Module 7: Te Whakamahi Pūrongo (Data Driven Leadership): This module focuses on using data effectively to inform decision-making, assess progress, and drive continuous improvement.
“He aha te take? He aha te pūtake?”
“What is the cause? What is the root cause?”
Module Objectives:
- Understand the importance of data-driven decision-making in education.
- Identify and collect relevant data to inform school improvement initiatives.
- Analyse and interpret data effectively to identify trends, patterns, and areas for improvement.
- Use data to inform and evaluate school programmes and initiatives.
- Communicate data effectively to stakeholders, including teachers, students, parents, and the wider community.
- Develop a data-driven improvement plan for a specific area of school focus.
Data are crucial for improving student achievement. By revealing gaps in student learning and instructional practices, they guide teachers and leaders in identifying areas for improvement and tailoring instruction to meet individual student needs.
However, data alone do not provide solutions. They serve as a valuable tool for understanding student learning and informing decision-making. Interpreting data is paramount; it involves uncovering the ‘story behind the numbers’ by identifying patterns and relationships. This process requires ongoing analysis, reflection, and the collection of further evidence to refine understanding and inform continuous improvement.
Types of Data:
- Demographic data: Information about students, staff, and the school community.
- Student achievement data: Standardised tests, classroom assessments, and student work samples.
- Perceptions data: Information gathered through surveys, questionnaires, observations, and student voice.
- School processes data: Information about programs, classroom practices, and assessment strategies.
When gathering data, focus on relevant information that serves a specific purpose. Avoid collecting excessive data, which can be time-consuming and difficult to analyse.
While student achievement data provides valuable information about outcomes, it doesn’t explain the underlying causes. To understand these, utilise formative assessment data, classroom observations, student voice, and other relevant sources.
Analysing Data:
Start by posing a specific question about your data, focusing on differences, gaps, or the impact of teaching practices. Look for unexpected findings and identify patterns, trends, and categories.
Avoid jumping to conclusions; explore the data deeply, considering multiple perspectives and questioning your assumptions.
Evaluate data quality using the 4 Cs: Completeness, Consistency, Comparison, and Concealed information.
Create a concise data overview and share it with colleagues to gain diverse perspectives.
Generate inferences and potential explanations, remembering that correlation does not equal causation.
Develop a range of data stories to identify areas for further investigation.
Recognise that data may not tell the whole story and that further data collection may be necessary to confirm findings.
Resources:
https://research.acer.edu.au/cgi/viewcontent.cgi?article=1317&context=research_conference
Task: Developing a Data-Driven Improvement Plan
- Select a specific area of school focus (e.g., literacy, numeracy, student well-being).
- Identify relevant data sources and collect the necessary data.
- Analyse the data and identify key trends, patterns, and areas for improvement.
- Develop a data-driven improvement plan that outlines specific goals, strategies, and action steps.
- Post your data-driven improvement plan on the online forum for peer feedback and discussion.
Assessment:
- Completion of all readings.
- Participation in the online forum discussion.
- Development and submission of a data-driven improvement plan.
- Demonstration of the ability to analyse and interpret data effectively.
22 Responses
As Rickson has previously noted, we are wanting to improve student achievement in reading, with a specific focus on closing the achievement gap for students who are not meeting expected levels. Due to current data at a stage where it is still being collated, I took the end of year reading data to support my enquiry for this module. Having analysed the data, I have developed a data-driven improvement plan that outlines 2 specific goals, strategies, and action steps.
Reading Achievement Improvement Plan
Goal 1: Close the Ethnic Achievement Gap
Target: Increase Pacific and Maaori students’ reading achievement by 15 percentage points within one academic year
Strategies:
– Develop culturally responsive reading interventions
– Implement targeted small group support
– Create personalised learning plans for Pacific and Maaori students
– Engage whaanau and family in learning support
Action Steps:
1. Conduct individual student reading assessments that are consistent across the school. This may require some professional development for kaiako who have less experience in these assessments.
2. Design culturally relevant reading materials and ensure all students have access.
3. Provide additional reading support. This could be an intervention program or after school program. Utilise programs that allow children to listen, read and record their reading.
4. Train teachers in culturally responsive teaching practices. Engaging with whaanau and families to further support reading in the community.
5. Termly progress monitoring and intervention adjustment.
Goal 2: Improve Early Years Reading Performance
Target: Increase Year 1 reading achievement from 16% to 50% by end of academic year
Strategies:
– enhance early literacy interventions
– implement intensive phonics programmes
– increase individualised reading support
– develop parent literacy engagement programme.
Action Steps:
1. Introduce daily targeted phonics instruction – explicit teaching/scope and sequence
2. Create reading buddy system with older students
3. Provide fortnightly/monthly reading skills workshops for parents and help support them with supporting their tamariki at home.
4. Use digital learning tools for supplementary reading practice
5. Conduct termly progress assessments
Key Performance Indicators: Increase overall reading achievement from 47% to 62%, reduce ethnic achievement disparities, improve Year 1 reading performance, increase student engagement in reading activities.
Monitoring and Evaluation: Quarterly (Termly) data review, adjust intervention strategies based on student progress, continuous professional development for educators throughout the school.
Kia ora delegates. I agree that this is the most challenging and complex task to date, however really valuable to inform decision making. Rather than post a response to each of your posts I’ll take the time to discuss your responses individually when we meet online or in person this week. I hope the module has been beneficial to you to inform future practice,
Ngā mihi nui Robert
I am a little unsure if I’ve done this properly – but here goes – this is what we have done:
At the start of this year I was Dean for our Year 12 cohort. In March I received a severe concussion and I relinquished that role and am now sharing on of our Year 12 Whanau classes with a colleague.
During this time I have been able to really focus on this smaller cohort of students and have noticed a huge correlation between attendance and engagement at school and the number of credits that our students are gaining towards their NCEA Level 2.
I decided to use this as the basis of this task (As it is something that can be used straight away to benefit the programmes we already have in place in school for our students)
I used our school attendance and tracking platform “Helix” to gather attendance and credit data.
It was noted that low attendance (below the 80% threshold the Government has set) and low credits achievement is closely linked.
From a Year 12 Whanau class of 26 students 34% (9) were sitting below the 80% threshold or very close to (one was at 80% and the other was at 81%)
The amount of credits that this cohort of students were sitting at were between 6% (the lowest by quite a bit) and 63% of the total number they needed to gain NCEA Level 2 (60 credits).
When I looked closer some of these students were entered into as many as 122 possible credits for the year.
Student voice was then gathered from this cohort.
We discussed their attendance and workload (number of credits achieved and total credits entered into). We also discussed a number of factors that were affecting their engagement at school. These ranged from family circumstances to part time jobs, enjoyment of their courses and general wellbeing.
Once data was collated we looked at each individual and came up with different plans that could support them in their NCEA Level 2 goals.
This included one or a combination of the following:
Whanau meetings to discuss attendance and credits/workload
Possibilities of having modified timetables
Ensuring students had the correct gear they needed (ie:access to chromebooks, etc)
Working together to create study plans and small student buddy groups to support each other
Ensuring students had a safe place to go to at school where they felt they could seek support when necessary (counseling, a study space, a safe chill out space, somewhere to leave gear when not needed, etc)
The providing of food if they were arriving at school hungry
Tutoring possibilities with their subject teachers, online, with buddies or an outside provider (Whanau arranged)
Career pathways so they had a realistic and relevant goal
Referral to our local Community House Youth Connector for support
Six of these students were enrolled in over 95 credits for the year, so with discussions between them, myself and their subject teachers we looked at what standards they were able to withdraw from and therefore make their workload more meaningful and not as daunting.
Myself and the other whanau teacher had 7 whanau meetings with whanau and students to discuss the findings of this data and what we can all do to support their child.
From these meetings we were able to put a number of interventions in place for these students.
These included modified timetables (for 2 students)
Parents getting a tutor for one student in one subject area (Maths)
Study plans created with clear timeframes and weekly and daily goals (for 7 students)
Follow up hui were also arranged for 5 students and their whanau to see how these measures have supported their students.
Gathering this hard data and student voice gave myself and my colleague evidence that we were then able to use when talking to whanau, subject teachers and SLT about our plans moving forward.
We were also able to work closely with our Student Support teacher to put in place and supports the school was able to provide (One student is being assessed for learning assistant support in two of their classes)
We have been doing this sort of thing through the year with our students, but this task that involved gathering the hard data made things much clearer and also gave me a clearer idea of what can be done to support our students. It also helped that we had Parent/Teacher interviews last week so a majority of the parents were already scheduled to come see us.
(I have found this a huge and rewarding task which has been impossible to keep below our normal word count! It is still very much ongoing)
The primary focus for Rachel and I at Nawton School is to leverage the school’s Structured Literacy programme to improve student achievement in reading (using my class data for now, we are slowly collecting all classroom data and waiting for post test assessment completion). The overarching goal is to accelerate the progress of all learners, with a specific emphasis on closing the achievement gap for students who are not meeting expected levels.
Data Overview and Analysis
This plan is built on a comprehensive approach to data, using multiple sources to uncover the full “story behind the numbers.”
Data Sources: A variety of data is used, including student achievement data (standardised tests, reading fluency, and spelling), demographic data (ethnicity and special needs status), perceptions data (teacher and student voice), and school processes data (programme implementation and support).
Key Findings: A baseline assessment from March 2025 revealed a significant range in student achievement. For example, in oral reading fluency, student accuracy varied widely from 89% (Student A) to 100% (Student B). The data also shows that while some students are thriving, others (like Student C, who has low scores across multiple assessments) require further investigation to understand the underlying barriers.
Data-Driven Improvement Plan
Goals The plan has two clear goals:
Accelerate Progress: To improve the accuracy and comprehension of students in the lowest quartile.
Close Gaps: To address achievement disparities found in specific demographic groups, such as Maaori students.
Strategies and Action Steps This plan outlines targeted and responsive actions to meet these goals:
Targeted Interventions: Identify priority learners based on data and provide small-group or one-on-one support (Tier 2 and 3 interventions). These sessions will focus on specific areas of weakness, such as phonics and decoding.
Consistent Practice: Ensure the school’s approach to Structured Literacy is consistent across all classrooms. This includes developing a shared rubric for assessment and providing support for new teachers.
Communication and Collaboration: Conduct “Open-to-Learning Conversations” with students to understand their perspectives and potential learning barriers. Communicate with parents (whaanau) to share data and provide strategies they can use to support their children at home.
Continuous Monitoring: The same assessment with different variations will be conducted toward the end of Term 3 to measure the impact of these strategies. The team will review this new data to evaluate progress and make adjustments to the plan in real-time.
I found your post really interesting to read. Especially the last paragraph. Communicating the data to parents is one thing, but sharing with them how they can support their students at home in a simple way is so important, so many of our whanau want to help the children but don’t feel confident enough to do this, especially the higher up the schooling system you go. Having clear strategies and examples, open evenings to share and discuss and one on one conversations can go a long way to supporting this. Then sharing the data again and showing how their support has made such an impact can also be so empowering for everyone.
As some have mentioned, this module has definitely been one that took me a bit longer to dive into, consider and reflect on. What has been beneficial, is recent discussions as team leaders about data, end of year expectations and the new curriculum change and phases. Here are my thoughts….
As others from my school have mentioned, Structured Literacy has been a core focus for the last 4 years. I have taught this in various levels, being New entrants transitioning into school, Year 1’s and now currently Year 3’s. I have noticed a HUGE and pleasing change in the data and success rate coming through the school with tamariki being able to access their sounds and reading new sounds as a whole. Others who have been teaching in year 3 for longer have mentioned how children are more competent in decoding sounds and prepared for learning comprehension strategies.
Mid year data analysis:
School – As a school 91% of students are ‘at’ or ‘above’ the expected Year Level for Reading.
Team – As a team we have 88% of students who are ‘at’ or ‘above’ their expected Year Level for reading.
This team data has been analysed and students who are ‘working towards’ or identified ‘progressing towards’ have been highlighted as children we, as a team, need to consider, monitor and work closely with. With this information team members have carefully selected priority 1 learners and learners need monitoring and extra support as to not let them ‘who may fall between the cracks.’ As new data comes in throughout the term, I will re analyse and adjust these tamariki accordingly with conversations with each class teacher to reidentify their priority learners and children who need monitoring.
Alongside this analysis we have looked closer at those who are ‘working below’ our expected year level. This is what we have found.
Of the children who are working below the expected Year 3 Level 9 are ELL, 9 are on the SEN Register and 4 are new to Hukanui school this year (2 of which are also being ELL).
Of these identified students, 5 have moved up two or more Structured Literacy Stage levels so far this year, 20 have moved up one Stage level.
Those who have not moved up a Stage (6 students) will receive enrichment in Term 3.
14 students of those who need support have received enrichment in Term 2, this includes ELLP support, SEN support and enrichment groups.
It is also important to note – 70% of Māori students are achieving ‘at’ or ‘above’ the Year 3 expectations.
100% of Pasifika students are achieving ‘at’ the Year 3 expectations.
There is a 25% disparity between European and Maori students achieving.
Our plan for improvement/movement of these tamariki and our data is to identify those who are working below or at risk of falling behind, we identified these from this data analysis. Then make informed decisions as a team as to what will benefit these learners, the teachers know what will work best for each individual. We have discussed ways of targeting these tamariki with things like enrichment, LA support, homepacks, targeted writing dictation groups, one on one sessions to preload before the beginning of the day and conversations with whanau to support learning.
As team leader I am interested to see the changes and comparison with end of year level expectations and what that will look like for our percentages. Continued collaboration and responsiveness to data will be beneficial to all learners, particularly those most at risk, in the hope’s that we can make meaningful progress.
As a Team Leader with 13 direct reports (we work in pastoral teams) I am interested in how/whether the frequency of Kaimanaaki (learning mentor) contact with their pastoral ākonga correlates to the level of subject engagement (measured in hours of online engagement). Our kura has the luxury of daily data updates, as our funding model is based on our student engagement data. Today’s data indicates that we have 131 pastoral ākonga in our team. I am aware that some of our ākonga are also involved in paper-based learning for 1 or 2 subjects if they are studying something with an external provider such as Equine studies with Tertiary Link or a Primary ITO.
I need to contact our Learning Systems team to find out how to access data from earlier in the year so I can collate ākonga engagement for periods longer than the previous 30 days. I can compare this data with the Google sheet our Kaimanaaki record their pastoral contacts in; I have a minimum expectation of fortnightly contact (we don’t have a “form time” as such, this is run on a 1-1 basis by each Kaimanaaki) for engaged ākonga and weekly contact for unengaged ākonga. Our Kura operates in a different way to F2F Secondary schools; here, the Pastoral focus is the “umbrella” under which the subjects are organised, and the Kaimanaaki effectively acts as the Form teacher, Dean, Principal’s Nominee and Careers Advisor, with our admin/systems support coming from our Head office in Wellington (e.g. NZQA results, NCEA external registration liaison). Therefore, the frequency of Pastoral contact is a key component in supporting our ākonga.
One indicator we have for engagement is a month-end check called the “non-returners” check. Any ākonga who has not submitted work or attended a face to face event/online class in that month will be flagged as NR1 (non returner, 1 month) or NR2 (non-returner for 2 consecutive months). I will be able to collate hours of online engagement and NR status for the ākonga in my pastoral team and compare this against the frequency of pastoral contacts recorded. Some of the data might be incomplete as busy Kaimanaaki have been known to record their contact notes straight into our Student Management System (like KAMAR on steroids, but not as user-friendly) and intermittently update the Kaimanaaki Google sheet. I may need to check in with some Kaimanaaki for anecdotal updates to add to the data I have been able to collect. An additional factor to incorporate will be the “enrolment gateway” category for the ākonga. Anecdotally we find that the Exclusion/Expulsion and Wellbeing gateway ākonga have more barriers to overcome before being able to effectively engage regularly with our online learning platform. One such barrier is access to a laptop to do their learning on – some of the “Te Kura as a last resort” ākonga arrive on our roll with little to no advance preparation, and they may have to apply for a laptop before they can begin learning with us. I need to contact our Student Support team for data on how many ākonga applied for & received a school laptop; this information is not widely reported so a bit of sleuthing could be needed to track it down.
Missed off my original post (couldn’t work out how to delete and add this in!): Engagement data to date (last 30 days): 12/131 ākonga are “red” status – have not logged on for the last 30 days, 18/131 ākonga are “orange” status – have not logged on for the last 7 days. 21/131 ākonga have NR1 status (nothing submitted in July) and 10 ākonga have NR2 status (nothing submitted in June & July). The NR numbers and red + orange numbers tend to decrease over the calendar month as ākonga get their current pieces of work ready to submit for marking.
Engagement and achievement was also the basis for my task. I found it interesting to gather hard data and student voice as to why this is so for my students and then together, with them and their whaua in some cases, being able to make plans to move forward.
I know this is something we all do in our pastoral roles, but having this task in mind while looking at the data and doing more of a deep dive, I found it all being more meaningful – if that makes sense?
Being a dean with a very heavy pastoral load, student well being has jumped out at me as an area of interest. Being a dean for a while now I have experienced several forms of deaning. Specific year level, vertical system and moving through years with your cohort. With being in the vertical system for the last 6 years we changed back to a system where we move through the secondary years with our cohort. I have experienced the system we changed back to, as in our kura it was the system we used before we went to vertical. The change back is a chat for another time. But I was not ready for the massive change that presented itself to me both pastorally and from a student support point of view. It has gone from being manageable to all consuming. So looking into things brought some interesting data, and concerning data especially for my Year 9’s. I investigated the referrals to our guidance team at school.
Data sources
In 2025 the has been 363 individual (249 female, 114 male) referrals to our guidance team. Year 13 – 11.5% (42 students), Year 12 – 16.80% (61 students), Year 11 – 18.45% (67 students), Year 10 – 22.3% (81 students), and then Year 9 – 30.90% (112 students). Of these 363 referrals 37 of them were student referred and 326 coming from staff. It is also worth nothing that these are students that have been seen by our guidance team. When a referral from a staff member is made the students are given the option of taking the opportunity to see our guidance team. There are a number who choose not to.
The top 6 reasons the students see guidance is for 1 – Anxiety / Depression. 2 – Stress, 3 – Friend and peer interactions. 4 – Home and family relationships. 5 – Gender identity. 6 – Racism.
Seeing these numbers at Year 9 has made me think that maybe we need to do more around developing our students sense of belonging at our kura. We do this already, however evidence suggests that maybe more needs to be done to develop a place of safety and belonging for the students.
Improvement Plan
Allowing time for whakawhanaungatanga and not just at classroom and form class level but with whanau. The intention is always to have this but again that magic word of time seems to always get in the way. Currently we allocate 2 days to the introduction of our Year 9s. There is peer support put in place with senior students. The other 3 days the students are here on their own before the rest of the school arrives is dedicated to setting up of ICT and BYOD. The data above suggests that maybe 2 days is not enough. We have a lot of feeder schools some very rural that have 1 or 2 students come to our kura. A pretty daunting place to come to a school of 1800 from a school of 50 – 100. We have 75% of our cohort from one school so establishment of belonging for these 25% of students must be and is a challenge. I think the idea of revisiting that peer support or the continued development of whakawhanaungatanga throughout the year would be worth looking into. These thoughts and data and any suggestions would need presenting at SLT and board level for any real significant action to take place. But this can and is being done at a form class level but not across the board. As currently our form time is not considered contact time.
Like I said the difference 6 years has made has been extensive and trends and expectations put on our your people through the means of social media, influencers and celebrity via technology is something I was not expecting. It seems to have put a lot more pressure on our students to just be human. This has impact on the classroom and the achievement in the classroom. Hopefully the above ideas may have an impact in the classroom by not just teachers having closer bonds with students and whanau but students having closer positive experiences with each other.
Our school has also made a lot of changes around the structure of deaning – we have since moved away from a verticle system and are now horizontal deaning. However, still tweaking the system and looking at how far through deans follow their cohort as we are an area school.
I love that you have the ability to dig deeper in the pastoral space when it comes to guidance. Does the teacher who issues the referral note down the referral reason? Is this done for every referral? For our students we don’t have this recorded – however, I can see this being a great tool!
Kia ora Rebecca, yes the teacher that does refer the student notes down what the reason for the referral is. Sometimes the teacher just refers out of concern and does not have a conversation about it and other times they do have a chat. What we have found is that most of the students that staff refer are already being seen. Yes a statement of why is done for every referral. We have a referral button we can use through KAMAR and the referral form has been designed by our guidance counsellors. It has been a good tool, as sometimes counsellors can communicate back to the teacher with a bit of feedback around what we can do to support the student in the classroom.
Kia ora Jeremy, really interesting point about the Peer Support! I’ve Deaned in a school where we had a Tuakana-teina system with suitable (not all) Year 13s being assigned to Year 9 pastoral groups and accompanying them at events such as Year 9 Camp, sports days etc. It had mixed results in form time sessions and I think could have been improved in that respect with more training & preparation for the Tuakana before the school year began. They did a fabulous job at Camp with helping each dormitory/group of Year 9s put their Final Night Skit together, and always resulted in some ongoing “insider” jokes.
I really like the idea of peer support and tuakana-teina. I have started creating little support buddy groups within some of my classes so that students can bounce off each other and am finding that generally these work really well (only if I pair or group them up properly) There is so much power to be found in these systems. It is something I am wanting to look into growing more next year when I resume my deans role. Be good to chat more about how you have done it.
Focusing on literacy, over the last few years we have introduced Structured Literacy. It is now starting to become very noticeable, as students come into Year 4, the use of Structured Literacy in the lower year levels and how this is affecting students coming through the higher year levels. Our mid year data as a school for 2025 has 91% of all students ‘at’ or ‘above’ their Year level expectations for Reading. 83% of our Year 4 students are achieving at their expected levels. This needs to be monitored to continue to identify who is at risk of not achieving as the expectations increase throughout the year.
With an 8% disparity between the data of our whole school and Year 4 level, I looked into the demographic data, student achievement data and school processes data.
Demographic Data
17% need support and 19% are progressing towards. Enrichment programmes and targeted teaching by carefully selecting our ‘Priority One’ students.
17 ELL, 12 Special Education Needs, and 5 new to the school this year.
Achievement Data
Of the students who need support, 8 have moved up one Structured Literacy Stage, 4 have moved up two Structured Literacy Stages, 4 have moved up 3 or more Structured Literacy Stages. Those who have not moved up a Stage will receive enrichment in Term 3. In particular, a group of 7.1 and 7.2 students.
Of the 28 students who are working towards their year level’s expectations, 8 have moved off of Structured Literacy since the start of the year and are now working on the comprehension and retell skills needed to be proficient at their year level.
School Processes Data
14 students who need support have received enrichment in Term 2 as well as 8 students receiving support from designated learning assistants for their ELL or SEN needs.
18 of 28 students working towards have not moved reading levels since the start of the year. These students will become our Priority 1 students. All needing a focus on retell.
With this data, the analysis will inform our next steps as a team to best target these students throughout Term 3. We will analyse the data again before Term 4 to reassess.
Over the last few years we have introduced Structured Literacy. As a school, we have set a goal to increase student achievement in Reading to 90 percent working at or above their expected levels. Structured Literacy has had great success, but we are still seeing that more needs to be done.
Our mid year data as a school for 2025 has 91% of all students ‘at’ or ‘above’ their Year level expectations for Reading. 86% of our Year 2 students are achieving at their expected levels. This needs to be monitored to continue to identify who is at risk of not achieving as the expectations increase throughout the year.
Using this data, the analysis is
o 14% need support and 24% are progressing towards. Close monitoring, targeted teaching, and enrichment support will be provided
o Monitoring 55 students stage 5 and below; 16 ELLs, 9 Special Education Needs.
o New students who have only been at Hukanui for 6 months – 6
Now we have this data, we need to identify some next steps to support these Priority 1 learners
• Reading enrichment will target Yr 2 for terms 3 and 4. ‘Progressing towards’ students 24% and ‘needs support’ students 14%.
• We will look closely at the Year 1 students who have been at school more than 6 months – target with teacher enrichment if they are below stage 4 (Data is indicating 70 students currently in this range).
• Utilise the BUZZ literacy enrichment programme in years 1 & 2 to target students for phonological awareness and phonics. This is run by Learning Assistants. Four more Learning Assistants have been trained in this programme to support our junior students. This means all junior Learning Assistants are trained in this programme.
• Support Teacher to work alongside our new teachers in Year 1 teaching structured literacy.
Next steps – As the leader of the Year 0/1 Team, alongside being in charge of transitions to school, I am continuing to enquire into how our School Reading data is affected by:
• The cut off for Year 1. At our school Year 0 starts from 1st June. This means that some students have only two terms at school before moving to Year 2.
• The increase in ELL students
• The increase in students arriving that are not school ready
• The introduction of new staff as student numbers grow – New teachers need support with school procedures, teaching strategies and assessment tools (including eTAP). This is especially crucial for the teacher that opens the last Year 1 class.
It’s genuinely great to see our school’s overall reading achievement at 91% at or above expectations. That speaks volumes about the positive impact Structured Literacy is having. Still, that 86% for Year 2 and the 14% needing support with 24% progressing towards, definitely show us where we need to keep pushing. Your proactive approach to pinpointing and helping these students is truly commendable
With fellow Growth Culture student, Mr Zach Bootten, I am currently inquiring into effective writing practice with the explicit aim of raising student achievement to 90 percent of students working at or above expected levels and to accelerate Priority One learners by using The Writing Revolution (Years 2-4) and The Writers’ Toolbox (Years 5-6).
Currently, after trials in 2024 across several classes, we have implemented these programmes across the whole school. Both of the programmes are grounded in research, and a philosophy of writing that is similar to each other. The mid-year data suggests a successful rollout, with over 90 percent sitting at or above expectation. However, there are significant areas where the team will need to look deeper.
What has led to this success?
How consistent is the approach across the school?
Have our P1 learners shifted in a positive direction? If so, what has changed?
Are there barriers for our learners? What are they?
Are our learners set up for sustained success?
Are there discrepancies between key groups (Māori, Pacifika, gender)?
Are the teachers empowered by the programmes? Have they noticed the difference?
The focus now shifts from the initial success to collecting and analysing this data. The team have created surveys for students across the school, as well as teachers to assess their own capabilities. In addition, we must now look at what are barriers that may (will) be stopping progress for some of the learners at Hukanui. These surveys are currently being created.
With that data, the subsequent analysis will inform our next steps as a team and school, as well as give us hard data to report to the BOT.
I found this Module my toughest yet, and it did inspire me to realise that this is an area that I need to work on in my role. With the current set up of Deans in my kura I struggled to find a way to find multiple avenues for data – the only direction and access I was given was through attendance.
Attendance has been a personal deaning and school wide target and something I have actively worked on across my Deaning experience and with my particular cohort I now follow.
Throughout these years I have put into place multiple processes to monitor and improve these including monitoring documents including percentages, follow ups and patterns for individual students. I have created whanau pages to share our attendance as a cohort so parents see as a whole where we are sitting. I have created clear systems to allow whanau to be a part of the attendance follow up system and have consistently kept parents in the loop with their students’ attendance. As well as this I have created intervention processes at my own level where I support students and whanau at a ‘warning’ level, reward students who are maintaining a high level of attendance and warn parents of referral.
With our current structure being about to be revised I was asked to more so evaluate my current practice to feedforward into our next steps so I utilised this module for where we are now.
In reflection the data analysis I did showed a pleasing trend. Unexplained absences have decreased by 2.7, intermittent unexplained absences have decreased by 5.1 over my two years working with this cohort. Overall female attendance has improved from 74.4 to 84.3 – thus moving towards the base line of 85, with my ideal target being 90. Overall male attendance has improved from 82.7 to 87.2 now being able to reach our base line target of 85.
Looking at this data further I have created my key target areas to increase this to 90 percent, with NZ Maori Males being key in increasing the male data and NZ Euro Females and our single Tongan student being key for increasing the female data.
Looking closer at our statistics for our current position compared to the past two years I have an increase of 31.6% of my students now sitting above 90%. And a target of 30% of students below 85% that I need to work with although still concerning this has decreased by 8.3%.
I did not have the data to look into why these students are below, however, through where I can access this is largely our whanau who have a disconnection with our kura.
As others have stated the data does not give the whole situation a fair representation of what is the cause of this?
Recognising that this reflection is incomplete, that this is only statistical evidence and more detail is needed to know where to next. As Zach my next step would be trying to access more data through student and staff voice and also looking at our own processes at kura and if there is enough follow through to support and also encourage with clear follow through these whanau to step up their own follow through with their students.
I am also keen to cross-correlate this data with achievement data to bring a full picture as to where to next with our akonga in Y11.
As mentioned this is very new to me but I find it an exciting journey which I am looking forward to continuing to utilise and grow within my own practice and hopefully my kura will support me in including this in my role further.
I found this the trickiest task so far too! Some pleasing, positive results for you! Fantastic job!
Me too Rebecca – but I found it really good to make me really look at one area and try to create workable solutions that I feel I will be able to continue with in future. Great job with what you have been doing and achieving.
I’m currently engaged in an evidence-based inquiry into writing for our school, driven by our goals to increase student achievement to 90 percent working at or above expected levels and to accelerate Priority One learners by using The Writing Revolution (Years 2-4) and The Writers’ Toolbox (Years 5-6).
Our journey began in 2024 with an investigation and professional development for these programmes, followed by successful trials in junior, middle, and senior classes. Positive trial data led to a school-wide introduction at the start of 2025. This included staff meetings to articulate the ‘why,’ along with modelling, observations, and team check-ins. My initial data analysis question: What impact have these new writing programmes had on overall student achievement since their widespread implementation, and what can we learn from that?
Looking at our mid-year data, we’ve identified a significant and unexpected finding: we’ve reached 90 percent of students working ‘at or above’ expected levels, a shift from 86 percent at the end of 2024. This trend suggests that the initial rollout of the writing interventions, combined with robust professional development, has had a broad positive impact on our overall student writing outcomes. However, recognising that data often doesn’t tell the whole story, it also doesn’t fully answer the crucial questions: “He aha te take? He aha te pūtake?” (What is the cause? What is the root cause?) of this success. It doesn’t showcase the consistency of programme implementation across all classrooms, or the precise progress and ongoing needs of our Priority One learners toward their acceleration goal. This leaves me with further questions about how to understand and sustain this impact for every student.
Acknowledging that our current data is incomplete, further data collection is necessary to gain a more comprehensive picture. My immediate focus is to gather more perception data (from student and staff surveys) and school processes data (through questions about implementation consistency and specific teaching practices). The team and I are ensuring these survey questions are aligned to uncover the most relevant evidence, particularly regarding effective pedagogical strategies and any specific barriers or successes our Priority One learners are experiencing. This in-depth analysis, combining our existing achievement data with the new insights, will allow us to explore the data deeply, generate more precise inferences and explanations, and develop a range of specific data stories. Crucially, this analysis will directly inform the development of the data-driven improvement plan for our school’s writing focus, outlining specific goals, strategies, and action steps to take to the BOT and enact our next stages of growth.