Investigators' Blog

How we can make science education more equitable

How we can make science education more equitable

8 November 2021

Te Pūnaha Matatini was a natural home for Dr Steven Turnbull to complete his doctoral project on tertiary science participation in Aotearoa New Zealand.

Equity in science participation is central to Te Pūnaha Matatini’s ethos, and so is Dr Steven Turnbull’s distinctly transdisciplinary approach. For his PhD in Education, Steven combined quantitative analysis of large-scale administrative student records with sociological theory and qualititative analysis of interviews to explore why students chose to engage or disengage from science education.

Using these methods, he explored disparities in science education and created a theoretical model showing how we can make the field of science education more equitable.

Steven was supervised by Te Pūnaha Matatini Principal Investigators Dr Dion O’Neale and Dr Kirsten Locke.

“Steven’s thesis was ambitious in scope, application and methodology,” says Kirsten. “The blending of qualitative and quantitative research approaches is not for the faint-hearted and is notoriously difficult to correctly balance. On this point, Steven’s thesis is exemplary.”

Steven completed a Bachelor of Arts in Education and Psychology, before pursuing postgraduate research in Education, culminating in this PhD project. He has been working with Dion since he did a summer scholarship in Physics during his undergraduate study.

Throughout his PhD Steven was involved with Te Pūnaha Matatini Whānau, and is a regular participant in Te Pūnaha Matatini’s Annual Hui.

“Steven’s PhD is a perfect example of the sort of transdisciplinary research that Te Pūnaha Matatini has enabled,” says Dion.

“While Steven’s thesis was a substantive academic piece of work, throughout his research there was a continuing focus on applications and outcomes that could bring about positive change in STEM education at both a systemic level and for individual students.”

In his thesis Steven analysed data obtained from Aotearoa New Zealand’s Integrated Data Infrastructure (IDI) about students studying STEM subjects in Aotearoa New Zealand. He used this data to identify trends in science participation through a novel method of network analysis.

This data was complemented by a survey of science students, followed by in-depth interviews to gain more insight into the human dimension to education engagement.

Steven then interrogated his findings through a theoretical framework based on the sociological work of Pierre Bourdieu.

“Steven is the very first person to ever collect and analyse a decade’s worth of NCEA science data through the Integrated Data Infrastructure (IDI) at Stats NZ,” notes Kirsten.

“The analysis that Steven performed with this enormous data set enabled an evidence-based exploration of exactly what was happening with secondary students in their subject selection and the inequities that occur through students turning away from science credits such as physics that could lead to university education.”

“If Steven had stopped there, the thesis would have been an excellent piece of work. However, the truly innovative and astonishing element is how Steven framed and dealt with this comprehensive and thorough data collection approach in relation to the theoretical work of Pierre Bourdieu.”

Steven is now using the quantitative and qualitative skillsets developed in his thesis to address inequities present in existing sources of individual-level data as a postdoctoral research fellow on Te Pūnaha Matatini’s COVID-19 modelling team.

He says that “being in a place were you can contribute to mitigating COVID-19 risk in New Zealand is quite a powerful thing”.

For Steven and the modelling team, this is values-driven work. “Te Pūnaha Matatini is constantly taking an equity-based approach, putting marginalised groups at the centre of everything we do.”

 

He took foundational physics and is now teaching the course

He took foundational physics and is now teaching the course

3 November 2021

Dr Kannan Ridings teaches Tertiary Foundation Certificate and Tuākana students that the best work that they can do will come from collaborative efforts.

Dr Kannan Ridings (Rongowhakaata) struggled at high school – until he discovered science.

“In one of the first tests that we had for science at high school I ended up getting one of the top marks in the class. It just seemed to come naturally to me, and that sparked quite a bit of interest.”

“As I went through high school I became more interested in physics. I remember in one of my classes the teacher said that nothing can go faster than the speed of light, and I thought ‘wow that’s interesting, why is that?’”

“After high school I enrolled in the Tertiary Foundation Certificate and managed to do well enough to get accepted into a Bachelor of Science. I struggled quite a bit at first with studying, but in second and third year physics I hit my stride, and started getting quite good grades.”

When Kannan was taking his third year courses in physics, an inspirational lecturer started at the University of Auckland: Professor Shaun Hendy.

“Shaun was teaching a particularly interesting course about condensed matter physics, and he was one of the best lecturers I’ve had. I was continuously asking questions and being annoying. Shaun went on to become my PhD supervisor in computational materials science.”

“When I first met Shaun was also when Te Pūnaha Matatini was first funded. I remember having some conversations with him about using innovation as a way to improve New Zealand’s economy and move away from reliance on agriculture. Those were some interesting ideas to be exposed to.”

As Kannan was in the final stages of his PhD, Shaun invited him to work on our COVID-19 programme. “One of the things which was great about joining that programme was that it was a team of great scientists, mathematicians and modellers,” says Kannan. “Being in a team-based environment was quite different for me.”

“Working on the COVID-19 programme taught me that a lot of the best science happens when you have not just an individual working on something, but when you get teams of people. The best projects and the best results come from collaboratively working together.”

Kannan is now teaching the same foundational physics course that he took at the University of Auckland all those years ago. He is also a Tuākana mentor, offering academic support to Māori and Pacific students throughout their undergraduate experience.

“Teaching foundational physics has been a rewarding experience. I think that some of the students find it inspiring that somebody who’s done the Tertiary Foundation Certificate before is now teaching them.”

Working in an interdisciplinary environment has exposed Kannan to a range of different methods, techniques and styles of science that he is excited to apply as his career progresses. He teaches his students that acquiring a wide breadth of skills will make them very employable, and shares his insights into what can be achieved through collaboration.

“Throughout my study and time with Te Pūnaha Matatini I’ve seen that you learn the most when you’re working as a team. An individual is not going to solve something like climate change, it’s going to involve more of a collaborative effort.”

“Being exposed to these ideas and approaches at Te Pūnaha Matatini has been one of the biggest influences in what I try to talk to my students about today.”

 

Hīkoi, kōrero and community-led restoration of ngahere in Ōtaki

Hīkoi, kōrero and community-led restoration of ngahere in Ōtaki

Haruātai Park in Ōtaki. Photo by Katerina French Armstrong.

2 November 2021

Two masters projects funded by Te Pūnaha Matatini are currently flowing together like a braided river towards creating communications to support community-led environmental restoration in Ōtaki.

Design student Katerina French Armstrong (Tūhoe) and science in society student Vicky Gane have been exploring how to communicate the value of reforestation in Ōtaki in very different ways.

Katerina’s project connects kaupapa Māori and spatial narratives to navigate community-led environmental restoration, while Vicky’s project measures the environmental effects of tree planting along the Ōtaki River.

Friends of the Otaki River have been carrying out replanting and restoration along a section of this river for over two decades. Associate Professor Rhian Salmon often visits this beautiful reforested area with her students, and was recently struck by how little she knows about the effect that planting trees has on the environment.

 

 

A tree planting at the Ōtaki River. Photo by Katerina French Armstrong.

Rhian had a vision for creating a designed, living, growing science communication project that could tell visitors about how much carbon particular trees were absorbing, and how that relates to their climate impact.

She joined forces with designer Jo Bailey and they decided to approach the project from a transdisciplinary angle, bringing together a design student and a science in society student. They also realised they needed the help of Associate Professor Cate MacIinnis-Ng, to contribute her immense knowledge about trees.

For Te Pūnaha Matatini investigators Rhian, Jo and Cate, this is an exciting exploration into deliberately working transdisciplinarily, bringing together science communication, design, ecology and mātauranga Māori. The overall project also tests institutional boundaries, with Rhian based at Victoria University of Wellington, Jo at Massey University, Cate at the University of Auckland, and funding from Te Pūnaha Matatini.

“The thing that I love is that Kat has taken a big picture approach and looked into what the land used to look like in Ōtaki and how colonisation, politics and human presence have affected it,” says Rhian. “And then Vicky’s looking at the actual trees.”

Katerina currently plans to produce an augmented reality app that shows how key landscapes around Ōtaki looked in the past, and how they could potentially look in the future. Alongside Jo, she has supervision and guidance from artist Associate Professor Huhana Smith (Ngāti Tukorehe, Ngāti Raukawa ki Te Tonga) at Massey University.

“Aotearoa’s colonial history, rapid deforestation and land alteration has significantly changed the face of our whenua, and the relationship between tangata and the ngahere,” says Katerina. “I grew up beside the Tararua Range and saw deforestation happen right outside my window. That’s the point that I could relate to, so I went with that.”

 

 

The Tararua Ranges tower above Ōtaki. Photo by Katerina French Armstrong.

Vicky is using allometric equations to calculate the biomass of specific trees, five-minute bird counts and pitfall traps to understand the biodiversity of the area, and analysis of soil to understand its carbon content. She is co-supervised by ecologist Associate Professor Stephen Hartley at Te Herenga Waka Victoria University of Wellington.

“I haven’t done that kind of sampling before,” says Vicky. “I come from a conservation biology background, but my main focus before now has been on fauna rather than flora -and definitely not on soil, so I’m learning a lot of new stuff.”

The outcomes of both projects will be co-designed with the local community, and are intertwined in a way that Katerina and Vicky compare to a braided river.

 

 

Designing the projects was a collaborative process. Photo by Katerina French Armstrong.

A central methodology for the two projects is meeting each week in Haruātai Park for a walk and kōrero with Watene Kaihau from local iwi Ngati Raukawa ki te Tonga.

“It’s a co-design process with all the people that we’ve been meeting along the way,” explains Katerina. “This is a new way of working for me, because as a spatial designer I’m used to being handed a brief with set parameters. This project has been really rewarding because it feels a lot more meaningful to the specific site.”

“Our projects connect in interesting ways,” says Vicky. “Because I have been coming along to a lot of meetings with Katerina to talk to the locals about the area, I’m being informed by what the area was like originally, people’s connections to the land, and the history of the area.”

“I’m keeping all that in mind when I’m thinking about the measurements I’m doing. When I come to the next stage of communicating my findings it won’t just be the scientific benefits of the site, it will be how it sits in the wider historical landscape and the community.”

The results of the overall project are likely to ask questions as much as proffer answers, and Jo hopes that they will stimulate conversation.

“The great thing about this project is that it’s taken on a life of its own,” concludes Jo. “We’ve let it fly and it’s flown off and transformed in this really beautiful way.”

 

Modelling the August 2021 COVID-19 outbreak in New Zealand

27 October 2021

 

  • We use a branching process model to simulate the Auckland August 2021 outbreak through to early January 2022, including the effects of increasing vaccine coverage by age group and time.
  • Based on vaccination data and bookings for the Auckland metro region, we estimate that vaccination reduces the model reproduction number by approximately 67% relative to an unvaccinated population by early January 2022.
  • We assume that Alert Level 3 controls are held in place and that the effect of these controls does not diminish over time. Effective contact tracing capacity is set at 1,000 active cases.
  • In low-transmission scenarios, vaccination in tandem with sustained alert level restrictions is sufficient to bring Reff <1 in November. These scenarios generally lead to case numbers that are likely to be manageable within existing health system capacity.
  • In high-transmission scenarios, vaccination and current alert level restrictions are not sufficient to bring Reff <1 during 2021. These scenarios generally lead to case numbers that would place extreme demands on health system capacity.
  • In the high-transmission scenario, an effective two-week Alert Level 4 ‘circuit breaker’ in early November followed by a return to Alert Level 3 can significantly reduce demand on the health care system through to the beginning of 2022.

Links

Preliminary estimates of hospitalisation numbers for the August 2021 outbreak, assuming we stay in Alert Level 4

26 October 2021

Report provided 1 September 2021, this version published after internal peer review 15 October 2021

We use the contagion network model to project case numbers and thus hospital and critical care numbers for the current Auckland outbreak of August 2021, with current vaccination coverage.

The simulations used here model spread though a population with the demographic composition for Auckland. Hospitalisation rates are then shifted to account for the case data from the current outbreak, where the majority of infections to date are Pasifika, for whom the hospitalization rate is around 2.7-3 times higher.

 

‘Phased transition’ to phase transition: The network consequences of reconnecting

22 October 2021

Report delivered 10 September 2021

As Aotearoa New Zealand, and specifically Auckland, responds to the ongoing outbreak of COVID-19 that began in August 2021, we seek to explain and explore how changes to Alert Level restrictions may impact on the network of interactions on which COVID-19 is spread.

By representing Aotearoa New Zealand as an interaction network, we can investigate how changes to patterns of interactions between individuals translate into structural network changes that affect potential transmission pathways.

We use the Populated Aotearoa Interaction Network (PAIN), a synthetic network representing Aotearoa New Zealand, to illustrate how moves such as changing Alert Levels can affect the number of interactions that individuals will share and the expected size of largest connected component in the network. This combines analysis of the empirical interaction network with some estimates from network science for the level of connectivity in the interaction network for different scenarios of interactions outside the home and workplace.

A key finding of this report is that only a small increase in the number of connections between individuals from different dwellings (an increase from around 10% to around 20% of the number expected at Alert Level 1) is sufficient to increase the size of the largest connected component of the population who could be reached though transmission by a factor of 15; from around 90,000 to over 1.4 million.


Modelling for transport policy interventions

Modelling for transport policy interventions

19 October 2021

Julie Mugford is applying the skills that she learned through her doctoral project with Te Pūnaha Matatini to a career across the public service.

As she entered the final year of her PhD in 2020, Julie Mugford spotted an advertisement for a role with the Ministry of Transport.

Julie had just completed an internship with the Ministry of Social Development, to see whether she enjoyed working in the public sector. She had found it a good fit, and when she saw a job available with ‘agent-based modelling’ in the description, she jumped at the chance.

From May 2020 to September 2021, Julie worked as a data analyst on the team that is creating an agent-based model of the Aotearoa New Zealand transport system.

“It has the whole New Zealand transport network,” explains Julie. “All the roads and public transport options, cycleways and footpaths. Then it has a population of typical New Zealanders with their activities that they want to do during the day, such as going to school or to work.”

“They decide what time of the day they’re going to go and what mode they’re going to use. The aim of the model is to be able to change policy settings – for example, road pricing – and see what affect it has on transport behaviour and assessing the social and environmental impacts of such changes.”

This is new territory for transport policy in Aotearoa New Zealand. Small detailed modelling tasks and larger scale aggregated modelling are already in use, but Julie is not aware of any agent-based modelling being used here. She notes that this approach has already been successfully applied in London, Melbourne, and some European countries.

Julie’s PhD project in applied mathematics looked at citizen science, where members of the public help scientists gather and analyse various forms of information. The central question of her project was whether scientists could get useful insight out of noisy, biased citizen science data.

She worked with her Te Pūnaha Matatini supervisors to develop methods to improve the reliability of data collected or analysed by members of the public through platforms like iNaturalist.

Being involved in Te Pūnaha Matatini and Te Pūnaha Matatini Whānau was the highlight of Julie’s PhD experience.

“Te Pūnaha Matatini is full of so many amazing people,”she says. “It was a welcoming environment, and the interdisciplinary focus of Te Pūnaha Matatini added more depth to my PhD than I could have ever imagined when I signed up to a PhD at the University of Canterbury School of Mathematics and Statistics.”

She says that there was always a lot of variation in the speakers and activities that the Whānau organised, and serving as the chair was a great opportunity to develop leadership experience while studying.

Julie is enjoying working in the public sector and plans to explore working at different ministries over time. She recently continued this journey by accepting a role as a Senior Analyst at the Ministry of Health.

“I like working in the public sector. It’s really great how there are these big problems that I can work on and they actually require all the experience that I’ve gathered from my education.”

 

Estimates of new onset of COVID-like illness, symptomatic population, and testing rates

18 October 2021

Using the FluTracking survey data for 2021 up until the week ending 29 August 2021, we can estimate the weekly incidence (new onset) of COVID-19-like symptoms within different age groups and different parts of the country. We use this to produce an estimate of the newly symptomatic population, and combine this with current testing data (up until 1 September 2021) to estimate how many people with new onset of symptoms (in the past seven days) would have been tested for COVID-19 through time.

  • Weekly incidence rates for any two or more COVID-19-like symptoms (CLI2+) in the week ending 29 August, 2021 was 6.7% for under 5s, 3.1% for 5-19 year olds, 3.3% for 20-64 year olds, 1.9% for 65+.
  • Weekly incidence rates for any one or more COVID-19-like symptoms (CLI1+) in the week ending 29 August, 2021 was 7.1% for under 5s, 4.8% for 5-19 year olds, 5.7% for 20-64 year olds, 3% for 65+.
  • New onset of illness, especially among pre-school and school age children has seen a large drop. This matches the declines seen in earlier Alert Level changes when schools were closed (Alert Level 3 and 4).
  • Despite the drop in testing seen in many regions, the lower incidence of illness still produces high symptomatic testing rate estimates in Auckland Region DHBs across all age bands except under 5s. A number of the approaches used to calculate this find testing rates up to 100%.

These estimates have a number of caveats. First, we are assuming that the weekly incidence (new onset of symptoms) estimated from the FluTracking survey is representative across a number of different communities. Secondly, we assume that all tests without an entry in the National Contact Tracing System (NCTS) database are seeking a test due to COVID-like symptoms. Finally, we assume that people seeking tests for symptoms would have had new onset of symptoms within the past seven days (although we test the sensitivity to this last assumption in section 3.2.2). In future it would be worth using more detailed information on the reason for seeking a test, including the symptoms people seek tests for, and the time from symptom onset to seeking a test. Unfortunately this data is not available yet.

Estimates of effects on changing Alert Levels for the August 2021 outbreak

18 October 2021

Report delivered 9 September 2021, this version compiled 15 October 2021.

We use an individual-based, Aotearoa-specific Contagion Network Model (CNM) to simulate the spread of COVID-19 in the community for an outbreak comparable to that detected on 17 August 2021. The CNM explicitly simulates spreading processes and the effect of any interventions, in order to predict the spread of COVID-19. It is therefore able to avoid the need for input assumptions or external estimates of the effective reproduction number (Reff) during the outbreak.

We use this model to consider two scenarios:

  1. An intervention with parameters comparable to Alert Level 4 (AL4) is applied from 18 August 2021 onwards and remains in place for the duration of the simulations.
  2. An intervention with parameters comparable to AL4 is applied from 18 August to 15 September 2021, after which the intervention parameters are changed to match those expected for Alert Level 3 (AL3).

We complement the CNM simulations with results from a Branching Process Model (BPM). We use this to simulate scenarios where an Alert Level change on 16 September 2021 results in a multiplicative increase of Reff of factors of 1, 1.5, 2, or 3 times that estimated during AL4.

After 60 days at AL4, it is predicted that almost all trajectories will be either eliminated or contained (i.e. all cases are either in quarantine or isolation). In contrast, only a few trajectories are eliminated or contained for the optimistic and pessimistic AL3 scenarios. In the former, many trajectories exhibit suppression like behaviour, remaining at low numbers (under 20 new cases per day) or growing only slowly.

The pessimistic AL3 scenario shows a growing number of daily new cases for the majority of trajectories. The pessimistic AL3 scenario also suggests that it would initially be difficult to distinguish between uncontrolled growth and suppression or elimination like behaviour – it takes approximately another 10 days post-deescalation before the growing trajectories start to become distinguishable.

 

Making a global impact in predicting and preventing pandemics

Making a global impact in predicting and preventing pandemics

11 October 2021

Professor David Hayman made a global impact in 2020 with his contributions to the report on biodiversity and pandemics by the Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES).

David Hayman is an epidemiologist and Principal Investigator at Te Pūnaha Matatini who uses multidisciplinary approaches to address how infectious diseases are maintained within their hosts and how the process of emergence occurs.

Dave has spent a long time working on emerging infectious diseases and bats, making him a natural candidate for Aotearoa New Zealand to put forward when the Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES) put out a call for nominations for an expert panel to produce a report on the interactions between biodiversity and human drivers of disease emergence.

The report on escaping the ‘era of pandemics’ was produced at pace during a week-long virtual workshop to review the scientific evidence on the origin, emergence and impact of COVID-19 and other pandemics, as well as on options for controlling and preventing pandemics.

Dave now sits on the One Health High Level Expert Panel (OHHLEP), a high-level expert panel that gives advice across four international agencies: the World Health Organization, the World Organization for Animal Health, the Food and Agriculture Organisation and the United Nations Environmental Programme.

He says that the IPBES report has been influential across these agencies, and is often referred to. “We are a high level expert panel that provides expertise and advice to these major global organisations about how they can work better together,” he says. “And I think the IPBES report has actually influenced that.”

The IPBES report has been an important step in these four agencies coming to terms with the complexity and interrelatedness of disease and the environment, and they are recognising the need to address these issues in a transdisciplinary way.

“There’s a lot of things from Te Pūnaha Matatini and working in Aotearoa New Zealand that influenced my contributions to the report. There’s lots I’ve Iearned from Te Pūnaha Matatini about style of working and things like respect for Māori and Indigenous knowledge.”

Dave describes himself as both a pessimist and an optimist as we face a future of increasing pandemics and the effects of climate change.

“It can seem all bad,” he says. “But on the plus side a lot of the drivers for climate change, biodiversity crises and extinction crises are the same as the things that are driving disease emergence. So we can potentially have win, win solutions.”

“We can look at things like reducing industrial-scale trafficking of wildlife or agricultural encroachment into rainforest, both of which are bad for the environment and may also be bad for human health.”

“You can potentially reduce one risk and improve things in another way.”

Dave concludes that tackling these issues will require quite big societal changes, but “what COVID-19 did show is that you can do large-scale stuff. You can shut down whole countries. I’m not saying that’s a good thing, but it showed us the scale and pace at which societies can change and adapt.”