal lines into 3 segments. The top segment reads, ‘Diagnoses at specialist hospital care’, the middle reads, ‘Academic test data for those who participate’ and the bottom reads, ‘AEDC developmental vulnerabilities’.]
And can be used to identify children who are below clinical thresholds, however, still feeling impairment. I hope this presentation has shown how data similar to the AEDC has been used in previous research, and how the AEDC could be used in future research as a marker of developmental vulnerability and an outcome in pregnancy safety studies.
[Screen reads: email@example.com and firstname.lastname@example.org]
Both Alys and I would like to thank you for your attention and welcome any questions or inquiries, or collaboration requests. Thank you.
[Video concludes by displaying the NSW Government logo.]
[End of transcript]
Watch 'Using AEDC data in research conducted as part of the National Disability Data Asset Pilot – Early Childhood Test Case' (24:16)
[Text on screen reads, ‘AEDC Symposium. August 2022’. Screen shows the speaker, Keisi Cheung.]
Hello everyone, welcome to the National Disability Data Asset Early Childhood Test Case presentation. Before I start, I would like to acknowledge that I'm meeting on the lands of the Gadigal people, and pay my respects to Elders past, present and emerging.
My name is Keisi Cheung, and I'm a principal data analyst from the Early Childhood Education and Schools policy directorate, in the New South Wales Department of Education. I'm joined here today by my colleague, David Gummersall, to take you on the journey of the research conducted as part of this test case, when an emphasis on how AEDC data was utilised as both a cohort and outcome indicator in our analyses.
In late 2019, the former Australian Data and Digital Council and Disability Reform Council agreed to pilot an enduring longitudinal and National Disability Data Asset, integrating data from the Commonwealth, states, and territories, and to develop the design for a future enduring asset. The asset aims to be the one-stop data shop that forms the evidence base to help governments, service providers and researchers to improve the effectiveness of services and supports for people with disability.
While the NDDA is being established, in the next couple of years, the data asset built in this test case will continue to be utilised and refreshed, to form the evidence base for various government initiatives, such as the Brighter Beginnings. I'll now hand over to David, who's going to present the key statistics and research findings in this test case.
[Screen reads, ‘National Disability Data Asset (NDDA) – Early Childhood Test Case. Driving better outcomes for people with disability through enabling data-driven decisions. Keisi Cheung and David Gummersall.’]
Hello everyone, welcome to the National Disability Data Asset early childhood test case presentation. Firstly, I would like to acknowledge that I'm meeting on the land of the Gadigal people, and the other Aboriginal lands you are all on today, and pay my respects to Elders past, present and emerging. I would like to acknowledge the First Nation colleagues here with us today.
My name is David Gummersall. I'm a data analyst from the Early Childhood Education and Schools policy directorate in the Department of Education. In this presentation, we'll explore some of the research outcomes with a particular focus on how the AEDC data set was used as part of the NDDA early childhood test case.
[Screen reads, ‘What is the NDDA?
A data asset that would bring together data from across Australia relating to people with disability into one network – and make it easier to analyse, access and act upon.
It aims to drive better outcomes for people with disability through enabling data-driven decisions.
A national pilot is exploring how a permanent data asset could be designed and how it could improve information for people with disability, the broader community, service providers, governments and researchers.’]
What is the NDDA? The NDDA stands for the National Disability Data Asset, and is essentially an enduring asset that aims to be a data-rich hub that forms the evidence base to help governments, services providers and researchers to improve the effectiveness of services and supports for people with disability, and also with developmental vulnerability.
[Screen reads, ‘Five government test cases. The pilot is undertaking 5 public policy test cases:
Education to Employment (SA). Explores the pathways through education and barriers to employment.
Justice (NSW and DSS). Explores the interaction of people with disability and the justice system.
Early Childhood (NSW Department of Education). Explores the impacts of early childhood supports for children with developmental delays and disability prior to or during school.
Mental Health (VIC). Explores the needs of people with mental health and psycho-social disabilities, and how these are currently being me to improve outcomes.
Outcomes data (DSS). Explores the possibility of deriving a comprehensive measure of disability using information available across linked datasets.’]
Our test case was one of the 5 other test cases conducted across several states in the 18-month NDDA pilot, which ended in December 2021. Our early childhood test case was just one of the 2 test cases conducted in New South Wales.
[Screen reads, ‘Early childhood test case goals and questions’. On the left side of the screen, text reads, ‘What are the test case goals?
Provide baseline data for Government policy development.
Inform policies, programs and services to facilitate the best possible outcomes for children identified with disability (or developmental vulnerability), in early childhood.
Gain better understanding of the relationships between the use of early childhood supports and the impact on child developmental and educational outcomes.’
On the right side of the screen, text reads, ‘Early childhood test case research questions:
Disability definition: How is disability defined across different datasets?
Services and supports: What services and supports are provided for children with disability and developmental vulnerability?
Impact on outcomes:
What is the impact of early childhood supports on child developmental, educational outcomes, and participation in early childhood education and school?
How do the developmental outcomes differ between children with disabilities and without disabilities?
How do the developmental outcomes across each domain differ between disability types?
Effect of ECE service types on developmental and educational outcomes.
Effect of ECE enrolment hours on developmental and educational outcomes.’]
Overall, the pilot was extremely successful, and we achieved all of the goals mentioned earlier and listed here on the left. The key learnings from the pilot have helped shape the construction of the NDDA enduring asset. In this test case, our research focused on 3 main areas. Disability definition, across the data sets. Services and supports, access by children with disability and developmental vulnerability, and the impacts of developmental vulnerability and educational outcomes.
[Text on screen reads, ‘What is the NDDA – EC test case?’ Screen shows a flowchart. The flowchart illustrates how using 23 datasets led to 2.33 million children in NSW being identified by the National Disability Data Asset – Early Childhood test. Speaker provides further explanation of the flowchart.]
The overall picture is shown here, with the total of 23 data sets linking together to identify over 2 million unique individuals to form the data asset. The research findings can be found in our comprehensive research report, which will be published later this year. This was all done in collaboration between our department and the team at the University of New South Wales. We have also built a data visualisation tool in collaboration with the Better Outcomes lab team in DCS. That will be made available soon.
[Text on screen reads, ‘All 23 datasets’. In the centre of the screen, there is a table that shows all of the data sets. The table reads:
Medicare Consumer Directory (2003 – 2019)
Child Care Subsidy/Child Care Benefit (2003 – 2020)
Medicare Benefits Scheme (2003 – 2020)
Australian Early Development Census (2009, 2012, 2015, 2018)
National Disability Insurance Scheme, including Early Childhood Early Intervention (2013 – 2019)
Disability Services National Minimum Data Set and Commonwealth State, and Territory Disability Agreement National Minimum Data Set (2003 – 2019)
National Death Index (2003 – 2020)
NSW Admitted Patient Data Collection (2003 – 2019)
NSW Perinatal Data Collection (2003 – 2019)
NSW Registry of Births, Deaths and Marriages (2003 – 2019)
NSW Emergency Department Data Collection (2005 – 2019)
NSW School Enrolment Record (2010 – 2019)
NSW School Attendance (2018 – 2019)
National Assessment Program – Literacy and Numeracy for NSW (2010 – 2019 for Year 3, 2012 to 2019 for Year 5, 2014 – 2019 for Year 7 and 2016 – 2019 for Year 9)
NSW Best Start Kindergarten Assessment (2010 – 2017)
NSW ChildStory (2003 – 2019)
Nationally Consistent Collection of Data on School Students with Disability (2015 – 2019)
NSW Annual (Community) Preschool Census (2009 – 2019)
NSW School Suspensions and Expulsions (2012 – 2019)
NSW Department of Education Student Disability Data collection (2011 – 2019)
NSW Mid-Year Census (2014 – 2019)
NSW Preschool Disability Support Program (2015 – 2017)
NSW Disability and Inclusion Program for High Learning Support Needs (2018 – 2019)’
On the left of the screen, text reads:
‘NDAA EC data asset captured 2.33 million children born from 2003 to 2019.
Children who died before age 7 were removed (n equals 7,353) from all record sets.
No data from the NSW Best Start Kindergarten Assessment was used.’]
So what were the 23 data sets? Here is the full list of all the data sets, and the respective time coverage. Together, they tell the story of New South Wales residents from birth to age 17, in various aspects of their life, such as perinatal parameters, access to healthcare, early childhood and school education, targeted disability supports, child protection services, and developmental and educational outcomes.
[Screen highlights 10 of the data sets in green. The highlighted data sets are:
Medicare Benefits Scheme (1,292,154 children identified)
Australian Early Development Census (462,124 children identified)
National Disability Insurance Scheme, including Early Childhood Early Intervention (98,152 children identified)
Disability Services National Minimum Data Set and Commonwealth State, and Territory Disability Agreement National Minimum Data Set (50,350 children identified)
Nationally Consistent Collection of Data on School Students with Disability (241,788 children identified)
NSW Annual (Community) Preschool Census (232,984 children identified)
NSW Department of Education Student Disability Data collection (20,238 children identified through Integration Funding Support, and 29,890 children identified through the Support Class Administration System)
NSW Mid-Year Census (25,077 children identified through government preschools and 3,780 children identified through Early Intervention)
NSW Preschool Disability Support Program (5,366 children identified)
NSW Disability and Inclusion Program for High Learning Support Needs (3,108 children identified).]
These 10 highlighted data sets were used to determine the presence of disability. Note the AEDC data set features near the top here, as part of one of the 10 data sets used to capture children with disability.
[Text on screen reads, ‘Disability categorisation framework’. Screen displays a flowchart that shows how the 10 data sets classified disabilities during collection. The flowchart demonstrates that only 3 data sets used the NDIS to classify disabilities into 19 disability subtypes. Additionally, only the AEDC classified children as having a developmental vulnerability. Speaker provides further explanation of the flowchart.]
Here is our disability categorisation framework. Generally, we found that there was a considerable discrepancy between how disability was defined between each of the 10 data sets. For the purposes of unifying all data sets, this framework was needed to have a consistent definition of our sub cohorts. The framework classifies disability as either medically-verified disability or any disability, where there are 5 disability subtypes under any disability and a more detailed 19 disability subtypes under medically-verified disability. Although it's not too clear here, any child classified as medically-verified disability will also be classified in the any disability group. Hence, one is the subset of the other.
[Speaker points to the 3 data sets that used the NDIS to classify disabilities into 19 disability subtypes. These datasets are the Disability Services National Minimum Data Set, the Medicare Benefits Scheme and the National Disability Insurance Scheme.]
While all 10 data sets can be categorised into the 5 disability subtypes, only 3 Commonwealth data sets here on the left have an additional classification of the 19 disability subtypes based on the NDIS disability classifications.
[Speaker points to the section of the flowchart that represents developmental vulnerability.]
We also created another cohort deemed as having developmental vulnerability, here on the right. And that's if they scored vulnerable on 2 or more out of the 5 AEDC domains. Hence the AEDC dataset helped us to not only identify children in the any disability group, but also was solely used to define children in the developmental vulnerability group.
Note the developmental vulnerability group is not mutually exclusive to the other two disability groups. So for this presentation, due to time constraints, we will just focus on the red rectangle area, which includes only developmental vulnerability group and any disability group, including the 5 disability subtypes.
[Screen reads, ‘What were the 5 disability subtypes?
Physical and diverse: Cerebral palsy, acquired brain injury, macrocephaly, dystrophy, cystic fibrosis, muscular dystrophy
Intellectual and learning: Autism, down syndrome, spina bifida, trisomy 21, global developmental delay, fragile X syndrome
Sensory and speech: Blind, deaf, hearing impairment, visual impairment, apraxia, congenital eye condition
Psychosocial: Anxiety, Tourette’s syndrome, ADHD and ADD, oppositional defiance disorder, schizophrenia, bipolar affective disorder
Other disability: Obesity, renal failure, malignant neoplasm of the brain, HIV, brachial plexus injury’.]
Here are some examples of what the disability diagnoses are, included in each of the disability subtypes. This was loosely based on the NCCD classifications, with an additional subtype called other disability added to include diagnoses which can't be categorised in the other 4 disability subtypes.
[Text on screen reads, ‘Disability prevalence’. Screen shows a line graph that demonstrates the percentage of cumulative disability between birth and 7 years of age. Speaker provides further explanation of the data.]
Given that this is a test case with an emphasis on early childhood disability, we created an age cut-off of 7 years of age for disability diagnoses. Meaning, in our analyses, we are only considering disability diagnosed and identified before the age of 7. And by 7 years of age, about 13% of children in this test case were identified with a disability. Prevalence rate increases more steeply between the age of 4 to 7, due to some disabilities like psychosocial disabilities and being diagnosed only until later in the early ages of childhood.
[Text on screen reads, ‘Disability type percentage’. Screen shows another line graph. This time, there are 5 differently-coloured lines. A navy blue line is used to represent physical and diverse disabilities. A green line is used to represent intellectual and learning disabilities. A blue line is used to represent sensory and speech disabilities. A light blue line is used to represent psychosocial disabilities. A purple line is used to represent other disabilities. Speaker provides further explanation of the data.]
This is a similar graph to the previous one, but is a proportion of children with disability by the 5 disability subtypes for each age band. We see that, as mentioned, intellectual and learning disabilities, the green line at the top here, is proportionally the dominant disability subtype for nearly all ages, with a particular increase around the ages of 3 to 5. Notice how physical and diverse disability is proportionally dominant at the very early stages of childhood, relative to the other disability subtypes. This is likely due to the other disability subtypes, like psychosocial disability, tending to present themselves at later stages of early childhood, as shown here with an upwards trend in the light blue line.
[Text on screen reads, ‘NSW developmental vulnerability prevalence’. Screen shows a new line graph. This line graph demonstrates the percentage of developmental vulnerability in 2 or more AEDC domains between 2009 and 2018. Speaker provides further explanation of the data.]
So this is the developmental vulnerability prevalence rate across AEDC years in the cohort of children present in our AEDC records that were supplied. As we all probably know, the AEDC is a census carried out every 3 years, with our data consisting of censuses collections from 2009 up until 2018.
[Speaker points to a table on the screen. The table shows the 4 AEDC categories. The categories are:
Vulnerable – zero to tenth percentile
At risk – 11th to 25th percentile
On track – 26th to 50th percentile
On track – 51st to 100th percentile.]
There are 5 AEDC domains, each with 4 categories, ranging from vulnerable to on track, as shown here. Vulnerability on each domain is defined as scoring less than the 10th percentile cut-off score, set in the 2009 census.
So as you can see, the rate of being developmentally vulnerable has remained fairly constant throughout the years. In this presentation, we will only focus on the vulnerable category. And in the later slides, I will talk about the AEDC analysis in greater detail, where the data set was used as both an outcome and as an indicator in our NAPLAN analyses.
[Screen reads, ‘AEDC data in the NDDA’. On the left side of the screen, there is a summary of the findings from the AEDC data. The text reads, ‘Of the 462,124 children with an AEDC record:
5.7% were classified as having special needs and therefore have no valid domain-level AEDC data
9.8% were identified as developmentally vulnerable overall (DV on 2 or more domains).
Of those with a valid domain-level AEDC record (n equals 434,892):
15.1% were identified with a disability from other record sets before the age of 7
24.4% were from a non-English speaking background
27.4% were from a regional or remote area (not major cities) in NSW
21.4% were from areas of the lowest quintile of socioeconomic disadvantage index (SEIFA).’
On the right side of the screen, there is a pie graph. According to the graph, 49% of developmentally vulnerable children are vulnerable in 2 domains, 27% are vulnerable in 3 domains, 16% are vulnerable in 4 domains and 8% are vulnerable in 5 domains.]
And here is a more detailed summary of the AEDC data supplied, just mainly for your reference. Note nearly half of our developmental vulnerability group consists of children vulnerable on 2 domains, here to the right. I'll come back to this in the modelling, but note about 5.7 of the children in our AEDC records were special needs and were removed from analysis, according to this first dot point here.
[Screen reads, ‘Cohort summary. Total test case population: 2.33 million NSW children born between 2003 and 2019’.]
So to sum up our cohort, by 7 years of age, approximately 13% of the children in our test case were identified with a disability, of which more than 1 in 4 had multiple disabilities, and more than 1 in 2 had an intellectual and learning disability.
Disability was most commonly identified in the MBS data set, which identified around 66% of children with disability in our cohort. This means that if we had access to the MBS data at an early stage of early childhood, before preschool age for instance, we could possibly allocate more resources for early intervention.
[Screen reads, ‘Health, early childhood, school and social support usage’.]
In the next 4 slides, I will quickly talk about what the service usage pattern was for children with disability and developmental vulnerability, relative to the children in our cohort that were without disability.
[Text on screen reads, ‘Health support usage’. Screen shows a set of column graphs. These graphs demonstrate the percentage of children accessing health support services, including NSW Emergency Department presentations, NSW hospital admissions, MBS mental health services and MBS GP services. The data is grouped according to whether the children have any disability, a developmental vulnerability or no disability. In each group, there are 4 columns representing the 4 different services. Speaker provides further explanation of the data.]
For health service usage, almost all children with disability and developmental vulnerability access GP services before the age of 7, and proportionally more children with disability and developmental vulnerability accessed hospital services.
[Speaker points to the part of the graph that focuses on children with no disability. There are only 2 columns in this section.]
No data was available for the Medicare Benefits Scheme, the MBS data, services for the sub cohort of children with no disability because of the flagging of the children for whom the Commonwealth data was provided, to researchers, hence the missing bars here on the right.
[Text on screen reads, ‘Early childhood education usage’. Screen shows a new set of column graphs. These graphs demonstrate the percentage of children accessing early childhood services, including community preschools, government preschools, centre-based day care and any early childhood education centre. The data is grouped according to whether the children have any disability, a developmental vulnerability or no disability. Speaker provides further explanation of the data.]
For early childhood education usage, we are very glad to see that proportionally more children with disability accessed ECE services than the other two groups. This is likely a result of target disability supports in the ECE sector.
[Text on screen reads, ‘School support usage’. Screen shows a new set of column graphs. These graphs demonstrate the percentage of children accessing school-based services, including integration funding support, specialist support classes, schools for specific purposes and mainstream classes. The data is grouped according to whether the children have any disability, a developmental vulnerability or no disability. Speaker provides further explanation of the data.]
For school service usage, we see that proportionally more children with developmental vulnerability attending schools for specific purposes, relative to the other 2 groups. So right here. Children with disability were well represented within the mainstream classes. This is likely a result of school disability-targeted supports enabling children with disability to attend mainstream classes, as well as part of the inclusive education policies.
[Text on screen reads, ‘Social support usage’. Screen shows two sets of column graphs. The first set of graphs shows the percentage of children who have a child protection contact. This data is grouped according to whether the children have any disability, a developmental vulnerability or no disability. The second set of graphs shows the percentage of children with a specific disability type, including physical and diverse disabilities, intellectual and learning disabilities, sensory and speech disabilities, psychosocial disabilities and other disabilities. This data is grouped according to whether students have no risk of significant harm, unsubstantiated risk of significant harm, substantiated significant harm or are in out of home care. Speaker provides further explanation of the data.]
Lastly, for social service usage there was an over-representation of children with disability and developmentally vulnerability amongst children with at least one child protection services contact, relative to children with no disability. Among the children with disability, intellectual learning and psychosocial disabilities were consistently overrepresented across levels of social support severity, ranging from non-rush, non-risk of substantial harm report, to out-of-home care replacement.
[Screen reads, ‘AEDC modelling’.]
In the next 7 slides, we will take a fairly detailed look at the AEDC modelling analysis, where we will explore questions regarding the impact of ECE type and hours, as well as risk factors for developmental vulnerability.
[Text on screen reads, ‘AEDC modelling details’. Screen shows a flowchart that outlines how students were sorted into their comparison groups. It demonstrates that there were 2,330,929 children at the start of the process. 1,868,805 children were then excluded, as they had no AEDC records. From here, an additional 26,349 students were excluded, as they were classified as having special needs on the AEDC. A further 883 children were then excluded due to incomplete covariate data. This left the sample with 434,892 children. Of these children, 369,036 were placed in the ‘no disability’ comparison group, and 65,856 were placed in the ‘any disability’ comparison group.]
Here's the flow chart to classify our analysis groups, used to measure the impact of disability on developmental vulnerability. To be part of our analyses, the children needed to be, of course, in the AEDC data set and not be classified as special needs, nor have incomplete covariate data, which I'll show on the next slide. Now as mentioned earlier, the main hurdle we faced was the removal of children classified as special needs. And hence no domain scores were supplied for these children to us.
Fortunately, due to the linked nature of the asset with other disability data sets, we were still able to capture a considerable number of children, before the age of 7, with disability, within the AEDC data set. But however, this removal of children classified as special needs will likely underestimate the risk factors for children with disability – something to keep in mind when looking at the results coming up.
[Text on screen reads, ‘AEDC modelling details’. Screen shows a table of the outcomes and covariate results from the AEDC modelling. Speaker provides further explanation of the data.]
Here's the counts and distributions of outcomes and covariates used in our modelling. We use developmental vulnerability in all 5 AEDC domains, and covariate data capturing child sex, language background other than English (LBOE), remoteness and socioeconomic disadvantage indicators. Perinatal data was also considered as potential covariance, but due to low counts, we had to exclude these from our current analyses.
[Text on screen reads, ‘Odds of vulnerability on each AEDC domain for children with disability’. Screen shows a column graph that matches the content of this text. Speaker provides further explanation of the data.]
So to get an overall picture, let's jump straight into the results. Presented here are adjusted odds ratios of vulnerability for children with disability from the logistic regression analyses, which adjust for the covariates using children without disability as the reference group. Down here. In general, the children with disability have nearly 2 to 3 times the odds of being vulnerable on any one or more AEDC domains, more than the children without disability. And you'll notice, to the right of the dashed line, there is a similar scaling for vulnerable on one and 2 or more domains.
[Text on screen reads, ‘Disability type risk factors for scoring vulnerable on each of the 5 AEDC domains’. Screen shows a set of column graphs. These graphs demonstrate the adjusted odds ratios for children with a disability according to their disability type. The data is grouped according to whether children have a physical or diverse disability, an intellectual or learning disability, a sensory or speech disability, a psychosocial disability or a different disability. In each group, there are 5 columns that represent the 5 AEDC domains. Speaker provides further explanation of the data.]
Now, if we break disability into the 5 disability subtypes for each of the 5 AEDC domains, we get a much richer picture of the severity of disability in terms of scoring vulnerable on each of the domains. Again, we see that universally, children with disability are over 2 times more likely to score vulnerable on any one of the 5 AEDC domains, with physical and diverse having the highest odds. What's interesting here is that for a given disability subtype, for instance, intellectual learning, the odds are roughly similar across the AEDC domains, with the exception of psychosocial disability, where it's more strongly associated with vulnerability on the emotional maturity and social competence AEDC domains.
[Text on screen reads, ‘Effect of ECE type on likelihood of developmental vulnerability’. Screen shows 2 sets of bar graphs. Both sets demonstrate the adjusted odds ratios for children who are developmentally vulnerable in a number of the AEDC domains. The first set of graphs shows how enrolment in an Early Childhood Education service influences developmental vulnerability. These service types include community preschools, government preschools, centre-based day care and other Early Childhood Education services. The second set of graphs shows how other factors influence developmental vulnerability. These include any disability, male sex, a language background other than English, inner and outer regional locations, remote and very remote locations, and socioeconomical disadvantage. Speaker provides further explanation of the data.]
Now, it's not all bad news. The good news is, what we find in our research is that ECE enrolment generally leads to a decreased likelihood of developmental vulnerability, compared to children who didn't enrol in an ECE service, as showed in this adjusted odds ratio graph. So after accounting for all the covariates listed below the solid black line, which includes sex, language background, et cetera. The odds ratio bars pointing to the left are less than one, and hence are protective factors. And the bars pointing to the right, greater than one, are risk factors. So as you can see, 3 out of the 4 ECE types are pointing to the left, indicating ECE enrolment in these types of services generally leads to a decreased likelihood of developmental vulnerability, with community preschool having the most prominent effect.
[Text on screen reads, ‘Effect of ECE hours on likelihood of developmental vulnerability.’ Screen shows 2 sets of bar graphs that are similar to the previous slide. In these graphs, the data is organised according to children who spend less than 600 hours in an Early Childhood Education service and children who spend 600 hours or more in an Early Childhood Education service. Speaker provides further explanation of the data.]
How does ECE hours affect developmental vulnerability? So this is a similar graph as to the previous one, with each ECE type is now a coloured bar. We were able to investigate a rough dosage effect, with ECE hours split by less than 600 enrolled annual hours in the year before school, and 600 or more enrolled annual hours in the year before school. Again, we see a consistently positive result associated with being enrolled in more than 600 hours in ECE services that offer a preschool programme in line with the department's Start Strong policy.
Attending hours was not able to be used, as this information was only available for the centre-based daycare from about 2018 onwards. Hopefully this will change as the department will soon be upgrading their backend systems to collect more detailed and thorough child attendance data.
[Screen reads, ‘AEDC summary.
Children with disability were 2 to 3 times as likely to be developmentally vulnerable in one or more AEDC domains, relative to children without disability.
Odds for scoring ‘vulnerable’ were not significantly different across AEDC domains for each disability type, except for psychosocial disability.
Psychosocial disability affects the emotional maturity and social competence domains the most.
ECE enrolment generally led to a decreased likelihood of developmental vulnerability, with community preschool having the most effect.
600 hours or more of ECE enrolment generally decreased the likelihood of developmental vulnerability.’]
Here's the summary for our AEDC analysis. It's all presented here. There's much more in the full report for those interested, but generally, children with disability are 2 to 3 times as likely to be developmentally vulnerable on one or more of the AEDC domains. And our modelling suggests that there is a very strong ECE enrolment protective effect in the year before school.
[Screen reads, ‘NAPLAN modelling’.]
And finally, we'll turn to our NAPLAN Grade 3 modelling, where I'll address questions around the risk factors for NAPLAN performance and whether ECE enrolment makes a difference in this space.
[Screen reads, ‘Children with developmental vulnerability performs more poorly in NAPLAN’. Screen shows a set of bar graphs that demonstrate the odds of students achieving below the National Minimum Standard according to whether they have any disability or a developmental vulnerability. Speaker provides further explanation of the data.]
Both disability and developmental vulnerability increase the chance of achieving below the national minimum standard in NAPLAN at Grade 3. Here we show their impact on numeracy and reading domains, as well as the overall impact on the any NAPLAN domain in Grade 3. We see that the effect of developmental vulnerability is almost twofold compared to children with disability. This alone would suggest that we need to be able to identify children with developmental vulnerability as soon as possible, preferably before the first year of school, to ensure our adequate support is provided to these children before schooling age.
[Text on screen reads, ‘Predictors of NAPLAN results – Developmental vulnerability’. Screen shows a set of bar graphs that demonstrate how different factors influence the odds of children achieving the National Minimum Standard. These factors include developmental vulnerability, male sex, remoteness to major city, a language background other than English, socioeconomic disadvantage, low birthweight, preterm birth and prenatal smoking exposure. Speaker provides further explanation of the data.]
Even when accounting for covariates, the adjusted odd ratios, the red bars here, the children with developmental vulnerability are still over 4 times as likely to achieve below the national minimum standard, compared to their peers without developmental vulnerability. Perinatal data was able to be used this time in our modelling. So covariate risk factors of NAPLAN Grade 3 performance now include low birth weight, preterm birth and prenatal smoking exposure.
[Speaker points to the section of the graph that represents students with a language background other than English.]
However, recall that language background other than English was a risk factor in the AEDC analyses. It went from being a risk factor then, to in the first year of school, to now a protective factor in the fourth year of schooling, shown here.
[Text on screen reads, ‘Predictors of NAPLAN results – Disability’. Screen shows a set of bar graphs that are similar to the previous slide. This time, the graphs demonstrate the adjusted odds ratio for reading and numeracy. Speaker provides further explanation of the data.]
Now, if we quickly look at a similar modelling done using children with disability, versus those children without disability, we see again a very similar pattern shown previously. Note here, the blue bars are the adjusted odd ratios on the NAPLAN reading domain. And the red are the numeracy domain.
[Speaker points to the section of the graph that represents students with a language background other than English.]
Again, a very similar story, however, LBOTE covariate it now plays a split role, just here, as both a protective factor and a risk factor for the reading and numeracy domains respectively, which is an interesting split.
[Text on screen reads, ‘NAPLAN modelling by disability type’. Screen shows a set of bar graphs that demonstrate the odds of children achieving the National Minimum Standard in NAPLAN. The data is grouped according to whether a student has a physical or diverse disability, an intellectual or learning disability, a sensory or speech disability, a psychosocial disability or another disability. Speaker provides further explanation of the data.]
What about NAPLAN Grade 3 performance for the 5 disability subtypes? Interestingly, our modelling suggests that psychosocial disability is the smallest risk factor among the 5 disability subtypes for NAPLAN Grade 3 performance.
[Text on screen reads, ‘Effect of ECE type on NAPLAN’. Screen shows 2 sets of bar graphs. The first set of graphs show how enrolment in an Early Childhood Education service influences the odds of children achieving the National Minimum Standard. The second set of graphs show how other factors influence the odds of children achieving the National Minimum Standard, including male sex, remoteness from a major city, a language background other than English, socioeconomic disadvantage, low birthweight, preterm birth and prenatal smoking exposure. Speaker provides further explanation of the data.]
So despite NAPLAN being several years away from ECE age, early childhood education age, the effect of ECE is still relatively strong for community preschool. For both children with and without disability, shown here in the blue and red bars respectively.
[Description not needed. The visuals in this part of the video only support what is spoken; the visuals do not provide additional information.]
Here is the summary of our NAPLAN analyses, with developmental vulnerability being more strongly associated with achieving below the national minimum standard, and out of the 5 disability subtypes, psychosocial disability being the smallest risk factor for NAPLAN Grade 3 performance. It was also great to see community preschooling having a positive effect on NAPLAN performance in our analyses.
To wrap up, there are 3 main policy implications here. And of course, you can draw more on your own conclusions depending on your policy needs. First, we find that receiving supports early in life really makes a difference in the reduction of the impact of disability and developmental vulnerability. It builds skills and independence, and could potentially reduce the extent of supports needed later in life. Second, we recommend additional supports to be provided to developmentally vulnerable children, to boost their literacy and numeracy skills. Third, it is very crucial that we identify these developmentally vulnerable children as early as possible, so that we can ensure adequate support is provided to those in need before school age.
So the main message is that if a child does not have 600 hours of quality early childhood education, then they are then at an increased chance of being assessed as developmentally vulnerable in the AEDC, which in turn means they are 4 times more likely to fail to achieve the national minimum standard in NAPLAN Grade 3.
[Screen reads, ‘Acknowledgement. The presentation uses population data owned by:
Australian Government’s Department of Health
Australian Institute of Health and Welfare
Department of Education, Skills and Employment
Department of Social Services
National Disability Insurance Agency
NSW Department of Education
NSW Department of Communities and Justice
NSW Ministry of Health
NSW Registry of Births, Deaths and Marriages.
This presentation also uses data from the Australian Early Development Census (AEDC). The AEDC is funded by the Australian Government Department of Education Skills and Employment. The findings and views reported are those of the author and should not be attributed to the Department or the Australian Government.
The project team acknowledges the assistance provided by the Centre for Health Record Linkage (CHeReL) and the Australian Institute of Health and Welfare (AIHW) in relation to this project.
NSW Department of Customer Service – Test Case implementation
Dr Celia Walker, NDDA Test Case Implementation Lead
NSW Department of Education, Early Childhood Education and Schools Policy
Mr Steven Gibbs, Manager, ECE Data and Research
Ms Keisi Cheung, Principal Data Analyst, ECE Data and Research
Dr David Gummersall, Data and Research Officer, ECE Data and Research
University of New South Wales, School of Psychiatry – Research Team
Professor Melissa Green
Dr Gabrielle Hindmarsh
Dr Joe Giorgio
Ms Felicity Harris’.]
So thank you all for listening. And I would like to thank again the whole project team, and especially the University of New South Wales team, listed here in the bottom right, who we worked really closely with to help make our early childhood test case such a success.
[Video concludes by displaying the NSW Government logo.]
[End of transcript]
Research in practice
These presentations highlight how educators and leaders in education have used the AEDC to inform planning and practice within in an educational setting.
Group 1 – schools
This presentation highlights the beginning of the journey in establishing strong community partnerships to support transition from Early Childhood to Kindergarten. Engagement with data can increase a sense of shared community responsibility and awareness of ways to support and manage early identification and intervention transition to school processes.
Watch 'How AEDC data was used to establish and support the management of transition to school processes' (23:15)
(Duration: 23 minute 15 seconds)
[Screen reads: AEDC Symposium August 2022.]
[Screen reads: The journey so far … Albury – Early Childhood Community of Practice.]
Before I begin today's presentation, I would like to acknowledge that I am meeting with you today from the lands of the Wiradjuri people. I also acknowledge the traditional custodians of the various lands on which you all meet with us today. And pay respect to Elders past, present, and emerging, and extend that respect to other Aboriginal people, and all of our colleagues joining us today.
My name is Teagan Sawyer, I'm the Assistant Principal Learning and Support for the Albury Network. And this presentation highlights the beginning of our journey in establishing strong community partnerships to support transition from early childhood education settings into Kindergarten. Engagement with data has supported our increased sense of shared understandings of our community responsibilities and awareness of ways to support and manage early identification, referral, and intervention for the young people in our community. Particularly, transitioning into Kindergarten in our Albury Public Schools.
[Description not needed: The visuals in this part of the video only support what is spoken; the visuals do not provide additional information.]
[Screen reads: Where did we start? P – K transition.]
Where did we start? I'd like to acknowledge the importance of a successful transition to school. We know that this is considered a significant event for both the children that we teach and their families. It is one that has a considerable impact on a child's long-term wellbeing, academic, and social outcomes throughout their life.
We acknowledge that the impact of COVID after the last 2 years has seen a decline in transitional experiences and communication between key stakeholders in early years settings and our primary schools. Our local schools had voiced difficulties faced with newly enrolled students presenting with high or complex support needs. In late 2021, Albury and Wagga Wagga Delivery Support Teams established a working party with a specific focus on preschool to Kindergarten transition points.
I sought some early data for our network based on the 2021 School Snapshots that were shared with me by our local principals. In previous years, there had been networks, including educational leader networks and community networks that were established, but often happened haphazardly across the community. And coming out of COVID-19, it was a timely moment for us to start networking as a community again.
[Screen reads: Why did I engage with the AEDC as a source of information.]
The reason I engaged with the AEDC data as a source of information to support this project and body of work was early in 2021, I completed the AECD data collection as a Kindergarten classroom teacher. Previously at my base schools, we had looked at School Snapshots to reflect on the current and sometimes changing needs of our Kindergarten cohorts.
My new role as Assistant Principal Learning and Support had to focus on supporting the broader community and strengthening community understandings and partnerships, particularly in the area of transition, preschool to Kindergarten.
Seeking data to capture the implications of COVID-19 on transition, early identification, referral and support is quite challenging. However, we could observe that practices and transition to school had been severely disrupted by school closes and social distancing regulations.
There were a number of challenges for children, their family, schools, and early childhood education services. The impact on children with special educational needs, disabilities, and children from disadvantaged backgrounds, particularly, had a greater negative impact on their successful transition to school. This has been caused by the lack of face-to-face contact, it has affected the building of relationships, reduced opportunities for children and their families to visit schools and establish strong relationships. There was limited collaboration between schools, early childhood services, and support services with educators, and school teachers, and support staff being unable to observe in both settings. Access to intervention services, such as speech and language therapy had also been restricted in some cases.
I'd like to note that by having clearer expectations and timelines for all stakeholders coming out of COVID-19, we will be able to support a more successful and smoother transition process for our future children and students. As a classroom teacher, a learning support teacher, and now supporting the wider Albury Network of Schools, the AEDC provides important information for communities and our schools to support our planning and service provisions.
The early environments and experiences children are exposed to shapes their development. So, it is in our communities’ interest to work together collaboratively of what we can do, particularly the 6 to 12 months prior to beginning Kindergarten, and in the 3 year old and 4 year old preschool groups is where we have been focusing our body of work.
It has been helpful to identify what has been done well in our community, what can be improved, and initiating, and perhaps re-establishing and forming partnerships. It has been pleasing to be able to initiate and support these conversations with leaders within the community. I have initially met with community health allied services, speeches, occupational therapists, and our directors in our community preschools, who some may not have been aware of the AEDC in the past, and particularly not aware that anyone can access the community profiles, which is really rich data for our community. And the way that we plan to implement activities, programs, and services to help shape the future of the wellbeing of the children within our Albury and surrounding communities.
[Screen reads: Community Snapshot.
Information about children in this community
Table 1.1 – Demographic information about this community.
Screen shows: a table displaying demographic data for this community over the last 3 AEDC data collection periods – 2015, 2018 and 2021. In 2018, the total number of children measured is 678, compared to 693 in 2021.]
[Teagan provides a further explanation of the data.]
When looking at our Community Snapshot, you will see that the total number of children measured hasn't increased significantly between the years of 2018 to 2021. Our Community Snapshot covers 9 subcommunities within Albury. This includes Albury and South Albury, East Albury, Glenroy, Lavington and surrounds, North Albury, Springdale Heights, Table Top, Thurgoona, and West Albury.
[Screen reads: Special needs.
Table 1.4 – Support.
Screen shows: a table displaying types of support required or identified in this community over the last 3 AEDC data collection periods – 2015, 2018 and 2021. In 2018, there are 48 children with a special needs status, compared to 35 in 2021. In 2018 there are 133 children identified by teachers as requiring further assessment, compared to 186 in 2021.]
[Teagan provides a further explanation of the data.]
In Table 1.4, you'll see that children with a formal diagnosis or special needs status did not increase. In fact, there was a slight decrease between 2018 and 2021. However, children identified by teachers as requiring further assessment, flagging or support, whether that be medical and physical, behaviour management, emotional or cognitive development, had increased quite significantly between the years of 2018 and 2021.
There was an increase of 53 students identified as needing further support and assessment. This was an increase of 7.6% between 2018 and 2021. And the information such as this is the information that our team as delivery support can use when working with our Early Stage One teachers and our transition to school coordinators within our schools.
It was also really important information for us to be able to share with our allied support services, our program coordinators and leaders, for them to know where they can target their support, particularly in the breakdown of our 9 subcommunity areas, and looking at the differences between averages and numbers in different parts of our wider community.
We know that school readiness is a widely accepted and multidimensional concept, and includes the capacity of families, communities, and services to provide the necessary opportunities, conditions, and support to optimise children's learning and development, particularly the individual needs of children, such as these 53 Kindergarten students, who were identified across our schools as requiring additional support and assessment in key areas.
[Screen reads: Key findings.
Screen shows: AEDC physical health and wellbeing domain icon and AEDC emotional maturity domain icon.]
Some other key findings from our community profile was that in physical health and wellbeing, 72.3% of children were on track, which was the lowest since 2009. 16.4 were at risk, which was an increase since 2015 and 2018 collections. Vulnerable had no change. In emotional maturity, there was a slow decrease. In emotional maturity, there was a slow decrease in children who were on track across this domain.
[Screen reads: Key findings.
Screen shows: language and cognitive skills (school-based) domain icon.]
In language and cognitive skills, the amount of children on track showed a slow increase. Children at risk were 13%, which was an increase of 4.6% since 2018. And children in the vulnerable categories had shown a slight decrease.
[Screen reads: Comparison to NSW and national data.]
When comparing our Community Snapshot to New South Wales and national data, less children were identified as on track in physical health and wellbeing, and there was a slightly higher proportion of children in at risk or vulnerable status.
Less children were identified as being on track in social competence. And there was a slightly higher proportion of children at risk or vulnerable.
There were similarities with language and cognition skills compared to past data collections, but there were less children identified as on track in emotional maturity, and slightly higher proportion of children at risk or vulnerable across this domain.
There were slightly more children vulnerable in communication skills and the general knowledge domain. And this has been reflected during robust conversations about educators and school leaders, acknowledging that there has been a shift in some of our cohorts, and the way that children are presenting during transition to school programs, and in their first year of schooling.
Developmentally vulnerable on 2 or more domains were slightly higher than national averages and New South Wales averages. Again, as we have been engaging in discussions looking at our community data, there are parts within our subcommunities, where this is actually higher in some of our areas, where more children are at risk or vulnerable in parts of our community, more than others.
The data suggests that there was a 6% decrease in children who were actively read to within the home environment. Potentially, we could liaise with our Albury City and our local libraries and advertise playgroups and the library sessions to areas of the community where this might be applicable.
Are there innovative ways that we can ensure that our families are well informed about what is available in the community? And what a successful transition looks like? What does quality care and learning look like across our early years learning settings? Does the community have well-established referral pathways for connecting families to service and support they may require? And does the community have well-connected services that work collaboratively to deliver programs across systems and sectors? And we hope that we are at the beginning of this journey.
[Screen reads: How has this information been shared? Data to inform shared community considerations.
Screen shows: an image taken at a P-K transition session in March 2022.]
The information has been shared to inform shared community considerations and planning for the future by acknowledging the different strengths of our community and our community members, we can strengthen our preschool to Kindergarten transition. We held sessions held by our Department of Education staff for our early childhood education services and leaders.
We have liaised with allied health professionals to share this data, and the implications for our teams, and for our schools. We've liased with NDIS program man managers and coordinators for the Albury Area, and are providing ongoing professional learning opportunities for Early Stage 1 staff in our local primary schools. For the remainder of this semester, we would like to see strengthened community partnerships, liaising, and having guest speakers in areas of interest, and a focus coming out of the Community Snapshots.
We have held a face-to-face session, virtual sessions, and catch up sessions, one-to-one, with people who have showed interest in learning more about the AEDC, and the way that our team is strengthening timelines to support transition, particularly for students who are at risk or vulnerable across domains, or are presenting with high or complex needs.
[Screen reads: How has this information been shared? Public facing resources and information to build shared and consistent understandings.]
One way that we have done this is by sharing the public facing resources on the Department of Education website to build shared and consistent understandings. Some of these include the starting school with additional needs platform, which you can see pictured to the left.
[Screen shows: screenshot of the ‘Starting school with additional needs’ webpage on the Department of Education website.]
Your child's personal timeline to enrollment is part of the Parents and Carers hub, in which you can put your child's birth date, and it will generate your local school from your address and information. It gives parents and carers really prescriptive steps on how they can make contact with their local school for further information and support.
Likewise, with the school finder tool, choosing where your child will learn is another part of this starting school with additional needs website. And it goes into the different models of learning and support that can take place in our local public schools, whether that be beginning in a mainstream school with integrated funding support. Or perhaps depending on the degree of need, the child may be applicable to go forward with an access request to get placement in a support class within our mainstream school, or a school for specific purposes. There's information on early intervention and support, as well as transition and orientation programs and support resources.
A new resource that has been valuable to share across all of these settings and stakeholders has been our inclusive practice hub. Where possible, we have encouraged our local community members, early childhood services and allied support to share these within their newsletters and within their social media platforms, so that consistent messaging is getting out to our community about what our public schools.
Where possible, we have encouraged our early childhood providers, as well as our allied support services and community health to share some of these resources in their newsletter or on their social media platforms, so that consistent messaging is going out into communities, and gaps are being met in the community and community understandings.
We have created a timeline that shows the responsibilities of the early childhood education services, and then the responsibilities of the local school in supporting the transition to school journey, particularly for children with high or complex needs. We have digitised previous forms to allow for easier access and usability for our colleagues in the early childhood. Already, we have a number of referrals through that we are able to share with our local school principals and start liaising with families and early childhood services to strengthen and support the individual needs of children coming to school in 2023.
We know that sharing information facilitates a successful transition. And we know that our early childhood services and families support and facilitate a child's transition, they know them best and can advocate for the voice of the child and the family. They have information about the child's existing knowledge, skills, and strengths. Information in the past may have been received too late to be useful.
In the past, it was noted that some information was being received too late to be useful. We have tried to be proactive in this space to allow the information to be received 6 to 12 months, prior to the child beginning school. Written information and combination. Written information combined with other transition practices, such as verbal conversations, community information sessions, and site visits, give educators from all sectors the opportunity to clarify information, ask additional questions, and establish strong partnerships as a community.
[Screen reads: What is the impact? What will the journey look like into 2022, 2023 and beyond?]
In time, we would like to see that there is an increase in continuity of learning between settings for children, and the sharing of information between all stakeholders. Collaborative partnerships with families and communities is a quality area in the National Quality Standards. And these quality area notes that collaborative partnerships promote continuity of learning and support transitions for all students.
Preschool to Kindergarten transition professional learning for identified transition contacts in all local primary schools is taking place in Week 2, Term 3. Increased partnership and collaboration between stakeholders in the community who support school readiness and key transition points is already being noted and shared amongst our services.
We are seeing improved practices and ongoing reflection and collaboration between teams to support individual transition of students for 2023. We are able to have robust discussions around what is working, and what requires strengthening and consistency across the community.
Our teams will continue to advocate for successful transition to school to lay strong foundations for positive partnerships and relationships with our families. This will support ongoing engagement for their child's learning. We also hope to support factors, including home learning environments, high quality early childhood, classroom and school environments, and effective collaboration between key stakeholders within the community. We need to adapt to the diverse needs of each child and their family, and meet them where they are at.
[Screen reads: Where to next? Plans for Semester 2, 2022 and into the future.]
The Australian Early Development Census has been the perfect platform to support our work, and the strategic goal of the Department of Education, where all children make a strong start in life and learning, and make a successful transition to school. A successful transition to school is about laying strong foundations for year-on-year improvement, by ensuring that our students are engaged and ready for challenge. The AEDC has offered us informative data to be able to target the needs of our community as times shift and cohorts change.
AEDC community data has worked hand in hand with the work that we will be doing for the reminder of Semester 2, 2022, and into the future. This semester, we will focus on the literature review on transition to school from the Centre for Education Statistics and Evaluation to support ongoing learning in the area of transition, with a clear focus on the areas identified in our community profile.
As a team, we are working to support the New South Wales Department of Education's strategic goal of all children making a strong start in life and learning, and making a successful transition to school. We know a successful transition to school is about laying strong foundations for year-on-year improvement, by ensuring that our students are engaged and ready for a challenge.
I look forward to leading the collaboration in the development and implementation of ongoing community planning that strategically provides vision and direction for our early year service provision within the community, and within the transition to school phase for the children within our community, and future leaders and learners of our country.
I look forward to continuing to lead and liaise with our community members to collaborate in the development and implementation of a community plan that strategically provides vision and direction for years to come, and helps to shape the future and wellbeing of children within the Albury Community and surrounding areas.
Thank you for your time today.
[Video concludes by displaying the NSW Government logo.]
[End of transcript]
Group 2 – Early childhood education services (ECE)
At Kurri Kurri and District Preschool, the 2018 AEDC data was used to enhance curriculum decisions to best meet the needs of children in our community. Using the data and connections with local organisations in the community, a series of initiatives were developed to focus on the vulnerabilities identified in the local community profile. These initiatives included a weekly ‘walking bus’ to the library, a partnership with university occupational therapists and funding secured as part of a local community partnerships grant.
Watch 'How AEDC data was used to enhance curriculum decisions to best meet the needs of children in the community' (8:19)
(Duration: 8 minutes 19 seconds)
[Text on screen reads, ‘AEDC Symposium. August 2022’. Screen shows the speaker, Nicci McDowell.]
Hi, my name is Nicci McDowell, and I am here today representing Kurri Kurri and District Kindergarten and Preschool. I'm coming from you today from the magical meeting place of the Wonnarua, Awabakal and Darkinuug people, and I pay my respects to all Aboriginal people past, present, future and joining us here today.
So I'm here today to talk a little bit about how, at the preschool, we used AEDC data in a variety of different ways. I think it's really important to note that for us, the data was just one piece of a pedagogical puzzle. We use many, many different types of information to inform our teaching and our practice, and the data from AEDC is just one element of that.
However, what the data has given us is an opportunity to have a more formal analysis of all the anecdotal evidence that we collect about our children in our community and that attend our preschool. And in particular, it really highlights what strengths and their challenges might be. And what we've found is that when we compare our in-practice knowledge to the AEDC data, some of the insights that we are forming and some of the initial understandings that we had, particularly about children's vulnerabilities, are confirmed to us through the data.
An example of this is how we used the 2018 AEDC community profile for our area. So in those years, when the children began attending our preschool, and as we got to know them, we could see through our observations of their play that some of these children were really challenged to engage in our physical environment. And what we also observed was that many of these children were very difficult to understand. So their speech and language wasn't particularly clear. And when we looked at the data from the AEDC, we could see that our anecdotal evidence and the observations that we'd collected matched the data from our community profile. So we could see in the data that children from our community were more vulnerable than other children across New South Wales and across Australia in the domains of physical development and language development.
We were then able to use this information to build in our planning and our curriculum. At the preschool, we had a really skilled and high skilled level of professionalism, and we could already offer lots of high quality learning experiences to support these children. But what we did is we began to reach out for other ways that we could enhance this. And we put some initiatives in place to support the children to learn across these areas of vulnerabilities.
The first initiative that we put into place was a collaboration with our local library. So we know that children's language is strongly influenced by literacy experiences, and there's no other better place than a local library to offer this. So with lots of planning, our goal was for every child at the preschool to have a library card and to be able to access high quality picture books to support their language development.
We approached this in many different ways. Initially, the library staff came to the preschool and they talked to the families about the importance of reading books to young children. The librarians also spent time with the children at the preschool to introduce themselves and begin to make connections to support their learning. And then once all of the children had a library card, we began our weekly trip in small groups to the library. While we were at the library, the librarians would read stories to the children. They would choose their own stories to borrow and take back to the preschool and back home, and they could engage with them there. It was a wonderful way to engage children in some really high quality language experiences.
The second part of our plan was how we would get to the library. So in the town, the library was approximately a 3 kilometre round trip from the preschool. So with all the parent permissions and the right procedures followed and in place, and with lots of collaboration from the children so that they were informed as well, we decided we will make this trip on our walking bus – as in, we would walk. So initially, this took some children a very long time, but what it did give was an opportunity to use their movement skills and to put into practice some physical development skills and build up a physical stamina that we couldn't recreate inside the preschool gates.
And from these library walks we found that there were 2 wonderful positive engagements that occurred. The first was that the children wanted to walk more. So once they became familiar with our library walks, then they didn't want to return to the preschool. They wanted to explore more areas in the community and they wanted to keep walking. We took detours and we would explore, sometimes for up to half a day. The second was that we noticed that when we were out walking, there was a shift in the conversations we were having with the children. So our conversations became more sustained. They were rich in content and they had a much wider use of language from the children. So as well as our planned experiences, from this experience and this initiative, there were also these unplanned successes that we really celebrated.
Some other ways we've used the data beyond this is in our applications for monetary grants. So as a community-based preschool, we were able to apply for different programs to support our curriculum. And one of those was a grant to redevelop an area of our playground. So we know that to support children best with their physical domain of development, we could offer really high quality physical spaces. So in an application, we were able to quote the data to highlight the importance of providing high quality play spaces to children and to support their physical vulnerabilities. That was successful and we could make some updates and upgrades to our playground to support that for children.
We were then able to use this data again to secure some funding, which allowed for us to build a partnership with the University of Newcastle and their occupational therapy clinic. So as part of the program, we were able to have an OT come to the preschool along with 2 of the university student OTs. And that OT and those student OTs, they would engage with the children and they would support their skills in play, and they would support the staff at the preschool to build their capacity to play with children and best support physical development too.
These are just a few ways that we've used the data at the preschool. Obviously there's a lot of work that went in behind the scenes for this. But our commitment to using the data really impacted the outcomes for our children at the preschool. So for us, the next round is looking at the next round of data. And as a preschool, we're very eager to look and to begin to understand how the 2021 AEDC data can shape our practice and what it means for our community, and how we can plan to best meet the needs of our children.
[Video concludes by displaying the NSW Government logo.]
[End of transcript]
At Bermagui Preschool the AEDC has provided us with important information to guide our planning and service provision. It has supported us to create and implement early environments and experiences to shape children’s development and support and enhance positive outcomes for our children, families and broader community. At Bermagui Preschool we agree with the AEDC beliefs that investing time, effort and resources in children’s early years, when their brains are developing rapidly, benefits children and the whole community. We know that by providing stimulating environments and rich experiences it can fundamentally enhance brain development, boost a young child’s learning and have lasting effects on a child’s development, future learning, health, and life success.
Watch 'How AEDC data was used to establish and support the management of transition to school processes' (31:43)
(Duration: 31 minutes 43 seconds)
[Text on screen reads, ‘AEDC Symposium. August 2022’.
Screen shows a young child playing a didgeridoo. Screen reads, ‘Acknowledgement of Country’. Screen shows Narelle Myers on the trop-right, superimposed in a small box.]
Hello, and walaawani. My name's Narelle Myers and I'm here in Bermagui, on Djiringanj land, in the Yuin Nation on the far south coast of New South Wales. I'd like to acknowledge the Aboriginal and Torres Strait Islander people, who are joining us here today and pay my respects to Elders past, present, and emerging, from the many lands on which we gather today.
[Screen reads, ‘About Bermagui Preschool, Narelle Myers – Service Director’. Screen shows an image of Narelle on the left-hand side and a group of young children walking on a log, among nature, on the right-hand side.]
Originally from Perth in Western Australia, I've lived in the beautiful coastal village of Bermagui for over 20 years. On a professional note, I've fulfilled a career spanning 30 years in very context of early childhood education, including preschool, long day care, out of our school care, family day care, community service, outreach projects, both in Australia and abroad. I'm currently the Director at Bermagui Preschool here in Bermagui.
In response to our community needs, I've guided our small not-for-profit community based preschool from humble beginnings with only two staff and eight children, to a service that now facilitates four different early education and care programs, employs 16 staff, and has over a hundred children enrolled. Overcoming rural isolation and multiple challenges, I've guided our educators and preschool team to achieve a rating of excellence in the national rating and assessment process in 2019 and again in 2021.
We provide quality early education and care with a focus on enabling access and affordability to vulnerable people in our community. Including children from culturally and linguistically diverse backgrounds, children with additional needs, and children and families who identify as Aboriginal and Torres Strait Islanders.
As a strong advocate for early childhood education and the opportunities that affords our children, families, and the community as a whole, I value the chance for our children and families to access not just excellent, but outstanding educational opportunities. I believe the Australian early development census is an excellent tool to strengthen ourselves as educational leaders and our teams to feel supported and well resourced to undertake our roles and inform our practise.
At Bermagui Preschool, the AEDC has provided us with important information to guide the planning and service provision. It's supported us to create and implement early environments and experiences to shape children's development and support and enhance positive outcomes for our children, families, and the broader community. It's also helped to validate understanding of what quality education should look like for our community. As well as a tool to support our work in advocacy, funding, applications, and quality improvement planning.
At Bermagui Preschool, we agree with the AEDC's belief that providing stimulating environments and rich experiences, can fundamentally enhance brain development, boost a child's learning and have lasting effects on child development, future learning, health and life success. It's been an honour to be invited to share our experiences in regards to the AEDC. And I'm excited to highlight how we've enacted this at Bermagui Preschool in the following presentation.
[Screen reads, ‘About CELA: Community Early Learning Australia’ with a CELA logo on the top right.]
Before I share Bermagui Preschool's experience, I'd like to mention CELA, Community Early Learning Australia for whom I do some freelance work. Community Early Learning Australia is a peak body for Australian early and middle child education sector. They are not for profit organisation with a focus on amplifying the value of early learning for every child across Australia. Representing their members and uniting our sector as a force for quality early education and care. Formally known as community childcare cooperative, it's a cause we've been committed to for over 40 years. CELA's mission is to amplify early learning values throughout Australia. Community early learning amplifies a voice for all members of the sector who share a common vision, a vision where children have access to affordable quality early and middle years education.
CELA do this by amplifying, amplifying the value of quality education and care, by informing families, influencing policy makers and inspiring educators. They shine a spotlight on the sector issues and support early educators to achieve the best outcomes for their service, their staff, and their own professional development. They also support evidence based research, grassroots consultation, and common sense action. CELA is also actively uniting both community based and small providers in early childhood settings under one banner for support of community benefit and purpose before profit. CELA's services also include advocacy, sector leadership, membership support their one 800 number, learning and development, consultancy events, networking, and ECE resources.
[Screen reads, ‘How Bermagui Preschool uses AEDC data in program planning’.]
Okay, Bermagui Preschool has a longstanding relationship with CELA, who have supported us in these ways and many more. As a regionally remote and standalone service, CELA have been pivotal to our success. Although we knew about the AEDC, it was through CELA that we became aware of the importance of this data and to use it in a simple and effective way. So how does Bermagui Preschool use AEDC data to program and plan?
Change fatigue is something that a lot of early education leaders are struggling with, with changes to funding, increased expectations for accountability, documentation, political shifts, not to mention the stress of the past two years. Finding time for implementing another contextual framework, can lead to exhaustion and frustration. With many initial thoughts of being, how are we going to find time to do this?
For us at Bermagui Preschool, learning about and using AEDC data has not been a daunting process. Because most of what we are already doing meets or addresses the domains that are mentioned within the AEDC. For services, it can validate what you might already know to support enhance your planning and programming, as well as providing statistical information and content for writing, funding applications, media releases, conversations with your families, educators, and allied partners. But most importantly, it's about maximising the potential for all children in your community. The AEDC can be used in creating strategies to address children's vulnerabilities in really specific and targeted ways.
[Screen reads, ‘The AEDC Domains:
Physical health and wellbeing
Language and cognitive skills (schools based)
Communication and general knowledge’.]
At Bermagui Preschool, we agree with the AEDC's belief that investing time, effort and resources in children's early years when critical learning and development takes place, benefits children, families, and the whole community. It does require a team effort and strong connections with your children, families, community, and educators, and teachers. If your educators and teachers are well informed about what the domains mean, then when programming either intentionally or spontaneously, child initiated or teacher initiated, you can draw on those domains and understanding of children who are on track or those who may not be meeting milestones. And you can develop programs to meet those children's needs.
Our first step of the AEDC journey, was making sure that the whole team had a sound understanding of the AEDC domains. We looked at, physical health and wellbeing, social competence, emotional maturity, language and cognitive skills and communication. We attended an information session on the AEDC, becoming aware of the data and what that data meant. Discovering how the data could be used to influence our programming and improve the outcomes for children in our community.
[Screen reads, ‘What the AEDC data tells us about children in Bermagui and surrounds’. Screen shows a graph titled, ‘Percentage of children developmentally vulnerable in 2021’. The left axis reads, ‘Percentage of children developmentally vulnerable in 2021’ and is numbered zero to 25 in increments of 5. The horizontal axis shows data across: Physical, Social, Emotional, Language, Communication, Vulnerable one and Vulnerable 2. Each of these contain 4 columns. On a key above the graph, it shows; red for Australia, green for New South Wales, blue for Bega Valley and orange for Bermagui/Wallaga Lake. On average, Bermagui/Wallaga Lake measures half the percentage of Australia, New South Wales and Bega Valley, with less than 5% of children developmentally vulnerable across Physical, Social, Emotional and Communication domains. Language measures at 12%, which is higher when compared with the rest of New South Wales and Australia. Vulnerable 1 and Vulnerable 2 is approximately half of the national % with 12% and 3%, respectively.]
So what does the AEDC data tell us about the children in Bermagui and surrounds? So our staff training was a great learning opportunity, but it also provided opportunities for our staff to connect and share a common understanding of not just the AEDC data, but our children, families, and broader community. Our team followed up with further reading and research. We discussed the data at staff meetings, and we brainstormed ideas about how it could be used to put into practise. This showed us that in Bermagui, language and social competence were areas that could be improved for the children and families in our community. Although we had a general sense of this vulnerability in our community, it enabled us to target and consolidate our response to this in early education context and a collaborative community response.
The AECD results over time show that there's a decrease in the social competence, the vulnerable, and an increase in emotional maturity. We were able to use this, as you can see with the example on the screen, to increase the emotional maturity but relating it to our targeted mental health and wellbeing program.
[Screen shows a table, titled, ‘Table 2.1 – AEDC domain results over time for this community.’ All 5 AEDC domains are listed on the left-hand side, ‘Physical health and wellbeing’, ‘Social competence’, ‘Emotional maturity’, ‘Language and cognitive skills (school-based)’, and ‘Communication skills and general knowledge’. For each domain, the number of children and % is provided for children on track, at risk and vulnerable across 2009 to 2021. Significant change is shown on the right-hand side for both 2009 versus 2021 and 2018 versus 2021. Physical health and wellbeing increased in 2021 compared with 2009. Social competence increased in 2021 compared with 2009 and 2018, and number of vulnerable children decreased. Emotional maturity increased in 2021 compared with 2009 and 2021. Finally, Communication skills and general knowledge increased in 2021 compared with 2009.]
However, there was a decrease in the social competence that led us to embedding social competence elements into our existing program, as well as developing targeted programs to support this vulnerability in our community. This included strengthening our transition to school program, our Moodji farm project, our active kids sports program, we looked at a community cookbook project and other community outreach projects. All with the focus on social competence rather than the other focuses that we had initially targeted and now had embedded in our program.
[Screen shows a table, titled, ‘Table 1.7 – Teachers’ response to the question: Would you say that this child is regularly read to/encouraged in his/her reading at home.’ The table shows data for whether the child is regularly read to/encouraged in his/her reading at home under the responses: true, not true and don’t know. The answer for whether the statement is true is over 80% across years 2015, 2018 and 2021.]
The community profile adds more useful contextual information. For us, it validated what we already knew about our children, families, and community. However, we were able to use the AEDC information to create strategies to address children's vulnerabilities in very specific and targeted ways. And most importantly, maximising the potential for all children in our community. For me as the director of a not-for-profit community based preschool, and also a strong advocate for excellence in early education, I found this information extremely useful for grant writing, funding applications, media releases, and conversations with our families, educators, and allied partners. It gave me the professional tools and the words to articulate the importance of early education and provide statistical and factual information related to the weaknesses and the potentials for children in our community.
All the domains are important and relate to other frameworks. The AEDC is now integrated into our planning and program, making connections to our existing knowledge of the early years learning framework and national quality standards. When we examine the AEDC data, we look at how it relates to all these other frameworks and documents across the five learning outcomes. So while the data tells us that children in Bermagui/Wallaga Lake are doing relatively well across all domains when compared to New South Wales and Australia, we can see a focus on language and cognitive skills, was important for our service going forward. We were also aware all of the domains are important, but interdependent. So we've used this information to embed language and cognitive skills into our existing program, as well as developing targeted programs to support this vulnerability in our community. This includes our Djiringanj language and cultural program, our STEM program, and our first scientist projects. The AECD domains intersect with the early years learning framework outcomes. So we use the data for our quality improvement plan to identify areas of strength and areas of improvement against the national quality standards. All of these documents meld so well together. We can look at areas of vulnerability and match with the quality area that these domains are related to, and then link to the early years learning framework outcomes when we do our program.
So when we're devising solutions or improving practise, support, learning and development, we have a holistic approach to the information we're putting into our planning, our program, and our quality improvement plan.
So let's have a look at some examples from Bermagui Preschool. The AEDC states children learn best when they're healthy, independent, and physically ready for each day.
[Screen reads, ‘Bermagui Preschool has developed an ‘Active Kids Sports Program’ which:
introduces basic movement
develops coordination, rhythm and fitness
allows us to explore and connect with the various sports and fitness facilities and instructors within our community.’]
At Bermagui Preschool, we believe physical activity provides children with the foundation for growing independence, confidence, and satisfaction in doing things for themselves. For children to fully engage in play, they need their bodies to function and respond, so they can explore, manipulate and move effectively. A set of skills known as fundamental movement skills, allows children to make the most of physical opportunities. Children don't always automatically know how to throw, kick, run, and jump as part of their growth and development. They need to learn these basic skills in order to lead physically active healthy lives. So with this in mind, we developed our active kids sports program. Our not for profit community based service is hub of our community. And it's natural for us to form partnerships with local networks within our community. We've made connections with various sporting opportunities within our community to develop our sports program. We travel to various sports venues around the community to participate in various activities. Each session has activities targeted to different sports and skills in a really fun and non-competitive way. Our active kids sports program aims to introduce basic movement skills, including throwing, catching, hitting, kicking, running, popping, jumping, galloping, and skipping, develop coordination, rhythm, and fitness. It also allows us to explore and connect with the various sports and fitness facilities and instructors within our community. From a social competence aspect, children are connecting with the Elders in our community, making connections with sporting facilities and experts that are available to them and gaining social competence by becoming connected, engaged, and developing a sense of belonging within our local community through this program.
Our children are also developing lifelong skills and a positive attitude towards sports and fitness. The long term benefits of guided and physical play, include better outcomes later in life relating to cardiovascular fitness, healthy weight, improved posture, better sleep, reduced stress and depression, anxiety, and enhanced self-esteem, concentration and social skills. Our children are also learning about being good sports and spectators as well. And they're also having lots of fun.
Back at our preschool, we consolidate and reflect on our learning with further discussions and activities and sharing of information. This consolidates learning by reflecting on the activities and weaving in other related domains to strengthen language and cognitive skills. Those vulnerabilities that we identified through the AEDC data.
[Screen reads, ‘Social competence’. Narelle explains the programs at Bermagui Preschool that support this domain.]
While Bermagui Preschool is already well connected with the community. The AEDC data delved a deeper level of understanding of children's development at our community level. As mentioned, the data was showing that children in our community had vulnerabilities in the area of language and social competence.
In line with the AEDC data, at Bermagui Preschool we encourage children to get along with each other and to share and be confident. We have a free flow program which builds social competence, but it's very strategic with opportunities to maximise children's capacity to make autonomous choices about what they do and learn.
We've run a fun friends program, that's been embedded into our program to enhance children's social competence. Through a variety of strategic and spontaneous activities, the children engage in small group activities and role plays, group discussions, storytelling, and other play-based activities and experiences to learn about sharing and turn taking, compromising, working collaboratively, problem solving and learning to accept and respect difference and diversity.
Our art studio and art therapy program also supports children to express their thoughts and ideas, and develop a sense of self and creativity through art.
We also do a lot of social planning projects, including a recent playground development project. Where our children worked with the local council and other stakeholders to plan, design and create our town's local playground. This really empowered our children as they were the designers of the playground. And they were so proud. Children have the best ideas when it comes to playground design, and it was really important to listen to their voices.
We also worked with a group of high school students, who work side by side with our children, showing nurturing care and respect. And a beautiful co-learning where they worked together to plant out the playground with seedlings that they had grown in our Moodji Garden.
[Screen reads, ‘Emotional maturity’. Narelle explains the programs at Bermagui Preschool that support this domain.]
Stress and challenges in Bermagui experienced by many families with young children, including rural isolation, lack of interaction between some community members, high unemployment, low income, increased expensive, expense of living costs, lack of affordable accommodation and housing, limited transport, high levels of domestic violence, relationship breakdowns and divorce, as well as limited support and facilities for young families and children exist in Bermagui and the surrounding communities. These concerns have been exacerbated by impact of bushfire, floods, and COVID 19.
It's believed that children are resilient and bounce back from negative experiences. But this is not always the case, our young children have processed trauma in varied in specific ways. And without appropriate support, this could have a long term and even lifelong effect. On the surface it appears business as usual at Bermagui Preschool, but if you look a little closer, you can see pale faces, dark rings around eyes, tighter hand holding and the need for cuddles and emotional outbursts, severe separation anxiety, and the sharing of stories of fear and confusion. All these are signs of ongoing shock trauma and grief.
There's no one size fits all approach when it comes to educating and supporting children. We've developed an individual targeted project that supports each child and family to learn. Within ourselves and our community, we have the power and resilience to be strong in our own mental health and wellbeing. When our children learn this at a young age, then these lifelong skills help them with future stress, anxiety, and trauma that may present in their increasingly complex lives.
We're supporting our families and educators to develop knowledge and skills so that our children can grow up healthy and stronger. When we have strong healthy children and families, in turn our communities become more vibrant and stronger.
At Bermagui Preschool, we've created a designated therapy and counselling room to facilitate a coordinated and targeted, centralised mental health program to support children and families and educators within our community. Our project looks to support our grassroots community, focused health and wellbeing initiative that aims to strengthen emotional wellbeing, resilience, and social connectedness. This aligns with the AEDC goal to ensure that children are able to concentrate, help others, are patient as well.
The therapy and counselling room provides one-on-one trauma and resilience counselling for children, and our families, and educators. We run parent and family workshops by networking with local health professionals. We also have individual therapy for children with additional needs including, speech and occupational therapy, physiotherapy, vision and hearing screening and child psychology and behaviour support with professionals visiting our preschool.
To support the mental health and wellbeing of our children and families, we also have to look to our preschool teachers and educators. This project also included a creation of a educator and teacher retreat for the purpose of lunch breaks and respite. We have a study desk and access to a separate outdoor courtyard. Where our educators and teachers can take a break, breathe fresh air, and relax in a beautiful garden setting, with added training to increase knowledge and understanding of how to support children and families and ourselves in regards to mental health and wellbeing.
This program has been particularly valuable for our community and supported us to recover and reconnect and move forward.
[Screen reads, ‘Language and cognitive skills’. Narelle explains the programs at Bermagui Preschool that support this domain.]
For Bermagui Preschool, working intentionally to address the AEDC vulnerabilities, also involves providing opportunities for children to explore language literacy and numeracy emergently. Modelling examples for children to extend their capabilities and realise the potential in these areas and provide resources to equip parents and families to consolidate the learning at home.
We run a play based numeracy and literacy program, which is interwoven throughout our preschool program. And aligns with the AEDC aim to support children to be interested in reading, writing, to count and recognise numbers and shapes. Examples of this include utilising everyday moments to teach fundamental skills such as counting the number of lady beetles a child might find in our Moodji Garden. Which is an amazing agricultural and cultural space that we've developed in a vacant lot adjoining the preschool.
Our program is based on the children's interests. However, we look at their interests and their needs as identified through the AEDC data as well to compliment learning potentials. So it might be that a child is interested in bugs and beetles they discover in our Moodji Garden. And we use that every day moment to teach fundamental skills such as counting. However, we might extend this by using posters, songs, art of insects to stimulate language and cognitive development as well. That enhances that domain of the AEDC, which we know is specific to our community.
Our children and educators are working together to create a cookbook using produce from our Moodji Garden. And we are also developing a First Nations Science project, which incorporates traditional Aboriginal knowledge, with age appropriate science based activities, such as observation, posing questions and hypothesising. These experiences aim to further diminish the language and cognitive vulnerabilities identified in the AEDC data in our community.
Cultural competency is so important for our children. Although Reconciliation Week and NAIDOC Week and other celebrations are important to recognise, at Bermagui Preschool, these aren't standalone experiences but rather embedded into our everyday program.
We had a recent example of our winter solstice, which involved many lead up cultural activities and experiences culminating in a fire festival. Amongst many highlights, one moment stood out. One of our young Koori children found a large feather and proceeded to take it outside and explore it through movement and vocalisations. This child has many challenges, including global development delays, being nonverbal, and lots of challenging behaviour. Another little friend and I watched as the beautiful child moved in dance like movements, raising the feather above her head and looking up to the sky and calling, oh, oh. When we watched, birds started to fly past, one by one to the point where it moved beyond coincidence. The child next to me said, ‘She has the heart of the nation in her, doesn't she?’ Acknowledging the conversation that we'd had previously about the overall statement. And it really highlighted the importance of those connections with culture, and country, and showed a beautiful example of children co-teaching each other.
[Screen reads, ‘Communication’. Narelle explains the programs at Bermagui Preschool that support this domain.]
In line with the AEDC, at Bermagui Preschool, we believe in interactions that stimulate the child's developing brain and builds the foundation for their future. Opportunities for children to practise communication are embedded into our program. Time for children to tell stories, communicate with adults and peers, and articulate themselves are entrenched into our daily routines and activities. We provide a language and numeracy rich environment, which includes language and literacy activities, puppet workshops, children creating books, and our Djiringanj language program.
This commenced when Kathy Thomas, a locales Djiringanj woman from Wallaga Lake who had grown up here and went to our local primary school, visited us and worked with us to teach the local Aboriginal language. She was able to share her knowledge of traditional Djiringanj language and culture with us, and Dhurga language and culture as well. This was a great opportunity to explore our rich and wonderful local language and culture. We learned to say, walaawani, which means hello and goodbye, sing head, shoulders, knees, and toes, and other familiar songs using the context of local language as well. We were then able to extend that language program out to other experiences that the children could identify with and then things that were more unfamiliar to them as well.
We also worked with Aboriginal art learning techniques and symbols. By sharing these experiences, our young children are helping to learn the language and keep the culture alive. We were also really excited to work with local Aboriginal artist, Dennis Pitt, who was commissioned to create a mural at the front of our preschool to pay tribute to our local Aboriginal culture and heritage. Our children were able to observe and talk with Dennis while he worked. They were able to create their own artwork as well with a variety of materials that were made accessible.
By embedding Aboriginal culture in our preschool program, we're promoting friendship, harmony, recognition of difference, as well as respect, acceptance, and understanding. In this way, we can work to improve connections and outcomes for all our children. We had one beautiful spontaneous moment that arose with this experience when Dennis was retelling the story of how Captain Cook had travelled along the coast for the first time. And on seeing Gulaga, our sacred mother mountain, decided to call it Mount Dromedary, due to it looking like a camel with humps. One of our four old children was outraged upon hearing this, and protested, ‘What do you mean? Captain Cook didn't even bother to stop and have a chat with the local people to ask what the real name was?’ The emergence of advocacy and the realisation of how important connection and communication from this four year old, highlights how important these experiences are for our young children and their understanding of our world.
So let's take a moment to think about how you might use AEDC information in your service in your context. How might you engage educators to discuss and implement strategies to address the AEDC data? What type of professional development might help to improve children's outcomes in areas of vulnerability in your community? What local services, schools, and partners are available to support children's development in your community? Who can you collaborate with to improve outcomes for your children? What information might you share with schools and families about learning opportunities that your children engage with? And how might families be engaged to help them connect with the local services and support?
How can AEDC data be used to inform programming in your service while still keeping a focus on your children's interests and supporting them in identified vulnerabilities? How might your service respond to the AEDC data through programming and practice?
Using the AEDC data as a resource to analyse any trends, our team at Bermagui Preschool has identified long term and short term goals, and has used the AEDC as a guide for future plans and programs. My suggestion for any early childhood service that has not yet explored the AEDC data is, have a look at the data and reflect on whether that is what you are seeing in your local community. It's really not a daunting process, because most of what you are doing in early childhood, already meets and addresses the domains that are mentioned in the AEDC.
It really is a wonderful tool to maximise the potential for all children in your community and consolidate the amazing work that you are already doing as early years teachers and educators.
Thank you very much. And on a final note, I'd just like you to take a moment to scan the code which is on the slide here.
[Screen reads, ‘Evaluation, www.surveymonkey.com/r/cela-training-evaluation’.]
If you have a moment to please use your phone or device and complete the evaluation survey, that will be very much appreciated. Thank you for your time, everybody and walaawani..
[Video concludes by displaying the NSW Government logo.]
[End of transcript]
Peony Daniels is the Schools as Community Centre (SaCC) Facilitator at Moree East Public School. In this presentation she explains how the centre uses AEDC data to plan and implement programs that address the needs of the local community. Peony has a strong belief that every child is unique and has to be given the opportunity to find and further develop their strengths and skills. AEDC data from across the Moree Plains Shire has informed early intervention and prevention playgroup programs that cater to the needs of the children at SaCC, and their parents.
Watch 'Early Intervention and prevention playgroup programs' (15:06)
(Duration: 15 minutes 6 seconds)
[Screen reads, ‘AEDC Symposium August 2022’.
Screen reads, ‘Early intervention and prevention playgroup programs’.]
Yama. I'm Peony Daniels. I'm the schools as Community Centre Facilitator at Moree East Public School.
Before I begin with this presentation, I would like to acknowledge the Kamilaroi people, all Aboriginal nations, for caring for this land for thousands of years. When we give the acknowledgement of country, it is with an understanding that all around and within this great land is a place of dreaming. Acknowledging country is accepting a welcome to all.
Moree East Public School is a connected community primary school located in North West New South Wales and stands proudly on Kamilaroi land. We have a current enrolment of 213 students, and 87% of our student population proudly identifies as Aboriginal.
[Screen shows Peony Daniels.]
So to begin with this presentation I would like to give you the background, the initial use of AEDC data and how we use the AEDC data to plan and implement our program, how the SaCC program looks like, and the evaluation, and the outcome.
So to start off, the background. SaCC programmes are planned through consultation with the executive principal, the Aboriginal Education Officers, parent/carers, community partners, and from data analysis.
In 2019, I began using the AEDC data to broaden my planning and implement programs that justified the whole community's need. So when I looked at the 2018 AEDC data, I found that there was an increase in vulnerability or at risk in physical health and wellbeing, language and cognitive skills, communication skills, and general knowledge across the Moree Plains Shire.
So these are the three areas that I chose to focus on, because I found that there was a significant increase in those vulnerability in those areas.
[Screen reads, ‘AEDC results.’ Peony provides an explanation of the data.]
So if you have a look at the AEDC results for Moree Plains Shire in 2018, vulnerability in physical health and wellbeing increased from 18.5% in 2012 to 22.3% in 2018. In the same manner, language and cognitive skills, there was an increase in vulnerability from 10.1% in 2012 to 11.7% in 2018. And finally, communication and general knowledge increased from 11.9% in 2012 to 18.3% in 2018.
So there was a significant increase in this vulnerabilities in these domains. And I was looking at implementing programs and providing programs for the community to focus on these areas and support children meet these milestones. So how did I do that, or how did we do that?
Well, to look at the physical health and wellbeing, we implemented two programs.
[Screen reads, ‘Parent cooking classes with nutritionist from Northwest Nutrition’ and ‘Midwife and health initiatives’.]
So one was with the nutritionist and one was with New South Wales Health. So I worked closely with the Northwest nutritionist and we worked together and looked at what could we do to cater for these needs? And we came up with a plan and we worked on cooking classes for parents. So these cooking classes focused on healthy cooking, introducing veggies. We had budgeting, we had label reading, we had managing diabetes, we had healthy lunchbox initiatives, or how to pack healthy lunchbox, and just simple things, day to day things that parents could incorporate into their lifestyles.
So we, the nutritionist worked with the families very closely, and she also allowed them to ask questions, and she asked them what they would like to learn, what they would like to change, and what was stopping certain people from not wanting to try some new food or try something new. And she worked very closely with the families, and the parents, and the carers to cater for their needs.
And these cooking classes were quite successful. We had increased interest in these cooking classes. We had parents/carers who have never cooked, starting to cook and bring meals into playgroup. We even went ahead and won the Reconciliation Cookoff in 2018, and parents who were attending the cooking classes were very proud of their achievements. And we could see a change in the lunch boxes, and we could see a change in the way they approached cooking, and budgeting, and managing food, base state in different areas of nutrition.
So from this initiative, the school also started the cafeteria initiative where all the children who attend school get a hot meal for $1 a day. So I won't go too much into the cafeteria initiative, but these all started from the cooking classes and the interest that the parents showed in these cooking sessions.
So that was one program. And then the health initiative. So we had different health professionals come and visit our playgroups and talk to our families. We had mid midwife visits, which were quite regular. They were coming and talking to parents and addressing their questions. They encouraged them to go and see the midwife regularly. And we used the school as a bridge between the community and health, or the school and health, and it was just really lovely to see that connection happening. And we had dental visits, we had nutritionist visit, we had hearing visits. It was just having all these health professionals coming to the playgroup and having small talks and just explaining the importance of each of these initiatives was quite important for parents to understand and see.
So secondly, for the language and cognitive skills, how does the SaCC program look like? How do I cater for those needs?
[Screen reads, ‘Language and cognitive skills, with weekly developmental skills focus’. Screen shows a program that Peony explains.]
So this is a program that I do every term. So each week we focus on one developmental skill. And so for an example, if the focus was on language skills, then everything that I did throughout the day for that playgroup would focus on that skill mainly. So the activities, the reading activity, the craft activity, the activities that I put outdoor, indoor, everything has the main focus on that developmental area that I'm focusing on. And then, even though I had one focus for the children, there was also a focus for the parents every week. So some weeks it's the health visits, some weeks it's collecting surveys from parents as to what they would like to see in playgroup, some weeks it's something different for the parents to do, like we had, we have weaving classes sometimes where some ladies from Centre Care would come in and teach parents to make do, some earrings for themself or weave some baskets. It's each week we have something different for the parents. And then we have specifically, developmentally focused activities for children.
So this is how the programme looks like.
[Screen shows a program for Term 2 Weeks 2 to 8. It is broken up into ‘child learning/engagement’ and ‘Parent or community learning/engagement’. Below these are a focus area, details, data collected and other important links.]
And the programs are linked to the earliest learning framework so that I could see how it all links, and how I'm trying to link my activities to EYLF and justify the program.
[Screen reads, ‘Language skills – Speech focus playgroup’. Peony explains the initiatives summarised on screen.]
So language skills. So to focus on the language skills, we had a speech focus playgroup. So we had a speech pathologist run the playgroup. So the whole program was planned by her, I supported her, but she would have all the activities, the group time, everything was planned by her, and she had a specific focus every week. And she spoke to the parents and she was, she'd explain importance of speech sounds, reading with children, speaking with children, just little information, but they were very valuable information for parents. And it also allowed the parents to come and ask questions from the speech pathologist without feeling the pressure of going in for an assessment.
So for a lot of parents taking that first step or accepting that their children need support is the hardest part. So instead of straight away going and trying to get a referral, and waiting on a waiting list, they were able to come in to the playgroup and have a chat with the speech pathologist and get an idea of what they had to do, where they had to go next, which was a subtle way of getting them in, and for them not feeling the pressure of having to go through the whole stress of getting assessed or being on a waiting list to go and see the speech, or even acknowledging that, okay, I need to see someone.
So these speech focus playgroup supported parents and carers with information and assessments. The speech pathologist was able to give out some referrals for some families, she was able to support some families with NDIS support, and with some families with early intervention, referral to OT, and she also went ahead and worked alongside with the Early Years teachers for transition to school program.
And these speech playgroups have been highly successful, we had really increased numbers. So because we had high interest, we have been continuing these playgroups every term, twice a year. Sorry, yeah, twice a year, so we have it for five weeks every term.
[Screen reads, ‘SACC Evaluation’. Peony explains the points summarised on screen.]
So the evaluation, so to look if the programs that we are doing are making a difference or if we had to improve more, I look at the best start data, I looked at the AEDC data from 2021, parents surveys and feedback, speech pathologist assessments, observations, and assessments that I take during playgroup, and transition to kindergarten.
So in term three and four in transition to kindergarten programs, I take observations and assessments, and then I look at, okay, what can I do to further improve my programs? What do I have to focus more on? So when I look at certain areas, I think, okay, I haven't looked at this area and I think we have to work on this area, for an example, coming back from COVID, I found that a lot of children had very poor muscle tones because they've been so focused on using the iPad and probably doing a lot of games in isolation, just even holding a pencil or playing with play dough was so hard for children to get used to.
So that was something for this year that I worked on, I've been getting some support from OT to implement some programs in my playgroup. So things like that, I learned from the transition to kindergarten groups in term three and four, and then I implement my programs the following year to cater for those needs. And then I also go on the following year into kindergarten and support those children one day a week with whatever areas of support that they need.
[Screen reads, ‘Moree East Public School SACC Outcome Summary.’ Peony provides an explanation of the data.]
So finally, outcomes. So we've had a increased playgroup attendance from 2017 to 2022. I could proudly say in 2017 we had seven to eight attendance, children attend playgroup, and in 2022, we are looking at 32 children attending playgroup. We've had to extend our outdoor area to cater for these needs, because we didn't have enough room.
And there is a decrease in vulnerability, in physical wellbeing, language and cognitive skills, communication skills, and general knowledge across Moree Plains Shire. And this was taken from the 2021 results. Increased number of SaCC playgroups from 2 in 2017 to 4 in 2022. Again, this is because there's been an increased community need for early childhood services and playgroup in the community. And we've had increased partnership with government organisations, and non-government organisations, and we've had more and more organisations wanting to partner with us to work together to meet these development milestones for children.
And I believe that the AEDC data has really helped me focus on certain areas and work towards meeting an outcome. And I will continue to work with AEDC data, and surveys and observations, to further improve outcomes for children. Thank you very much.
[Video concludes by displaying the NSW Government logo.]
[End of transcript]
Research in action
In this session, stories from Western Australia, Tasmania and Queensland provide examples that highlight how schools, communities and early childhood services drew from observations in their AEDC data to developing initiatives, partnerships and conversations that support development in areas where they had more vulnerabilities. These stories provide examples of the type of actions that can be initiated in response to AEDC outcomes.
Watch NSW AEDC State Co-ordinator, Mary Taiwo, introduce 'Research in Action – stories across Australia' (1:23)
(Duration: 1 minute 23 seconds)
[Screen reads, ‘Mary Taiwo – NSW AEDC State Coordinator, Department of Education’. Screen shows Mary inside an office with a child’s painting in the background.]
Hello everyone, my name is Mary Taiwo from the Department of Education. I am AEDC NSW’s State Coordinator.
This morning I am joining you from the land of the Darug people and I’d like to acknowledge Aboriginal elders past, present and emerging.
I’m here to introduce to you stories from across Australia, as part of the AEDC NSW research symposium.
Through these stories we are going to see how various stakeholders moved from observation to action. Wee have provided some reflective questions as part of the attendee pack so that you can engage more effectively with these stories. You might want to download that and have it in hand while you engage with the stories.
While watching these stories, pay attention to how various schools or communities moved from observation in the AEDC results to action. Pay attention to what factors impacted the decisions they made, which of the AEDC domains did they focus on and why? Also, what kind of partnerships were formed and who were the stakeholders they engaged with.
You might have tried something similar, or you might be thinking of trying something similar? Probably get some inspiration on what you could do, based on your AEDC outcomes.
Either way, I hope you enjoy the stories, and you get the best out of it. Thank you.
[Video concludes by displaying the NSW Government logo.]
[End of transcript]
Where to now
AEDC NSW has repurposed and adapted previous AEDC resources, videos, and professional learning sessions to provide an interactive and engaging learning that informs all stakeholders. Each module focuses on specific aspects of the AEDC and in some instances, targets specific practitioners to meet their specific practice needs.
Senior Research Fellow
National Drug and Alcohol Research Centre and the School of Population Health
School of Population Health
Principal Data Analyst
ECE Data and Research
Data and Research Officer
ECE Data and Research
Early Learning Advisor
NSW Department of Education
Assistant Principal Learning and Support
Albury Principal Network
Schools as Community Centre Facilitator
Moree East Public School